{"database": "metadata", "table": "run_metadata", "is_view": false, "human_description_en": "where technology = \"10x\" and tissue_curation_coarse = \"Sensory System\"", "rows": [[25107, "SRR25605432", "SRX21332628", "SRS18578260", "SRP454539", "PRJNA1004255", "Unique activities of two overlapping PAX6 retinal enhancers", "GSE240575", "Transcriptome Analysis", "Enhancers play a critical role in development by precisely modulating spatial  temporal  and cell type specific gene expression. Sequence variants in enhancers have been implicated in disease  however establishing the functional consequences of these variants is challenging due to a lack of understanding of precise cell types and developmental stages where the enhancers are normally active. PAX6 is the master regulator of eye development  with a regulatory landscape containing multiple enhancers driving expression in the eye. Whether these enhancers perform additive  redundant  or distinct functions is unknown. Here we describe the precise cell types and regulatory activity of two PAX6 retinal enhancers  HS5 and NRE. Using a unique combination of live imaging and single cell RNA sequencing in dual enhancer reporter zebrafish embryos  we uncover differences in the spatiotemporal activity of these enhancers. Our results show that although overlapping  these enhancers have distinct activities in different cell types and therefore likely non redundant functions. This work demonstrates that unique cell type specific activities can be uncovered for apparently similar enhancers when investigated at high resolution in vivo. Overall design: In order to define the precise cell types within the retina where the PAX6 enhancers HS5 and NRE are active  we carried out scRNA seq on eyes from NRE eGFP/HS5 mCherry zebrafish reporter embryos. With this technique  we aimed to uncover cell type or transcriptional differences between the two enhancer active populations. We dissected eyes from 48 hpf NRE eGFP/HS5 mCherry embryos and used FACS to enrich for either mCherry positive/HS5 active cells or eGFP positive/NRE active cells. Three samples for each population were processed for scRNA seq using the 10x Genomics Chromium single cell three prime gene expression technology.", null, "pubmed:37643867", null, "gfp enriched rep3", "GSM7702835", null, "source name:Eye|tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf|geo loc name:missing|collection date:missing", "gfp enriched rep3", "Cell Ranger v6.1.2 was used to perform alignment  filtering  barcode counting  and UMI counting. A custom reference genome was created for alignment using cellranger mkref  combining the Danio rerio GRCz11 genome assembly with manually annotated eGFP and mCherry sequences. Cell calling and QC: The emptyDrops function from DropletUtils was used to filter out empty droplets/barcodes not corresponding to cells Lun et al.  2019. Mitochondrial and ribosomal genes were excluded from the emptyDrops analysis to improve the filtering of droplets containing ambient RNA or cell fragments. The scater package was used to filter cells based on the QC metrics of library size  detected genes  and mitochondrial reads McCarthy et al.  2017. Cells with detected genes \u2265 500  library size \u2265 800  and mitochondrial reads \u2264 10% were retained. Within the processed dataset  mean reads per cell = 11239  and median genes per cell = 1554. Reference mapping and filtering: The SingleR package was used to annotate cell types based on mapping to the zebrafish single cell transcriptome atlas Aran et al.  2019; Farnsworth et al.  2019. Expression matrix and cell annotation data were downloaded from the UCSC cell browser http://zebrafish dev.cells.ucsc.edu; only the 2 dpf data were used for mapping. Erroneously sorted cells of non retinal identity for example pigmented cell types such as melanocytes with high autofluorescence were filtered out at this stage. This was carried out to improve the resolution of clustering for retinal cell types.  Clustering and cell type annotation: Seurat v4 was used for clustering and further analysis for a total of 6 288 cells Butler et al.  2018. SCTransform was used to perform log normalisation  scaling  and highly variable gene HVG detection on a dataset consisting of the 6 samples merged into one. Standard SCTransform options were used  with regression of mitochondrial expression and cell cycle stage using \u2018vars.to.regress\u2019. We performed Principle Component Analysis PCA on the normalized counts matrix restricted to HVGs  using Seurat's RunPCA function with number of PCs = 50. To enable integration of the samples  we then used Harmony to generate PCs corrected for batch effects between libraries Korsunsky et al.  2019. The Harmony PCs were then used to perform K nearest neighbour analysis k=20 and Louvain clustering using Seurat 15 dimensions and resolution 0.6. Clusters were annotated as retinal cell types based on the highest expressed marker genes  and other known genes for each cell type  using information from the literature and ZFIN Sprague et al.  2008. Cell cycle scoring was performed using the Seurat CellCycleScoring function  using zebrafish genes homologous to the \u2018s.features\u2019 and \u2018g2m.features\u2019 genes provided by Seurat. Assembly: GRCz11 Supplementary files format and content: Tab separated values files  matrix files  Seurat object RDS file", "Eye", null, "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell 3\u2019 gene expression technology v3.1.", null, "tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf", "GSM7702835", "GSM7702835: gfp enriched rep3; Danio rerio; RNA Seq", "GSM7702835 r1", "GSM7702835", "1", "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell three prime gene expression technology v3.1.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "SINGLE", "ILLUMINA", "NextSeq 2000", null, "SRP454539", null, "loader:fastq load.py", "2707_GFP_pos_S4_L001_R2_001.fastq.gz 2707_GFP_pos_S4_L001_R1_001.fastq.gz 2707_GFP_pos_S4_L001_I2_001.fastq.gz 2707_GFP_pos_S4_L001_I1_001.fastq.gz", "fastq fastq fastq fastq", 21603309774.0, 156545723.0, "GSM7702835 r1", "0:10 1:10 2:28 3:90", "A:3960451458;C:3105338977;G:3480072824;T:3541218595;N:2033216", 10, 10, 28, 90, 3960451458, 3105338977, 3480072824, 3541218595, 2033216, "SRX21332628", "SRS18578260", "SRA1702612", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", 1, 0.94286, null, 0.14175, null, 0.78395, null, 0.51541, null, 90, null, "B", null, "usable mapping rate", "illumina", "nextseq_v2", "3prime", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United Kingdom", "2023-08-10", "Hatching", "Embryo", "Eye", "Sensory System"], [25108, "SRR25605433", "SRX21332628", "SRS18578260", "SRP454539", "PRJNA1004255", "Unique activities of two overlapping PAX6 retinal enhancers", "GSE240575", "Transcriptome Analysis", "Enhancers play a critical role in development by precisely modulating spatial  temporal  and cell type specific gene expression. Sequence variants in enhancers have been implicated in disease  however establishing the functional consequences of these variants is challenging due to a lack of understanding of precise cell types and developmental stages where the enhancers are normally active. PAX6 is the master regulator of eye development  with a regulatory landscape containing multiple enhancers driving expression in the eye. Whether these enhancers perform additive  redundant  or distinct functions is unknown. Here we describe the precise cell types and regulatory activity of two PAX6 retinal enhancers  HS5 and NRE. Using a unique combination of live imaging and single cell RNA sequencing in dual enhancer reporter zebrafish embryos  we uncover differences in the spatiotemporal activity of these enhancers. Our results show that although overlapping  these enhancers have distinct activities in different cell types and therefore likely non redundant functions. This work demonstrates that unique cell type specific activities can be uncovered for apparently similar enhancers when investigated at high resolution in vivo. Overall design: In order to define the precise cell types within the retina where the PAX6 enhancers HS5 and NRE are active  we carried out scRNA seq on eyes from NRE eGFP/HS5 mCherry zebrafish reporter embryos. With this technique  we aimed to uncover cell type or transcriptional differences between the two enhancer active populations. We dissected eyes from 48 hpf NRE eGFP/HS5 mCherry embryos and used FACS to enrich for either mCherry positive/HS5 active cells or eGFP positive/NRE active cells. Three samples for each population were processed for scRNA seq using the 10x Genomics Chromium single cell three prime gene expression technology.", null, "pubmed:37643867", null, "gfp enriched rep3", "GSM7702835", null, "source name:Eye|tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf|geo loc name:missing|collection date:missing", "gfp enriched rep3", "Cell Ranger v6.1.2 was used to perform alignment  filtering  barcode counting  and UMI counting. A custom reference genome was created for alignment using cellranger mkref  combining the Danio rerio GRCz11 genome assembly with manually annotated eGFP and mCherry sequences. Cell calling and QC: The emptyDrops function from DropletUtils was used to filter out empty droplets/barcodes not corresponding to cells Lun et al.  2019. Mitochondrial and ribosomal genes were excluded from the emptyDrops analysis to improve the filtering of droplets containing ambient RNA or cell fragments. The scater package was used to filter cells based on the QC metrics of library size  detected genes  and mitochondrial reads McCarthy et al.  2017. Cells with detected genes \u2265 500  library size \u2265 800  and mitochondrial reads \u2264 10% were retained. Within the processed dataset  mean reads per cell = 11239  and median genes per cell = 1554. Reference mapping and filtering: The SingleR package was used to annotate cell types based on mapping to the zebrafish single cell transcriptome atlas Aran et al.  2019; Farnsworth et al.  2019. Expression matrix and cell annotation data were downloaded from the UCSC cell browser http://zebrafish dev.cells.ucsc.edu; only the 2 dpf data were used for mapping. Erroneously sorted cells of non retinal identity for example pigmented cell types such as melanocytes with high autofluorescence were filtered out at this stage. This was carried out to improve the resolution of clustering for retinal cell types.  Clustering and cell type annotation: Seurat v4 was used for clustering and further analysis for a total of 6 288 cells Butler et al.  2018. SCTransform was used to perform log normalisation  scaling  and highly variable gene HVG detection on a dataset consisting of the 6 samples merged into one. Standard SCTransform options were used  with regression of mitochondrial expression and cell cycle stage using \u2018vars.to.regress\u2019. We performed Principle Component Analysis PCA on the normalized counts matrix restricted to HVGs  using Seurat's RunPCA function with number of PCs = 50. To enable integration of the samples  we then used Harmony to generate PCs corrected for batch effects between libraries Korsunsky et al.  2019. The Harmony PCs were then used to perform K nearest neighbour analysis k=20 and Louvain clustering using Seurat 15 dimensions and resolution 0.6. Clusters were annotated as retinal cell types based on the highest expressed marker genes  and other known genes for each cell type  using information from the literature and ZFIN Sprague et al.  2008. Cell cycle scoring was performed using the Seurat CellCycleScoring function  using zebrafish genes homologous to the \u2018s.features\u2019 and \u2018g2m.features\u2019 genes provided by Seurat. Assembly: GRCz11 Supplementary files format and content: Tab separated values files  matrix files  Seurat object RDS file", "Eye", null, "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell 3\u2019 gene expression technology v3.1.", null, "tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf", "GSM7702835", "GSM7702835: gfp enriched rep3; Danio rerio; RNA Seq", "GSM7702835 r1", "GSM7702835", "1", "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell three prime gene expression technology v3.1.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "SINGLE", "ILLUMINA", "NextSeq 2000", null, "SRP454539", null, "loader:fastq load.py", "2707_GFP_pos_S4_L002_I1_001.fastq.gz 2707_GFP_pos_S4_L002_I2_001.fastq.gz 2707_GFP_pos_S4_L002_R1_001.fastq.gz 2707_GFP_pos_S4_L002_R2_001.fastq.gz", "fastq fastq fastq fastq", 22413465270.0, 162416415.0, "GSM7702835 r2", "0:10 1:10 2:28 3:90", "A:4104405257;C:3220235633;G:3625448968;T:3667329471;N:58021", 10, 10, 28, 90, 4104405257, 3220235633, 3625448968, 3667329471, 58021, "SRX21332628", "SRS18578260", "SRA1702612", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", 1, 0.94239, null, 0.14234, null, 0.78338, null, 0.50616, null, 90, null, "B", null, "usable mapping rate", "illumina", "nextseq_v2", "3prime", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United Kingdom", "2023-08-10", "Hatching", "Embryo", "Eye", "Sensory System"], [25109, "SRR25822232", "SRX21332628", "SRS18578260", "SRP454539", "PRJNA1004255", "Unique activities of two overlapping PAX6 retinal enhancers", "GSE240575", "Transcriptome Analysis", "Enhancers play a critical role in development by precisely modulating spatial  temporal  and cell type specific gene expression. Sequence variants in enhancers have been implicated in disease  however establishing the functional consequences of these variants is challenging due to a lack of understanding of precise cell types and developmental stages where the enhancers are normally active. PAX6 is the master regulator of eye development  with a regulatory landscape containing multiple enhancers driving expression in the eye. Whether these enhancers perform additive  redundant  or distinct functions is unknown. Here we describe the precise cell types and regulatory activity of two PAX6 retinal enhancers  HS5 and NRE. Using a unique combination of live imaging and single cell RNA sequencing in dual enhancer reporter zebrafish embryos  we uncover differences in the spatiotemporal activity of these enhancers. Our results show that although overlapping  these enhancers have distinct activities in different cell types and therefore likely non redundant functions. This work demonstrates that unique cell type specific activities can be uncovered for apparently similar enhancers when investigated at high resolution in vivo. Overall design: In order to define the precise cell types within the retina where the PAX6 enhancers HS5 and NRE are active  we carried out scRNA seq on eyes from NRE eGFP/HS5 mCherry zebrafish reporter embryos. With this technique  we aimed to uncover cell type or transcriptional differences between the two enhancer active populations. We dissected eyes from 48 hpf NRE eGFP/HS5 mCherry embryos and used FACS to enrich for either mCherry positive/HS5 active cells or eGFP positive/NRE active cells. Three samples for each population were processed for scRNA seq using the 10x Genomics Chromium single cell three prime gene expression technology.", null, "pubmed:37643867", null, "gfp enriched rep3", "GSM7702835", null, "source name:Eye|tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf|geo loc name:missing|collection date:missing", "gfp enriched rep3", "Cell Ranger v6.1.2 was used to perform alignment  filtering  barcode counting  and UMI counting. A custom reference genome was created for alignment using cellranger mkref  combining the Danio rerio GRCz11 genome assembly with manually annotated eGFP and mCherry sequences. Cell calling and QC: The emptyDrops function from DropletUtils was used to filter out empty droplets/barcodes not corresponding to cells Lun et al.  2019. Mitochondrial and ribosomal genes were excluded from the emptyDrops analysis to improve the filtering of droplets containing ambient RNA or cell fragments. The scater package was used to filter cells based on the QC metrics of library size  detected genes  and mitochondrial reads McCarthy et al.  2017. Cells with detected genes \u2265 500  library size \u2265 800  and mitochondrial reads \u2264 10% were retained. Within the processed dataset  mean reads per cell = 11239  and median genes per cell = 1554. Reference mapping and filtering: The SingleR package was used to annotate cell types based on mapping to the zebrafish single cell transcriptome atlas Aran et al.  2019; Farnsworth et al.  2019. Expression matrix and cell annotation data were downloaded from the UCSC cell browser http://zebrafish dev.cells.ucsc.edu; only the 2 dpf data were used for mapping. Erroneously sorted cells of non retinal identity for example pigmented cell types such as melanocytes with high autofluorescence were filtered out at this stage. This was carried out to improve the resolution of clustering for retinal cell types.  Clustering and cell type annotation: Seurat v4 was used for clustering and further analysis for a total of 6 288 cells Butler et al.  2018. SCTransform was used to perform log normalisation  scaling  and highly variable gene HVG detection on a dataset consisting of the 6 samples merged into one. Standard SCTransform options were used  with regression of mitochondrial expression and cell cycle stage using \u2018vars.to.regress\u2019. We performed Principle Component Analysis PCA on the normalized counts matrix restricted to HVGs  using Seurat's RunPCA function with number of PCs = 50. To enable integration of the samples  we then used Harmony to generate PCs corrected for batch effects between libraries Korsunsky et al.  2019. The Harmony PCs were then used to perform K nearest neighbour analysis k=20 and Louvain clustering using Seurat 15 dimensions and resolution 0.6. Clusters were annotated as retinal cell types based on the highest expressed marker genes  and other known genes for each cell type  using information from the literature and ZFIN Sprague et al.  2008. Cell cycle scoring was performed using the Seurat CellCycleScoring function  using zebrafish genes homologous to the \u2018s.features\u2019 and \u2018g2m.features\u2019 genes provided by Seurat. Assembly: GRCz11 Supplementary files format and content: Tab separated values files  matrix files  Seurat object RDS file", "Eye", null, "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell 3\u2019 gene expression technology v3.1.", null, "tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf", "GSM7702835", "GSM7702835: gfp enriched rep3; Danio rerio; RNA Seq", "GSM7702835 r1", "GSM7702835", "1", "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell three prime gene expression technology v3.1.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "SINGLE", "ILLUMINA", "NextSeq 2000", null, "SRP454539", null, "loader:fastq load.py", "2707_GFP_pos_S4_L001_R2_002.fastq.gz 2707_GFP_pos_S4_L001_R1_002.fastq.gz 2707_GFP_pos_S4_L001_I2_002.fastq.gz 2707_GFP_pos_S4_L001_I1_002.fastq.gz", "fastq fastq fastq fastq", 21424338264.0, 155248828.0, "GSM7702835 r3", "0:10 1:10 2:28 3:90", "A:3928077020;C:3077672525;G:3451667186;T:3513734857;N:1242932", 10, 10, 28, 90, 3928077020, 3077672525, 3451667186, 3513734857, 1242932, "SRX21332628", "SRS18578260", "SRA1702612", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", 1, 0.9433, null, 0.14242, null, 0.78328, null, 0.52384, null, 90, null, "B", null, "usable mapping rate", "illumina", "nextseq_v2", "3prime", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United Kingdom", "2023-08-10", "Hatching", "Embryo", "Eye", "Sensory System"], [25110, "SRR25822233", "SRX21332628", "SRS18578260", "SRP454539", "PRJNA1004255", "Unique activities of two overlapping PAX6 retinal enhancers", "GSE240575", "Transcriptome Analysis", "Enhancers play a critical role in development by precisely modulating spatial  temporal  and cell type specific gene expression. Sequence variants in enhancers have been implicated in disease  however establishing the functional consequences of these variants is challenging due to a lack of understanding of precise cell types and developmental stages where the enhancers are normally active. PAX6 is the master regulator of eye development  with a regulatory landscape containing multiple enhancers driving expression in the eye. Whether these enhancers perform additive  redundant  or distinct functions is unknown. Here we describe the precise cell types and regulatory activity of two PAX6 retinal enhancers  HS5 and NRE. Using a unique combination of live imaging and single cell RNA sequencing in dual enhancer reporter zebrafish embryos  we uncover differences in the spatiotemporal activity of these enhancers. Our results show that although overlapping  these enhancers have distinct activities in different cell types and therefore likely non redundant functions. This work demonstrates that unique cell type specific activities can be uncovered for apparently similar enhancers when investigated at high resolution in vivo. Overall design: In order to define the precise cell types within the retina where the PAX6 enhancers HS5 and NRE are active  we carried out scRNA seq on eyes from NRE eGFP/HS5 mCherry zebrafish reporter embryos. With this technique  we aimed to uncover cell type or transcriptional differences between the two enhancer active populations. We dissected eyes from 48 hpf NRE eGFP/HS5 mCherry embryos and used FACS to enrich for either mCherry positive/HS5 active cells or eGFP positive/NRE active cells. Three samples for each population were processed for scRNA seq using the 10x Genomics Chromium single cell three prime gene expression technology.", null, "pubmed:37643867", null, "gfp enriched rep3", "GSM7702835", null, "source name:Eye|tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf|geo loc name:missing|collection date:missing", "gfp enriched rep3", "Cell Ranger v6.1.2 was used to perform alignment  filtering  barcode counting  and UMI counting. A custom reference genome was created for alignment using cellranger mkref  combining the Danio rerio GRCz11 genome assembly with manually annotated eGFP and mCherry sequences. Cell calling and QC: The emptyDrops function from DropletUtils was used to filter out empty droplets/barcodes not corresponding to cells Lun et al.  2019. Mitochondrial and ribosomal genes were excluded from the emptyDrops analysis to improve the filtering of droplets containing ambient RNA or cell fragments. The scater package was used to filter cells based on the QC metrics of library size  detected genes  and mitochondrial reads McCarthy et al.  2017. Cells with detected genes \u2265 500  library size \u2265 800  and mitochondrial reads \u2264 10% were retained. Within the processed dataset  mean reads per cell = 11239  and median genes per cell = 1554. Reference mapping and filtering: The SingleR package was used to annotate cell types based on mapping to the zebrafish single cell transcriptome atlas Aran et al.  2019; Farnsworth et al.  2019. Expression matrix and cell annotation data were downloaded from the UCSC cell browser http://zebrafish dev.cells.ucsc.edu; only the 2 dpf data were used for mapping. Erroneously sorted cells of non retinal identity for example pigmented cell types such as melanocytes with high autofluorescence were filtered out at this stage. This was carried out to improve the resolution of clustering for retinal cell types.  Clustering and cell type annotation: Seurat v4 was used for clustering and further analysis for a total of 6 288 cells Butler et al.  2018. SCTransform was used to perform log normalisation  scaling  and highly variable gene HVG detection on a dataset consisting of the 6 samples merged into one. Standard SCTransform options were used  with regression of mitochondrial expression and cell cycle stage using \u2018vars.to.regress\u2019. We performed Principle Component Analysis PCA on the normalized counts matrix restricted to HVGs  using Seurat's RunPCA function with number of PCs = 50. To enable integration of the samples  we then used Harmony to generate PCs corrected for batch effects between libraries Korsunsky et al.  2019. The Harmony PCs were then used to perform K nearest neighbour analysis k=20 and Louvain clustering using Seurat 15 dimensions and resolution 0.6. Clusters were annotated as retinal cell types based on the highest expressed marker genes  and other known genes for each cell type  using information from the literature and ZFIN Sprague et al.  2008. Cell cycle scoring was performed using the Seurat CellCycleScoring function  using zebrafish genes homologous to the \u2018s.features\u2019 and \u2018g2m.features\u2019 genes provided by Seurat. Assembly: GRCz11 Supplementary files format and content: Tab separated values files  matrix files  Seurat object RDS file", "Eye", null, "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell 3\u2019 gene expression technology v3.1.", null, "tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf", "GSM7702835", "GSM7702835: gfp enriched rep3; Danio rerio; RNA Seq", "GSM7702835 r1", "GSM7702835", "1", "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell three prime gene expression technology v3.1.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "SINGLE", "ILLUMINA", "NextSeq 2000", null, "SRP454539", null, "loader:fastq load.py", "2707_GFP_pos_S4_L002_I1_002.fastq.gz 2707_GFP_pos_S4_L002_I2_002.fastq.gz 2707_GFP_pos_S4_L002_R1_002.fastq.gz 2707_GFP_pos_S4_L002_R2_002.fastq.gz", "fastq fastq fastq fastq", 22542479952.0, 163351304.0, "GSM7702835 r4", "0:10 1:10 2:28 3:90", "A:4130174287;C:3235362228;G:3643457599;T:3691295761;N:1327485", 10, 10, 28, 90, 4130174287, 3235362228, 3643457599, 3691295761, 1327485, "SRX21332628", "SRS18578260", "SRA1702612", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", 1, 0.94183, null, 0.14124, null, 0.78301, null, 0.50517, null, 90, null, "B", null, "usable mapping rate", "illumina", "nextseq_v2", "3prime", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United Kingdom", "2023-08-10", "Hatching", "Embryo", "Eye", "Sensory System"], [25111, "SRR25605434", "SRX21332627", "SRS18578259", "SRP454539", "PRJNA1004255", "Unique activities of two overlapping PAX6 retinal enhancers", "GSE240575", "Transcriptome Analysis", "Enhancers play a critical role in development by precisely modulating spatial  temporal  and cell type specific gene expression. Sequence variants in enhancers have been implicated in disease  however establishing the functional consequences of these variants is challenging due to a lack of understanding of precise cell types and developmental stages where the enhancers are normally active. PAX6 is the master regulator of eye development  with a regulatory landscape containing multiple enhancers driving expression in the eye. Whether these enhancers perform additive  redundant  or distinct functions is unknown. Here we describe the precise cell types and regulatory activity of two PAX6 retinal enhancers  HS5 and NRE. Using a unique combination of live imaging and single cell RNA sequencing in dual enhancer reporter zebrafish embryos  we uncover differences in the spatiotemporal activity of these enhancers. Our results show that although overlapping  these enhancers have distinct activities in different cell types and therefore likely non redundant functions. This work demonstrates that unique cell type specific activities can be uncovered for apparently similar enhancers when investigated at high resolution in vivo. Overall design: In order to define the precise cell types within the retina where the PAX6 enhancers HS5 and NRE are active  we carried out scRNA seq on eyes from NRE eGFP/HS5 mCherry zebrafish reporter embryos. With this technique  we aimed to uncover cell type or transcriptional differences between the two enhancer active populations. We dissected eyes from 48 hpf NRE eGFP/HS5 mCherry embryos and used FACS to enrich for either mCherry positive/HS5 active cells or eGFP positive/NRE active cells. Three samples for each population were processed for scRNA seq using the 10x Genomics Chromium single cell three prime gene expression technology.", null, "pubmed:37643867", null, "mcherry enriched rep3", "GSM7702834", null, "source name:Eye|tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf|geo loc name:missing|collection date:missing", "mcherry enriched rep3", "Cell Ranger v6.1.2 was used to perform alignment  filtering  barcode counting  and UMI counting. A custom reference genome was created for alignment using cellranger mkref  combining the Danio rerio GRCz11 genome assembly with manually annotated eGFP and mCherry sequences. Cell calling and QC: The emptyDrops function from DropletUtils was used to filter out empty droplets/barcodes not corresponding to cells Lun et al.  2019. Mitochondrial and ribosomal genes were excluded from the emptyDrops analysis to improve the filtering of droplets containing ambient RNA or cell fragments. The scater package was used to filter cells based on the QC metrics of library size  detected genes  and mitochondrial reads McCarthy et al.  2017. Cells with detected genes \u2265 500  library size \u2265 800  and mitochondrial reads \u2264 10% were retained. Within the processed dataset  mean reads per cell = 11239  and median genes per cell = 1554. Reference mapping and filtering: The SingleR package was used to annotate cell types based on mapping to the zebrafish single cell transcriptome atlas Aran et al.  2019; Farnsworth et al.  2019. Expression matrix and cell annotation data were downloaded from the UCSC cell browser http://zebrafish dev.cells.ucsc.edu; only the 2 dpf data were used for mapping. Erroneously sorted cells of non retinal identity for example pigmented cell types such as melanocytes with high autofluorescence were filtered out at this stage. This was carried out to improve the resolution of clustering for retinal cell types.  Clustering and cell type annotation: Seurat v4 was used for clustering and further analysis for a total of 6 288 cells Butler et al.  2018. SCTransform was used to perform log normalisation  scaling  and highly variable gene HVG detection on a dataset consisting of the 6 samples merged into one. Standard SCTransform options were used  with regression of mitochondrial expression and cell cycle stage using \u2018vars.to.regress\u2019. We performed Principle Component Analysis PCA on the normalized counts matrix restricted to HVGs  using Seurat's RunPCA function with number of PCs = 50. To enable integration of the samples  we then used Harmony to generate PCs corrected for batch effects between libraries Korsunsky et al.  2019. The Harmony PCs were then used to perform K nearest neighbour analysis k=20 and Louvain clustering using Seurat 15 dimensions and resolution 0.6. Clusters were annotated as retinal cell types based on the highest expressed marker genes  and other known genes for each cell type  using information from the literature and ZFIN Sprague et al.  2008. Cell cycle scoring was performed using the Seurat CellCycleScoring function  using zebrafish genes homologous to the \u2018s.features\u2019 and \u2018g2m.features\u2019 genes provided by Seurat. Assembly: GRCz11 Supplementary files format and content: Tab separated values files  matrix files  Seurat object RDS file", "Eye", null, "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell 3\u2019 gene expression technology v3.1.", null, "tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf", "GSM7702834", "GSM7702834: mcherry enriched rep3; Danio rerio; RNA Seq", "GSM7702834 r1", "GSM7702834", "1", "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell three prime gene expression technology v3.1.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "SINGLE", "ILLUMINA", "NextSeq 2000", null, "SRP454539", null, "loader:fastq load.py", "2707_pos_Mcherry_S3_L001_R2_001.fastq.gz 2707_pos_Mcherry_S3_L001_R1_001.fastq.gz 2707_pos_Mcherry_S3_L001_I2_001.fastq.gz 2707_pos_Mcherry_S3_L001_I1_001.fastq.gz", "fastq fastq fastq fastq", 20161522758.0, 146097991.0, "GSM7702834 r1", "0:10 1:10 2:28 3:90", "A:3649819934;C:2958286158;G:3267504300;T:3271384686;N:1824112", 10, 10, 28, 90, 3649819934, 2958286158, 3267504300, 3271384686, 1824112, "SRX21332627", "SRS18578259", "SRA1702612", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", 1, 0.94851, null, 0.1483, null, 0.80012, null, 0.52549, null, 90, null, "B", null, "usable mapping rate", "illumina", "nextseq_v2", "3prime", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United Kingdom", "2023-08-10", "Hatching", "Embryo", "Eye", "Sensory System"], [25112, "SRR25605435", "SRX21332627", "SRS18578259", "SRP454539", "PRJNA1004255", "Unique activities of two overlapping PAX6 retinal enhancers", "GSE240575", "Transcriptome Analysis", "Enhancers play a critical role in development by precisely modulating spatial  temporal  and cell type specific gene expression. Sequence variants in enhancers have been implicated in disease  however establishing the functional consequences of these variants is challenging due to a lack of understanding of precise cell types and developmental stages where the enhancers are normally active. PAX6 is the master regulator of eye development  with a regulatory landscape containing multiple enhancers driving expression in the eye. Whether these enhancers perform additive  redundant  or distinct functions is unknown. Here we describe the precise cell types and regulatory activity of two PAX6 retinal enhancers  HS5 and NRE. Using a unique combination of live imaging and single cell RNA sequencing in dual enhancer reporter zebrafish embryos  we uncover differences in the spatiotemporal activity of these enhancers. Our results show that although overlapping  these enhancers have distinct activities in different cell types and therefore likely non redundant functions. This work demonstrates that unique cell type specific activities can be uncovered for apparently similar enhancers when investigated at high resolution in vivo. Overall design: In order to define the precise cell types within the retina where the PAX6 enhancers HS5 and NRE are active  we carried out scRNA seq on eyes from NRE eGFP/HS5 mCherry zebrafish reporter embryos. With this technique  we aimed to uncover cell type or transcriptional differences between the two enhancer active populations. We dissected eyes from 48 hpf NRE eGFP/HS5 mCherry embryos and used FACS to enrich for either mCherry positive/HS5 active cells or eGFP positive/NRE active cells. Three samples for each population were processed for scRNA seq using the 10x Genomics Chromium single cell three prime gene expression technology.", null, "pubmed:37643867", null, "mcherry enriched rep3", "GSM7702834", null, "source name:Eye|tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf|geo loc name:missing|collection date:missing", "mcherry enriched rep3", "Cell Ranger v6.1.2 was used to perform alignment  filtering  barcode counting  and UMI counting. A custom reference genome was created for alignment using cellranger mkref  combining the Danio rerio GRCz11 genome assembly with manually annotated eGFP and mCherry sequences. Cell calling and QC: The emptyDrops function from DropletUtils was used to filter out empty droplets/barcodes not corresponding to cells Lun et al.  2019. Mitochondrial and ribosomal genes were excluded from the emptyDrops analysis to improve the filtering of droplets containing ambient RNA or cell fragments. The scater package was used to filter cells based on the QC metrics of library size  detected genes  and mitochondrial reads McCarthy et al.  2017. Cells with detected genes \u2265 500  library size \u2265 800  and mitochondrial reads \u2264 10% were retained. Within the processed dataset  mean reads per cell = 11239  and median genes per cell = 1554. Reference mapping and filtering: The SingleR package was used to annotate cell types based on mapping to the zebrafish single cell transcriptome atlas Aran et al.  2019; Farnsworth et al.  2019. Expression matrix and cell annotation data were downloaded from the UCSC cell browser http://zebrafish dev.cells.ucsc.edu; only the 2 dpf data were used for mapping. Erroneously sorted cells of non retinal identity for example pigmented cell types such as melanocytes with high autofluorescence were filtered out at this stage. This was carried out to improve the resolution of clustering for retinal cell types.  Clustering and cell type annotation: Seurat v4 was used for clustering and further analysis for a total of 6 288 cells Butler et al.  2018. SCTransform was used to perform log normalisation  scaling  and highly variable gene HVG detection on a dataset consisting of the 6 samples merged into one. Standard SCTransform options were used  with regression of mitochondrial expression and cell cycle stage using \u2018vars.to.regress\u2019. We performed Principle Component Analysis PCA on the normalized counts matrix restricted to HVGs  using Seurat's RunPCA function with number of PCs = 50. To enable integration of the samples  we then used Harmony to generate PCs corrected for batch effects between libraries Korsunsky et al.  2019. The Harmony PCs were then used to perform K nearest neighbour analysis k=20 and Louvain clustering using Seurat 15 dimensions and resolution 0.6. Clusters were annotated as retinal cell types based on the highest expressed marker genes  and other known genes for each cell type  using information from the literature and ZFIN Sprague et al.  2008. Cell cycle scoring was performed using the Seurat CellCycleScoring function  using zebrafish genes homologous to the \u2018s.features\u2019 and \u2018g2m.features\u2019 genes provided by Seurat. Assembly: GRCz11 Supplementary files format and content: Tab separated values files  matrix files  Seurat object RDS file", "Eye", null, "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell 3\u2019 gene expression technology v3.1.", null, "tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf", "GSM7702834", "GSM7702834: mcherry enriched rep3; Danio rerio; RNA Seq", "GSM7702834 r1", "GSM7702834", "1", "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell three prime gene expression technology v3.1.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "SINGLE", "ILLUMINA", "NextSeq 2000", null, "SRP454539", null, "loader:fastq load.py", "2707_pos_Mcherry_S3_L002_I1_001.fastq.gz 2707_pos_Mcherry_S3_L002_I2_001.fastq.gz 2707_pos_Mcherry_S3_L002_R1_001.fastq.gz 2707_pos_Mcherry_S3_L002_R2_001.fastq.gz", "fastq fastq fastq fastq", 20708273928.0, 150059956.0, "GSM7702834 r2", "0:10 1:10 2:28 3:90", "A:3746088654;C:3037032642;G:3368938151;T:3353289242;N:47351", 10, 10, 28, 90, 3746088654, 3037032642, 3368938151, 3353289242, 47351, "SRX21332627", "SRS18578259", "SRA1702612", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", 1, 0.94778, null, 0.14581, null, 0.80028, null, 0.52885, null, 90, null, "B", null, "usable mapping rate", "illumina", "nextseq_v2", "3prime", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United Kingdom", "2023-08-10", "Hatching", "Embryo", "Eye", "Sensory System"], [25113, "SRR25822230", "SRX21332627", "SRS18578259", "SRP454539", "PRJNA1004255", "Unique activities of two overlapping PAX6 retinal enhancers", "GSE240575", "Transcriptome Analysis", "Enhancers play a critical role in development by precisely modulating spatial  temporal  and cell type specific gene expression. Sequence variants in enhancers have been implicated in disease  however establishing the functional consequences of these variants is challenging due to a lack of understanding of precise cell types and developmental stages where the enhancers are normally active. PAX6 is the master regulator of eye development  with a regulatory landscape containing multiple enhancers driving expression in the eye. Whether these enhancers perform additive  redundant  or distinct functions is unknown. Here we describe the precise cell types and regulatory activity of two PAX6 retinal enhancers  HS5 and NRE. Using a unique combination of live imaging and single cell RNA sequencing in dual enhancer reporter zebrafish embryos  we uncover differences in the spatiotemporal activity of these enhancers. Our results show that although overlapping  these enhancers have distinct activities in different cell types and therefore likely non redundant functions. This work demonstrates that unique cell type specific activities can be uncovered for apparently similar enhancers when investigated at high resolution in vivo. Overall design: In order to define the precise cell types within the retina where the PAX6 enhancers HS5 and NRE are active  we carried out scRNA seq on eyes from NRE eGFP/HS5 mCherry zebrafish reporter embryos. With this technique  we aimed to uncover cell type or transcriptional differences between the two enhancer active populations. We dissected eyes from 48 hpf NRE eGFP/HS5 mCherry embryos and used FACS to enrich for either mCherry positive/HS5 active cells or eGFP positive/NRE active cells. Three samples for each population were processed for scRNA seq using the 10x Genomics Chromium single cell three prime gene expression technology.", null, "pubmed:37643867", null, "mcherry enriched rep3", "GSM7702834", null, "source name:Eye|tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf|geo loc name:missing|collection date:missing", "mcherry enriched rep3", "Cell Ranger v6.1.2 was used to perform alignment  filtering  barcode counting  and UMI counting. A custom reference genome was created for alignment using cellranger mkref  combining the Danio rerio GRCz11 genome assembly with manually annotated eGFP and mCherry sequences. Cell calling and QC: The emptyDrops function from DropletUtils was used to filter out empty droplets/barcodes not corresponding to cells Lun et al.  2019. Mitochondrial and ribosomal genes were excluded from the emptyDrops analysis to improve the filtering of droplets containing ambient RNA or cell fragments. The scater package was used to filter cells based on the QC metrics of library size  detected genes  and mitochondrial reads McCarthy et al.  2017. Cells with detected genes \u2265 500  library size \u2265 800  and mitochondrial reads \u2264 10% were retained. Within the processed dataset  mean reads per cell = 11239  and median genes per cell = 1554. Reference mapping and filtering: The SingleR package was used to annotate cell types based on mapping to the zebrafish single cell transcriptome atlas Aran et al.  2019; Farnsworth et al.  2019. Expression matrix and cell annotation data were downloaded from the UCSC cell browser http://zebrafish dev.cells.ucsc.edu; only the 2 dpf data were used for mapping. Erroneously sorted cells of non retinal identity for example pigmented cell types such as melanocytes with high autofluorescence were filtered out at this stage. This was carried out to improve the resolution of clustering for retinal cell types.  Clustering and cell type annotation: Seurat v4 was used for clustering and further analysis for a total of 6 288 cells Butler et al.  2018. SCTransform was used to perform log normalisation  scaling  and highly variable gene HVG detection on a dataset consisting of the 6 samples merged into one. Standard SCTransform options were used  with regression of mitochondrial expression and cell cycle stage using \u2018vars.to.regress\u2019. We performed Principle Component Analysis PCA on the normalized counts matrix restricted to HVGs  using Seurat's RunPCA function with number of PCs = 50. To enable integration of the samples  we then used Harmony to generate PCs corrected for batch effects between libraries Korsunsky et al.  2019. The Harmony PCs were then used to perform K nearest neighbour analysis k=20 and Louvain clustering using Seurat 15 dimensions and resolution 0.6. Clusters were annotated as retinal cell types based on the highest expressed marker genes  and other known genes for each cell type  using information from the literature and ZFIN Sprague et al.  2008. Cell cycle scoring was performed using the Seurat CellCycleScoring function  using zebrafish genes homologous to the \u2018s.features\u2019 and \u2018g2m.features\u2019 genes provided by Seurat. Assembly: GRCz11 Supplementary files format and content: Tab separated values files  matrix files  Seurat object RDS file", "Eye", null, "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell 3\u2019 gene expression technology v3.1.", null, "tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf", "GSM7702834", "GSM7702834: mcherry enriched rep3; Danio rerio; RNA Seq", "GSM7702834 r1", "GSM7702834", "1", "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell three prime gene expression technology v3.1.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "SINGLE", "ILLUMINA", "NextSeq 2000", null, "SRP454539", null, "loader:fastq load.py", "2707_pos_Mcherry_S3_L001_I1_002.fastq.gz 2707_pos_Mcherry_S3_L001_I2_002.fastq.gz 2707_pos_Mcherry_S3_L001_R1_002.fastq.gz 2707_pos_Mcherry_S3_L001_R2_002.fastq.gz", "fastq fastq fastq fastq", 20078121078.0, 145493631.0, "GSM7702834 r3", "0:10 1:10 2:28 3:90", "A:3634984131;C:2943891505;G:3255149272;T:3259243920;N:1157962", 10, 10, 28, 90, 3634984131, 2943891505, 3255149272, 3259243920, 1157962, "SRX21332627", "SRS18578259", "SRA1702612", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", 1, 0.94884, null, 0.14622, null, 0.80099, null, 0.52572, null, 90, null, "B", null, "usable mapping rate", "illumina", "nextseq_v2", "3prime", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United Kingdom", "2023-08-10", "Hatching", "Embryo", "Eye", "Sensory System"], [25114, "SRR25822231", "SRX21332627", "SRS18578259", "SRP454539", "PRJNA1004255", "Unique activities of two overlapping PAX6 retinal enhancers", "GSE240575", "Transcriptome Analysis", "Enhancers play a critical role in development by precisely modulating spatial  temporal  and cell type specific gene expression. Sequence variants in enhancers have been implicated in disease  however establishing the functional consequences of these variants is challenging due to a lack of understanding of precise cell types and developmental stages where the enhancers are normally active. PAX6 is the master regulator of eye development  with a regulatory landscape containing multiple enhancers driving expression in the eye. Whether these enhancers perform additive  redundant  or distinct functions is unknown. Here we describe the precise cell types and regulatory activity of two PAX6 retinal enhancers  HS5 and NRE. Using a unique combination of live imaging and single cell RNA sequencing in dual enhancer reporter zebrafish embryos  we uncover differences in the spatiotemporal activity of these enhancers. Our results show that although overlapping  these enhancers have distinct activities in different cell types and therefore likely non redundant functions. This work demonstrates that unique cell type specific activities can be uncovered for apparently similar enhancers when investigated at high resolution in vivo. Overall design: In order to define the precise cell types within the retina where the PAX6 enhancers HS5 and NRE are active  we carried out scRNA seq on eyes from NRE eGFP/HS5 mCherry zebrafish reporter embryos. With this technique  we aimed to uncover cell type or transcriptional differences between the two enhancer active populations. We dissected eyes from 48 hpf NRE eGFP/HS5 mCherry embryos and used FACS to enrich for either mCherry positive/HS5 active cells or eGFP positive/NRE active cells. Three samples for each population were processed for scRNA seq using the 10x Genomics Chromium single cell three prime gene expression technology.", null, "pubmed:37643867", null, "mcherry enriched rep3", "GSM7702834", null, "source name:Eye|tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf|geo loc name:missing|collection date:missing", "mcherry enriched rep3", "Cell Ranger v6.1.2 was used to perform alignment  filtering  barcode counting  and UMI counting. A custom reference genome was created for alignment using cellranger mkref  combining the Danio rerio GRCz11 genome assembly with manually annotated eGFP and mCherry sequences. Cell calling and QC: The emptyDrops function from DropletUtils was used to filter out empty droplets/barcodes not corresponding to cells Lun et al.  2019. Mitochondrial and ribosomal genes were excluded from the emptyDrops analysis to improve the filtering of droplets containing ambient RNA or cell fragments. The scater package was used to filter cells based on the QC metrics of library size  detected genes  and mitochondrial reads McCarthy et al.  2017. Cells with detected genes \u2265 500  library size \u2265 800  and mitochondrial reads \u2264 10% were retained. Within the processed dataset  mean reads per cell = 11239  and median genes per cell = 1554. Reference mapping and filtering: The SingleR package was used to annotate cell types based on mapping to the zebrafish single cell transcriptome atlas Aran et al.  2019; Farnsworth et al.  2019. Expression matrix and cell annotation data were downloaded from the UCSC cell browser http://zebrafish dev.cells.ucsc.edu; only the 2 dpf data were used for mapping. Erroneously sorted cells of non retinal identity for example pigmented cell types such as melanocytes with high autofluorescence were filtered out at this stage. This was carried out to improve the resolution of clustering for retinal cell types.  Clustering and cell type annotation: Seurat v4 was used for clustering and further analysis for a total of 6 288 cells Butler et al.  2018. SCTransform was used to perform log normalisation  scaling  and highly variable gene HVG detection on a dataset consisting of the 6 samples merged into one. Standard SCTransform options were used  with regression of mitochondrial expression and cell cycle stage using \u2018vars.to.regress\u2019. We performed Principle Component Analysis PCA on the normalized counts matrix restricted to HVGs  using Seurat's RunPCA function with number of PCs = 50. To enable integration of the samples  we then used Harmony to generate PCs corrected for batch effects between libraries Korsunsky et al.  2019. The Harmony PCs were then used to perform K nearest neighbour analysis k=20 and Louvain clustering using Seurat 15 dimensions and resolution 0.6. Clusters were annotated as retinal cell types based on the highest expressed marker genes  and other known genes for each cell type  using information from the literature and ZFIN Sprague et al.  2008. Cell cycle scoring was performed using the Seurat CellCycleScoring function  using zebrafish genes homologous to the \u2018s.features\u2019 and \u2018g2m.features\u2019 genes provided by Seurat. Assembly: GRCz11 Supplementary files format and content: Tab separated values files  matrix files  Seurat object RDS file", "Eye", null, "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell 3\u2019 gene expression technology v3.1.", null, "tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf", "GSM7702834", "GSM7702834: mcherry enriched rep3; Danio rerio; RNA Seq", "GSM7702834 r1", "GSM7702834", "1", "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell three prime gene expression technology v3.1.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "SINGLE", "ILLUMINA", "NextSeq 2000", null, "SRP454539", null, "loader:fastq load.py", "2707_pos_Mcherry_S3_L002_I1_002.fastq.gz 2707_pos_Mcherry_S3_L002_I2_002.fastq.gz 2707_pos_Mcherry_S3_L002_R1_002.fastq.gz 2707_pos_Mcherry_S3_L002_R2_002.fastq.gz", "fastq fastq fastq fastq", 20884392978.0, 151336181.0, "GSM7702834 r4", "0:10 1:10 2:28 3:90", "A:3779370721;C:3059502508;G:3396295214;T:3383865877;N:1221970", 10, 10, 28, 90, 3779370721, 3059502508, 3396295214, 3383865877, 1221970, "SRX21332627", "SRS18578259", "SRA1702612", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", 1, 0.94896, null, 0.14559, null, 0.8002, null, 0.51418, null, 90, null, "B", null, "usable mapping rate", "illumina", "nextseq_v2", "3prime", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United Kingdom", "2023-08-10", "Hatching", "Embryo", "Eye", "Sensory System"], [25115, "SRR25605436", "SRX21332626", "SRS18578258", "SRP454539", "PRJNA1004255", "Unique activities of two overlapping PAX6 retinal enhancers", "GSE240575", "Transcriptome Analysis", "Enhancers play a critical role in development by precisely modulating spatial  temporal  and cell type specific gene expression. Sequence variants in enhancers have been implicated in disease  however establishing the functional consequences of these variants is challenging due to a lack of understanding of precise cell types and developmental stages where the enhancers are normally active. PAX6 is the master regulator of eye development  with a regulatory landscape containing multiple enhancers driving expression in the eye. Whether these enhancers perform additive  redundant  or distinct functions is unknown. Here we describe the precise cell types and regulatory activity of two PAX6 retinal enhancers  HS5 and NRE. Using a unique combination of live imaging and single cell RNA sequencing in dual enhancer reporter zebrafish embryos  we uncover differences in the spatiotemporal activity of these enhancers. Our results show that although overlapping  these enhancers have distinct activities in different cell types and therefore likely non redundant functions. This work demonstrates that unique cell type specific activities can be uncovered for apparently similar enhancers when investigated at high resolution in vivo. Overall design: In order to define the precise cell types within the retina where the PAX6 enhancers HS5 and NRE are active  we carried out scRNA seq on eyes from NRE eGFP/HS5 mCherry zebrafish reporter embryos. With this technique  we aimed to uncover cell type or transcriptional differences between the two enhancer active populations. We dissected eyes from 48 hpf NRE eGFP/HS5 mCherry embryos and used FACS to enrich for either mCherry positive/HS5 active cells or eGFP positive/NRE active cells. Three samples for each population were processed for scRNA seq using the 10x Genomics Chromium single cell three prime gene expression technology.", null, "pubmed:37643867", null, "gfp enriched rep2", "GSM7702833", null, "source name:Eye|tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf|geo loc name:missing|collection date:missing", "gfp enriched rep2", "Cell Ranger v6.1.2 was used to perform alignment  filtering  barcode counting  and UMI counting. A custom reference genome was created for alignment using cellranger mkref  combining the Danio rerio GRCz11 genome assembly with manually annotated eGFP and mCherry sequences. Cell calling and QC: The emptyDrops function from DropletUtils was used to filter out empty droplets/barcodes not corresponding to cells Lun et al.  2019. Mitochondrial and ribosomal genes were excluded from the emptyDrops analysis to improve the filtering of droplets containing ambient RNA or cell fragments. The scater package was used to filter cells based on the QC metrics of library size  detected genes  and mitochondrial reads McCarthy et al.  2017. Cells with detected genes \u2265 500  library size \u2265 800  and mitochondrial reads \u2264 10% were retained. Within the processed dataset  mean reads per cell = 11239  and median genes per cell = 1554. Reference mapping and filtering: The SingleR package was used to annotate cell types based on mapping to the zebrafish single cell transcriptome atlas Aran et al.  2019; Farnsworth et al.  2019. Expression matrix and cell annotation data were downloaded from the UCSC cell browser http://zebrafish dev.cells.ucsc.edu; only the 2 dpf data were used for mapping. Erroneously sorted cells of non retinal identity for example pigmented cell types such as melanocytes with high autofluorescence were filtered out at this stage. This was carried out to improve the resolution of clustering for retinal cell types.  Clustering and cell type annotation: Seurat v4 was used for clustering and further analysis for a total of 6 288 cells Butler et al.  2018. SCTransform was used to perform log normalisation  scaling  and highly variable gene HVG detection on a dataset consisting of the 6 samples merged into one. Standard SCTransform options were used  with regression of mitochondrial expression and cell cycle stage using \u2018vars.to.regress\u2019. We performed Principle Component Analysis PCA on the normalized counts matrix restricted to HVGs  using Seurat's RunPCA function with number of PCs = 50. To enable integration of the samples  we then used Harmony to generate PCs corrected for batch effects between libraries Korsunsky et al.  2019. The Harmony PCs were then used to perform K nearest neighbour analysis k=20 and Louvain clustering using Seurat 15 dimensions and resolution 0.6. Clusters were annotated as retinal cell types based on the highest expressed marker genes  and other known genes for each cell type  using information from the literature and ZFIN Sprague et al.  2008. Cell cycle scoring was performed using the Seurat CellCycleScoring function  using zebrafish genes homologous to the \u2018s.features\u2019 and \u2018g2m.features\u2019 genes provided by Seurat. Assembly: GRCz11 Supplementary files format and content: Tab separated values files  matrix files  Seurat object RDS file", "Eye", null, "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell 3\u2019 gene expression technology v3.1.", null, "tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf", "GSM7702833", "GSM7702833: gfp enriched rep2; Danio rerio; RNA Seq", "GSM7702833 r1", "GSM7702833", "1", "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell three prime gene expression technology v3.1.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "SINGLE", "ILLUMINA", "NextSeq 2000", null, "SRP454539", null, "loader:fastq load.py|options:  allowEarlyFileEnd", "1907_GFP_pos_S2_L001_I1_001.fastq.gz 1907_GFP_pos_S2_L001_I2_001.fastq.gz 1907_GFP_pos_S2_L001_R1_001.fastq.gz 1907_GFP_pos_S2_L001_R2_001.fastq.gz", "fastq fastq fastq fastq", 22174775364.0, 160686778.0, "GSM7702833 r1", "0:10 1:10 2:28 3:90", "A:4207510387;C:3050740898;G:3362227609;T:3839333241;N:1997885", 10, 10, 28, 90, 4207510387, 3050740898, 3362227609, 3839333241, 1997885, "SRX21332626", "SRS18578258", "SRA1702612", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", 1, 0.93287, null, 0.11844, null, 0.81087, null, 0.55264, null, 90, null, "B", null, "usable mapping rate", "illumina", "nextseq_v2", "3prime", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United Kingdom", "2023-08-10", "Hatching", "Embryo", "Eye", "Sensory System"], [25116, "SRR25605437", "SRX21332626", "SRS18578258", "SRP454539", "PRJNA1004255", "Unique activities of two overlapping PAX6 retinal enhancers", "GSE240575", "Transcriptome Analysis", "Enhancers play a critical role in development by precisely modulating spatial  temporal  and cell type specific gene expression. Sequence variants in enhancers have been implicated in disease  however establishing the functional consequences of these variants is challenging due to a lack of understanding of precise cell types and developmental stages where the enhancers are normally active. PAX6 is the master regulator of eye development  with a regulatory landscape containing multiple enhancers driving expression in the eye. Whether these enhancers perform additive  redundant  or distinct functions is unknown. Here we describe the precise cell types and regulatory activity of two PAX6 retinal enhancers  HS5 and NRE. Using a unique combination of live imaging and single cell RNA sequencing in dual enhancer reporter zebrafish embryos  we uncover differences in the spatiotemporal activity of these enhancers. Our results show that although overlapping  these enhancers have distinct activities in different cell types and therefore likely non redundant functions. This work demonstrates that unique cell type specific activities can be uncovered for apparently similar enhancers when investigated at high resolution in vivo. Overall design: In order to define the precise cell types within the retina where the PAX6 enhancers HS5 and NRE are active  we carried out scRNA seq on eyes from NRE eGFP/HS5 mCherry zebrafish reporter embryos. With this technique  we aimed to uncover cell type or transcriptional differences between the two enhancer active populations. We dissected eyes from 48 hpf NRE eGFP/HS5 mCherry embryos and used FACS to enrich for either mCherry positive/HS5 active cells or eGFP positive/NRE active cells. Three samples for each population were processed for scRNA seq using the 10x Genomics Chromium single cell three prime gene expression technology.", null, "pubmed:37643867", null, "gfp enriched rep2", "GSM7702833", null, "source name:Eye|tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf|geo loc name:missing|collection date:missing", "gfp enriched rep2", "Cell Ranger v6.1.2 was used to perform alignment  filtering  barcode counting  and UMI counting. A custom reference genome was created for alignment using cellranger mkref  combining the Danio rerio GRCz11 genome assembly with manually annotated eGFP and mCherry sequences. Cell calling and QC: The emptyDrops function from DropletUtils was used to filter out empty droplets/barcodes not corresponding to cells Lun et al.  2019. Mitochondrial and ribosomal genes were excluded from the emptyDrops analysis to improve the filtering of droplets containing ambient RNA or cell fragments. The scater package was used to filter cells based on the QC metrics of library size  detected genes  and mitochondrial reads McCarthy et al.  2017. Cells with detected genes \u2265 500  library size \u2265 800  and mitochondrial reads \u2264 10% were retained. Within the processed dataset  mean reads per cell = 11239  and median genes per cell = 1554. Reference mapping and filtering: The SingleR package was used to annotate cell types based on mapping to the zebrafish single cell transcriptome atlas Aran et al.  2019; Farnsworth et al.  2019. Expression matrix and cell annotation data were downloaded from the UCSC cell browser http://zebrafish dev.cells.ucsc.edu; only the 2 dpf data were used for mapping. Erroneously sorted cells of non retinal identity for example pigmented cell types such as melanocytes with high autofluorescence were filtered out at this stage. This was carried out to improve the resolution of clustering for retinal cell types.  Clustering and cell type annotation: Seurat v4 was used for clustering and further analysis for a total of 6 288 cells Butler et al.  2018. SCTransform was used to perform log normalisation  scaling  and highly variable gene HVG detection on a dataset consisting of the 6 samples merged into one. Standard SCTransform options were used  with regression of mitochondrial expression and cell cycle stage using \u2018vars.to.regress\u2019. We performed Principle Component Analysis PCA on the normalized counts matrix restricted to HVGs  using Seurat's RunPCA function with number of PCs = 50. To enable integration of the samples  we then used Harmony to generate PCs corrected for batch effects between libraries Korsunsky et al.  2019. The Harmony PCs were then used to perform K nearest neighbour analysis k=20 and Louvain clustering using Seurat 15 dimensions and resolution 0.6. Clusters were annotated as retinal cell types based on the highest expressed marker genes  and other known genes for each cell type  using information from the literature and ZFIN Sprague et al.  2008. Cell cycle scoring was performed using the Seurat CellCycleScoring function  using zebrafish genes homologous to the \u2018s.features\u2019 and \u2018g2m.features\u2019 genes provided by Seurat. Assembly: GRCz11 Supplementary files format and content: Tab separated values files  matrix files  Seurat object RDS file", "Eye", null, "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell 3\u2019 gene expression technology v3.1.", null, "tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf", "GSM7702833", "GSM7702833: gfp enriched rep2; Danio rerio; RNA Seq", "GSM7702833 r1", "GSM7702833", "1", "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell three prime gene expression technology v3.1.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "SINGLE", "ILLUMINA", "NextSeq 2000", null, "SRP454539", null, "loader:fastq load.py|options:  allowEarlyFileEnd", "1907_GFP_pos_S2_L002_I1_001.fastq.gz 1907_GFP_pos_S2_L002_I2_001.fastq.gz 1907_GFP_pos_S2_L002_R1_001.fastq.gz 1907_GFP_pos_S2_L002_R2_001.fastq.gz", "fastq fastq fastq fastq", 22047847518.0, 159767011.0, "GSM7702833 r2", "0:10 1:10 2:28 3:90", "A:4174013532;C:3033959926;G:3357962867;T:3813042664;N:52001", 10, 10, 28, 90, 4174013532, 3033959926, 3357962867, 3813042664, 52001, "SRX21332626", "SRS18578258", "SRA1702612", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", 1, 0.93359, null, 0.11585, null, 0.81087, null, 0.55705, null, 90, null, "B", null, "usable mapping rate", "illumina", "nextseq_v2", "3prime", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United Kingdom", "2023-08-10", "Hatching", "Embryo", "Eye", "Sensory System"], [25117, "SRR25822228", "SRX21332626", "SRS18578258", "SRP454539", "PRJNA1004255", "Unique activities of two overlapping PAX6 retinal enhancers", "GSE240575", "Transcriptome Analysis", "Enhancers play a critical role in development by precisely modulating spatial  temporal  and cell type specific gene expression. Sequence variants in enhancers have been implicated in disease  however establishing the functional consequences of these variants is challenging due to a lack of understanding of precise cell types and developmental stages where the enhancers are normally active. PAX6 is the master regulator of eye development  with a regulatory landscape containing multiple enhancers driving expression in the eye. Whether these enhancers perform additive  redundant  or distinct functions is unknown. Here we describe the precise cell types and regulatory activity of two PAX6 retinal enhancers  HS5 and NRE. Using a unique combination of live imaging and single cell RNA sequencing in dual enhancer reporter zebrafish embryos  we uncover differences in the spatiotemporal activity of these enhancers. Our results show that although overlapping  these enhancers have distinct activities in different cell types and therefore likely non redundant functions. This work demonstrates that unique cell type specific activities can be uncovered for apparently similar enhancers when investigated at high resolution in vivo. Overall design: In order to define the precise cell types within the retina where the PAX6 enhancers HS5 and NRE are active  we carried out scRNA seq on eyes from NRE eGFP/HS5 mCherry zebrafish reporter embryos. With this technique  we aimed to uncover cell type or transcriptional differences between the two enhancer active populations. We dissected eyes from 48 hpf NRE eGFP/HS5 mCherry embryos and used FACS to enrich for either mCherry positive/HS5 active cells or eGFP positive/NRE active cells. Three samples for each population were processed for scRNA seq using the 10x Genomics Chromium single cell three prime gene expression technology.", null, "pubmed:37643867", null, "gfp enriched rep2", "GSM7702833", null, "source name:Eye|tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf|geo loc name:missing|collection date:missing", "gfp enriched rep2", "Cell Ranger v6.1.2 was used to perform alignment  filtering  barcode counting  and UMI counting. A custom reference genome was created for alignment using cellranger mkref  combining the Danio rerio GRCz11 genome assembly with manually annotated eGFP and mCherry sequences. Cell calling and QC: The emptyDrops function from DropletUtils was used to filter out empty droplets/barcodes not corresponding to cells Lun et al.  2019. Mitochondrial and ribosomal genes were excluded from the emptyDrops analysis to improve the filtering of droplets containing ambient RNA or cell fragments. The scater package was used to filter cells based on the QC metrics of library size  detected genes  and mitochondrial reads McCarthy et al.  2017. Cells with detected genes \u2265 500  library size \u2265 800  and mitochondrial reads \u2264 10% were retained. Within the processed dataset  mean reads per cell = 11239  and median genes per cell = 1554. Reference mapping and filtering: The SingleR package was used to annotate cell types based on mapping to the zebrafish single cell transcriptome atlas Aran et al.  2019; Farnsworth et al.  2019. Expression matrix and cell annotation data were downloaded from the UCSC cell browser http://zebrafish dev.cells.ucsc.edu; only the 2 dpf data were used for mapping. Erroneously sorted cells of non retinal identity for example pigmented cell types such as melanocytes with high autofluorescence were filtered out at this stage. This was carried out to improve the resolution of clustering for retinal cell types.  Clustering and cell type annotation: Seurat v4 was used for clustering and further analysis for a total of 6 288 cells Butler et al.  2018. SCTransform was used to perform log normalisation  scaling  and highly variable gene HVG detection on a dataset consisting of the 6 samples merged into one. Standard SCTransform options were used  with regression of mitochondrial expression and cell cycle stage using \u2018vars.to.regress\u2019. We performed Principle Component Analysis PCA on the normalized counts matrix restricted to HVGs  using Seurat's RunPCA function with number of PCs = 50. To enable integration of the samples  we then used Harmony to generate PCs corrected for batch effects between libraries Korsunsky et al.  2019. The Harmony PCs were then used to perform K nearest neighbour analysis k=20 and Louvain clustering using Seurat 15 dimensions and resolution 0.6. Clusters were annotated as retinal cell types based on the highest expressed marker genes  and other known genes for each cell type  using information from the literature and ZFIN Sprague et al.  2008. Cell cycle scoring was performed using the Seurat CellCycleScoring function  using zebrafish genes homologous to the \u2018s.features\u2019 and \u2018g2m.features\u2019 genes provided by Seurat. Assembly: GRCz11 Supplementary files format and content: Tab separated values files  matrix files  Seurat object RDS file", "Eye", null, "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell 3\u2019 gene expression technology v3.1.", null, "tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf", "GSM7702833", "GSM7702833: gfp enriched rep2; Danio rerio; RNA Seq", "GSM7702833 r1", "GSM7702833", "1", "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell three prime gene expression technology v3.1.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "SINGLE", "ILLUMINA", "NextSeq 2000", null, "SRP454539", null, "loader:fastq load.py", "1907_GFP_pos_S2_L001_I1_002.fastq.gz 1907_GFP_pos_S2_L001_I2_002.fastq.gz 1907_GFP_pos_S2_L001_R1_002.fastq.gz 1907_GFP_pos_S2_L001_R2_002.fastq.gz", "fastq fastq fastq fastq", 22010894568.0, 159499236.0, "GSM7702833 r3", "0:10 1:10 2:28 3:90", "A:4176090595;C:3026940106;G:3336506731;T:3814128890;N:1264918", 10, 10, 28, 90, 4176090595, 3026940106, 3336506731, 3814128890, 1264918, "SRX21332626", "SRS18578258", "SRA1702612", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", 1, 0.93457, null, 0.11733, null, 0.81032, null, 0.55203, null, 90, null, "B", null, "usable mapping rate", "illumina", "nextseq_v2", "3prime", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United Kingdom", "2023-08-10", "Hatching", "Embryo", "Eye", "Sensory System"], [25118, "SRR25822229", "SRX21332626", "SRS18578258", "SRP454539", "PRJNA1004255", "Unique activities of two overlapping PAX6 retinal enhancers", "GSE240575", "Transcriptome Analysis", "Enhancers play a critical role in development by precisely modulating spatial  temporal  and cell type specific gene expression. Sequence variants in enhancers have been implicated in disease  however establishing the functional consequences of these variants is challenging due to a lack of understanding of precise cell types and developmental stages where the enhancers are normally active. PAX6 is the master regulator of eye development  with a regulatory landscape containing multiple enhancers driving expression in the eye. Whether these enhancers perform additive  redundant  or distinct functions is unknown. Here we describe the precise cell types and regulatory activity of two PAX6 retinal enhancers  HS5 and NRE. Using a unique combination of live imaging and single cell RNA sequencing in dual enhancer reporter zebrafish embryos  we uncover differences in the spatiotemporal activity of these enhancers. Our results show that although overlapping  these enhancers have distinct activities in different cell types and therefore likely non redundant functions. This work demonstrates that unique cell type specific activities can be uncovered for apparently similar enhancers when investigated at high resolution in vivo. Overall design: In order to define the precise cell types within the retina where the PAX6 enhancers HS5 and NRE are active  we carried out scRNA seq on eyes from NRE eGFP/HS5 mCherry zebrafish reporter embryos. With this technique  we aimed to uncover cell type or transcriptional differences between the two enhancer active populations. We dissected eyes from 48 hpf NRE eGFP/HS5 mCherry embryos and used FACS to enrich for either mCherry positive/HS5 active cells or eGFP positive/NRE active cells. Three samples for each population were processed for scRNA seq using the 10x Genomics Chromium single cell three prime gene expression technology.", null, "pubmed:37643867", null, "gfp enriched rep2", "GSM7702833", null, "source name:Eye|tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf|geo loc name:missing|collection date:missing", "gfp enriched rep2", "Cell Ranger v6.1.2 was used to perform alignment  filtering  barcode counting  and UMI counting. A custom reference genome was created for alignment using cellranger mkref  combining the Danio rerio GRCz11 genome assembly with manually annotated eGFP and mCherry sequences. Cell calling and QC: The emptyDrops function from DropletUtils was used to filter out empty droplets/barcodes not corresponding to cells Lun et al.  2019. Mitochondrial and ribosomal genes were excluded from the emptyDrops analysis to improve the filtering of droplets containing ambient RNA or cell fragments. The scater package was used to filter cells based on the QC metrics of library size  detected genes  and mitochondrial reads McCarthy et al.  2017. Cells with detected genes \u2265 500  library size \u2265 800  and mitochondrial reads \u2264 10% were retained. Within the processed dataset  mean reads per cell = 11239  and median genes per cell = 1554. Reference mapping and filtering: The SingleR package was used to annotate cell types based on mapping to the zebrafish single cell transcriptome atlas Aran et al.  2019; Farnsworth et al.  2019. Expression matrix and cell annotation data were downloaded from the UCSC cell browser http://zebrafish dev.cells.ucsc.edu; only the 2 dpf data were used for mapping. Erroneously sorted cells of non retinal identity for example pigmented cell types such as melanocytes with high autofluorescence were filtered out at this stage. This was carried out to improve the resolution of clustering for retinal cell types.  Clustering and cell type annotation: Seurat v4 was used for clustering and further analysis for a total of 6 288 cells Butler et al.  2018. SCTransform was used to perform log normalisation  scaling  and highly variable gene HVG detection on a dataset consisting of the 6 samples merged into one. Standard SCTransform options were used  with regression of mitochondrial expression and cell cycle stage using \u2018vars.to.regress\u2019. We performed Principle Component Analysis PCA on the normalized counts matrix restricted to HVGs  using Seurat's RunPCA function with number of PCs = 50. To enable integration of the samples  we then used Harmony to generate PCs corrected for batch effects between libraries Korsunsky et al.  2019. The Harmony PCs were then used to perform K nearest neighbour analysis k=20 and Louvain clustering using Seurat 15 dimensions and resolution 0.6. Clusters were annotated as retinal cell types based on the highest expressed marker genes  and other known genes for each cell type  using information from the literature and ZFIN Sprague et al.  2008. Cell cycle scoring was performed using the Seurat CellCycleScoring function  using zebrafish genes homologous to the \u2018s.features\u2019 and \u2018g2m.features\u2019 genes provided by Seurat. Assembly: GRCz11 Supplementary files format and content: Tab separated values files  matrix files  Seurat object RDS file", "Eye", null, "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell 3\u2019 gene expression technology v3.1.", null, "tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf", "GSM7702833", "GSM7702833: gfp enriched rep2; Danio rerio; RNA Seq", "GSM7702833 r1", "GSM7702833", "1", "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell three prime gene expression technology v3.1.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "SINGLE", "ILLUMINA", "NextSeq 2000", null, "SRP454539", null, "loader:fastq load.py", "1907_GFP_pos_S2_L002_I1_002.fastq.gz 1907_GFP_pos_S2_L002_I2_002.fastq.gz 1907_GFP_pos_S2_L002_R1_002.fastq.gz 1907_GFP_pos_S2_L002_R2_002.fastq.gz", "fastq fastq fastq fastq", 22227220746.0, 161066817.0, "GSM7702833 r4", "0:10 1:10 2:28 3:90", "A:4209198596;C:3055507768;G:3382717459;T:3847294849;N:1294858", 10, 10, 28, 90, 4209198596, 3055507768, 3382717459, 3847294849, 1294858, "SRX21332626", "SRS18578258", "SRA1702612", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", 1, 0.93428, null, 0.11629, null, 0.81014, null, 0.56014, null, 90, null, "B", null, "usable mapping rate", "illumina", "nextseq_v2", "3prime", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United Kingdom", "2023-08-10", "Hatching", "Embryo", "Eye", "Sensory System"], [25119, "SRR25605438", "SRX21332625", "SRS18578257", "SRP454539", "PRJNA1004255", "Unique activities of two overlapping PAX6 retinal enhancers", "GSE240575", "Transcriptome Analysis", "Enhancers play a critical role in development by precisely modulating spatial  temporal  and cell type specific gene expression. Sequence variants in enhancers have been implicated in disease  however establishing the functional consequences of these variants is challenging due to a lack of understanding of precise cell types and developmental stages where the enhancers are normally active. PAX6 is the master regulator of eye development  with a regulatory landscape containing multiple enhancers driving expression in the eye. Whether these enhancers perform additive  redundant  or distinct functions is unknown. Here we describe the precise cell types and regulatory activity of two PAX6 retinal enhancers  HS5 and NRE. Using a unique combination of live imaging and single cell RNA sequencing in dual enhancer reporter zebrafish embryos  we uncover differences in the spatiotemporal activity of these enhancers. Our results show that although overlapping  these enhancers have distinct activities in different cell types and therefore likely non redundant functions. This work demonstrates that unique cell type specific activities can be uncovered for apparently similar enhancers when investigated at high resolution in vivo. Overall design: In order to define the precise cell types within the retina where the PAX6 enhancers HS5 and NRE are active  we carried out scRNA seq on eyes from NRE eGFP/HS5 mCherry zebrafish reporter embryos. With this technique  we aimed to uncover cell type or transcriptional differences between the two enhancer active populations. We dissected eyes from 48 hpf NRE eGFP/HS5 mCherry embryos and used FACS to enrich for either mCherry positive/HS5 active cells or eGFP positive/NRE active cells. Three samples for each population were processed for scRNA seq using the 10x Genomics Chromium single cell three prime gene expression technology.", null, "pubmed:37643867", null, "mcherry enriched rep2", "GSM7702832", null, "source name:Eye|tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf|geo loc name:missing|collection date:missing", "mcherry enriched rep2", "Cell Ranger v6.1.2 was used to perform alignment  filtering  barcode counting  and UMI counting. A custom reference genome was created for alignment using cellranger mkref  combining the Danio rerio GRCz11 genome assembly with manually annotated eGFP and mCherry sequences. Cell calling and QC: The emptyDrops function from DropletUtils was used to filter out empty droplets/barcodes not corresponding to cells Lun et al.  2019. Mitochondrial and ribosomal genes were excluded from the emptyDrops analysis to improve the filtering of droplets containing ambient RNA or cell fragments. The scater package was used to filter cells based on the QC metrics of library size  detected genes  and mitochondrial reads McCarthy et al.  2017. Cells with detected genes \u2265 500  library size \u2265 800  and mitochondrial reads \u2264 10% were retained. Within the processed dataset  mean reads per cell = 11239  and median genes per cell = 1554. Reference mapping and filtering: The SingleR package was used to annotate cell types based on mapping to the zebrafish single cell transcriptome atlas Aran et al.  2019; Farnsworth et al.  2019. Expression matrix and cell annotation data were downloaded from the UCSC cell browser http://zebrafish dev.cells.ucsc.edu; only the 2 dpf data were used for mapping. Erroneously sorted cells of non retinal identity for example pigmented cell types such as melanocytes with high autofluorescence were filtered out at this stage. This was carried out to improve the resolution of clustering for retinal cell types.  Clustering and cell type annotation: Seurat v4 was used for clustering and further analysis for a total of 6 288 cells Butler et al.  2018. SCTransform was used to perform log normalisation  scaling  and highly variable gene HVG detection on a dataset consisting of the 6 samples merged into one. Standard SCTransform options were used  with regression of mitochondrial expression and cell cycle stage using \u2018vars.to.regress\u2019. We performed Principle Component Analysis PCA on the normalized counts matrix restricted to HVGs  using Seurat's RunPCA function with number of PCs = 50. To enable integration of the samples  we then used Harmony to generate PCs corrected for batch effects between libraries Korsunsky et al.  2019. The Harmony PCs were then used to perform K nearest neighbour analysis k=20 and Louvain clustering using Seurat 15 dimensions and resolution 0.6. Clusters were annotated as retinal cell types based on the highest expressed marker genes  and other known genes for each cell type  using information from the literature and ZFIN Sprague et al.  2008. Cell cycle scoring was performed using the Seurat CellCycleScoring function  using zebrafish genes homologous to the \u2018s.features\u2019 and \u2018g2m.features\u2019 genes provided by Seurat. Assembly: GRCz11 Supplementary files format and content: Tab separated values files  matrix files  Seurat object RDS file", "Eye", null, "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell 3\u2019 gene expression technology v3.1.", null, "tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf", "GSM7702832", "GSM7702832: mcherry enriched rep2; Danio rerio; RNA Seq", "GSM7702832 r1", "GSM7702832", "1", "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell three prime gene expression technology v3.1.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "SINGLE", "ILLUMINA", "NextSeq 2000", null, "SRP454539", null, "loader:fastq load.py", "1907_pos_pos_S1_L001_I1_001.fastq.gz 1907_pos_pos_S1_L001_I2_001.fastq.gz 1907_pos_pos_S1_L001_R1_001.fastq.gz 1907_pos_pos_S1_L001_R2_001.fastq.gz", "fastq fastq fastq fastq", 25141955454.0, 182188083.0, "GSM7702832 r1", "0:10 1:10 2:28 3:90", "A:4942067104;C:3446689328;G:3778138998;T:4227670796;N:2361244", 10, 10, 28, 90, 4942067104, 3446689328, 3778138998, 4227670796, 2361244, "SRX21332625", "SRS18578257", "SRA1702612", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", 1, 0.90803, null, 0.11273, null, 0.81872, null, 0.54345, null, 90, null, "B", null, "usable mapping rate", "illumina", "nextseq_v2", "3prime", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United Kingdom", "2023-08-10", "Hatching", "Embryo", "Eye", "Sensory System"], [25120, "SRR25605439", "SRX21332625", "SRS18578257", "SRP454539", "PRJNA1004255", "Unique activities of two overlapping PAX6 retinal enhancers", "GSE240575", "Transcriptome Analysis", "Enhancers play a critical role in development by precisely modulating spatial  temporal  and cell type specific gene expression. Sequence variants in enhancers have been implicated in disease  however establishing the functional consequences of these variants is challenging due to a lack of understanding of precise cell types and developmental stages where the enhancers are normally active. PAX6 is the master regulator of eye development  with a regulatory landscape containing multiple enhancers driving expression in the eye. Whether these enhancers perform additive  redundant  or distinct functions is unknown. Here we describe the precise cell types and regulatory activity of two PAX6 retinal enhancers  HS5 and NRE. Using a unique combination of live imaging and single cell RNA sequencing in dual enhancer reporter zebrafish embryos  we uncover differences in the spatiotemporal activity of these enhancers. Our results show that although overlapping  these enhancers have distinct activities in different cell types and therefore likely non redundant functions. This work demonstrates that unique cell type specific activities can be uncovered for apparently similar enhancers when investigated at high resolution in vivo. Overall design: In order to define the precise cell types within the retina where the PAX6 enhancers HS5 and NRE are active  we carried out scRNA seq on eyes from NRE eGFP/HS5 mCherry zebrafish reporter embryos. With this technique  we aimed to uncover cell type or transcriptional differences between the two enhancer active populations. We dissected eyes from 48 hpf NRE eGFP/HS5 mCherry embryos and used FACS to enrich for either mCherry positive/HS5 active cells or eGFP positive/NRE active cells. Three samples for each population were processed for scRNA seq using the 10x Genomics Chromium single cell three prime gene expression technology.", null, "pubmed:37643867", null, "mcherry enriched rep2", "GSM7702832", null, "source name:Eye|tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf|geo loc name:missing|collection date:missing", "mcherry enriched rep2", "Cell Ranger v6.1.2 was used to perform alignment  filtering  barcode counting  and UMI counting. A custom reference genome was created for alignment using cellranger mkref  combining the Danio rerio GRCz11 genome assembly with manually annotated eGFP and mCherry sequences. Cell calling and QC: The emptyDrops function from DropletUtils was used to filter out empty droplets/barcodes not corresponding to cells Lun et al.  2019. Mitochondrial and ribosomal genes were excluded from the emptyDrops analysis to improve the filtering of droplets containing ambient RNA or cell fragments. The scater package was used to filter cells based on the QC metrics of library size  detected genes  and mitochondrial reads McCarthy et al.  2017. Cells with detected genes \u2265 500  library size \u2265 800  and mitochondrial reads \u2264 10% were retained. Within the processed dataset  mean reads per cell = 11239  and median genes per cell = 1554. Reference mapping and filtering: The SingleR package was used to annotate cell types based on mapping to the zebrafish single cell transcriptome atlas Aran et al.  2019; Farnsworth et al.  2019. Expression matrix and cell annotation data were downloaded from the UCSC cell browser http://zebrafish dev.cells.ucsc.edu; only the 2 dpf data were used for mapping. Erroneously sorted cells of non retinal identity for example pigmented cell types such as melanocytes with high autofluorescence were filtered out at this stage. This was carried out to improve the resolution of clustering for retinal cell types.  Clustering and cell type annotation: Seurat v4 was used for clustering and further analysis for a total of 6 288 cells Butler et al.  2018. SCTransform was used to perform log normalisation  scaling  and highly variable gene HVG detection on a dataset consisting of the 6 samples merged into one. Standard SCTransform options were used  with regression of mitochondrial expression and cell cycle stage using \u2018vars.to.regress\u2019. We performed Principle Component Analysis PCA on the normalized counts matrix restricted to HVGs  using Seurat's RunPCA function with number of PCs = 50. To enable integration of the samples  we then used Harmony to generate PCs corrected for batch effects between libraries Korsunsky et al.  2019. The Harmony PCs were then used to perform K nearest neighbour analysis k=20 and Louvain clustering using Seurat 15 dimensions and resolution 0.6. Clusters were annotated as retinal cell types based on the highest expressed marker genes  and other known genes for each cell type  using information from the literature and ZFIN Sprague et al.  2008. Cell cycle scoring was performed using the Seurat CellCycleScoring function  using zebrafish genes homologous to the \u2018s.features\u2019 and \u2018g2m.features\u2019 genes provided by Seurat. Assembly: GRCz11 Supplementary files format and content: Tab separated values files  matrix files  Seurat object RDS file", "Eye", null, "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell 3\u2019 gene expression technology v3.1.", null, "tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf", "GSM7702832", "GSM7702832: mcherry enriched rep2; Danio rerio; RNA Seq", "GSM7702832 r1", "GSM7702832", "1", "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell three prime gene expression technology v3.1.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "SINGLE", "ILLUMINA", "NextSeq 2000", null, "SRP454539", null, "loader:fastq load.py", "1907_pos_pos_S1_L002_R2_001.fastq.gz 1907_pos_pos_S1_L002_R1_001.fastq.gz 1907_pos_pos_S1_L002_I2_001.fastq.gz 1907_pos_pos_S1_L002_I1_001.fastq.gz", "fastq fastq fastq fastq", 25433730786.0, 184302397.0, "GSM7702832 r2", "0:10 1:10 2:28 3:90", "A:4980326106;C:3488986366;G:3842594871;T:4275245265;N:63122", 10, 10, 28, 90, 4980326106, 3488986366, 3842594871, 4275245265, 63122, "SRX21332625", "SRS18578257", "SRA1702612", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", 1, 0.91035, null, 0.11175, null, 0.82016, null, 0.52814, null, 90, null, "B", null, "usable mapping rate", "illumina", "nextseq_v2", "3prime", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United Kingdom", "2023-08-10", "Hatching", "Embryo", "Eye", "Sensory System"], [25121, "SRR25822226", "SRX21332625", "SRS18578257", "SRP454539", "PRJNA1004255", "Unique activities of two overlapping PAX6 retinal enhancers", "GSE240575", "Transcriptome Analysis", "Enhancers play a critical role in development by precisely modulating spatial  temporal  and cell type specific gene expression. Sequence variants in enhancers have been implicated in disease  however establishing the functional consequences of these variants is challenging due to a lack of understanding of precise cell types and developmental stages where the enhancers are normally active. PAX6 is the master regulator of eye development  with a regulatory landscape containing multiple enhancers driving expression in the eye. Whether these enhancers perform additive  redundant  or distinct functions is unknown. Here we describe the precise cell types and regulatory activity of two PAX6 retinal enhancers  HS5 and NRE. Using a unique combination of live imaging and single cell RNA sequencing in dual enhancer reporter zebrafish embryos  we uncover differences in the spatiotemporal activity of these enhancers. Our results show that although overlapping  these enhancers have distinct activities in different cell types and therefore likely non redundant functions. This work demonstrates that unique cell type specific activities can be uncovered for apparently similar enhancers when investigated at high resolution in vivo. Overall design: In order to define the precise cell types within the retina where the PAX6 enhancers HS5 and NRE are active  we carried out scRNA seq on eyes from NRE eGFP/HS5 mCherry zebrafish reporter embryos. With this technique  we aimed to uncover cell type or transcriptional differences between the two enhancer active populations. We dissected eyes from 48 hpf NRE eGFP/HS5 mCherry embryos and used FACS to enrich for either mCherry positive/HS5 active cells or eGFP positive/NRE active cells. Three samples for each population were processed for scRNA seq using the 10x Genomics Chromium single cell three prime gene expression technology.", null, "pubmed:37643867", null, "mcherry enriched rep2", "GSM7702832", null, "source name:Eye|tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf|geo loc name:missing|collection date:missing", "mcherry enriched rep2", "Cell Ranger v6.1.2 was used to perform alignment  filtering  barcode counting  and UMI counting. A custom reference genome was created for alignment using cellranger mkref  combining the Danio rerio GRCz11 genome assembly with manually annotated eGFP and mCherry sequences. Cell calling and QC: The emptyDrops function from DropletUtils was used to filter out empty droplets/barcodes not corresponding to cells Lun et al.  2019. Mitochondrial and ribosomal genes were excluded from the emptyDrops analysis to improve the filtering of droplets containing ambient RNA or cell fragments. The scater package was used to filter cells based on the QC metrics of library size  detected genes  and mitochondrial reads McCarthy et al.  2017. Cells with detected genes \u2265 500  library size \u2265 800  and mitochondrial reads \u2264 10% were retained. Within the processed dataset  mean reads per cell = 11239  and median genes per cell = 1554. Reference mapping and filtering: The SingleR package was used to annotate cell types based on mapping to the zebrafish single cell transcriptome atlas Aran et al.  2019; Farnsworth et al.  2019. Expression matrix and cell annotation data were downloaded from the UCSC cell browser http://zebrafish dev.cells.ucsc.edu; only the 2 dpf data were used for mapping. Erroneously sorted cells of non retinal identity for example pigmented cell types such as melanocytes with high autofluorescence were filtered out at this stage. This was carried out to improve the resolution of clustering for retinal cell types.  Clustering and cell type annotation: Seurat v4 was used for clustering and further analysis for a total of 6 288 cells Butler et al.  2018. SCTransform was used to perform log normalisation  scaling  and highly variable gene HVG detection on a dataset consisting of the 6 samples merged into one. Standard SCTransform options were used  with regression of mitochondrial expression and cell cycle stage using \u2018vars.to.regress\u2019. We performed Principle Component Analysis PCA on the normalized counts matrix restricted to HVGs  using Seurat's RunPCA function with number of PCs = 50. To enable integration of the samples  we then used Harmony to generate PCs corrected for batch effects between libraries Korsunsky et al.  2019. The Harmony PCs were then used to perform K nearest neighbour analysis k=20 and Louvain clustering using Seurat 15 dimensions and resolution 0.6. Clusters were annotated as retinal cell types based on the highest expressed marker genes  and other known genes for each cell type  using information from the literature and ZFIN Sprague et al.  2008. Cell cycle scoring was performed using the Seurat CellCycleScoring function  using zebrafish genes homologous to the \u2018s.features\u2019 and \u2018g2m.features\u2019 genes provided by Seurat. Assembly: GRCz11 Supplementary files format and content: Tab separated values files  matrix files  Seurat object RDS file", "Eye", null, "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell 3\u2019 gene expression technology v3.1.", null, "tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf", "GSM7702832", "GSM7702832: mcherry enriched rep2; Danio rerio; RNA Seq", "GSM7702832 r1", "GSM7702832", "1", "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell three prime gene expression technology v3.1.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "SINGLE", "ILLUMINA", "NextSeq 2000", null, "SRP454539", null, "loader:fastq load.py", "1907_pos_pos_S1_L001_R2_002.fastq.gz 1907_pos_pos_S1_L001_R1_002.fastq.gz 1907_pos_pos_S1_L001_I2_002.fastq.gz 1907_pos_pos_S1_L001_I1_002.fastq.gz", "fastq fastq fastq fastq", 24834656088.0, 179961276.0, "GSM7702832 r3", "0:10 1:10 2:28 3:90", "A:4878672093;C:3403443000;G:3732878174;T:4180051888;N:1469685", 10, 10, 28, 90, 4878672093, 3403443000, 3732878174, 4180051888, 1469685, "SRX21332625", "SRS18578257", "SRA1702612", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", 1, 0.90776, null, 0.11325, null, 0.81852, null, 0.54011, null, 90, null, "B", null, "usable mapping rate", "illumina", "nextseq_v2", "3prime", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United Kingdom", "2023-08-10", "Hatching", "Embryo", "Eye", "Sensory System"], [25122, "SRR25822227", "SRX21332625", "SRS18578257", "SRP454539", "PRJNA1004255", "Unique activities of two overlapping PAX6 retinal enhancers", "GSE240575", "Transcriptome Analysis", "Enhancers play a critical role in development by precisely modulating spatial  temporal  and cell type specific gene expression. Sequence variants in enhancers have been implicated in disease  however establishing the functional consequences of these variants is challenging due to a lack of understanding of precise cell types and developmental stages where the enhancers are normally active. PAX6 is the master regulator of eye development  with a regulatory landscape containing multiple enhancers driving expression in the eye. Whether these enhancers perform additive  redundant  or distinct functions is unknown. Here we describe the precise cell types and regulatory activity of two PAX6 retinal enhancers  HS5 and NRE. Using a unique combination of live imaging and single cell RNA sequencing in dual enhancer reporter zebrafish embryos  we uncover differences in the spatiotemporal activity of these enhancers. Our results show that although overlapping  these enhancers have distinct activities in different cell types and therefore likely non redundant functions. This work demonstrates that unique cell type specific activities can be uncovered for apparently similar enhancers when investigated at high resolution in vivo. Overall design: In order to define the precise cell types within the retina where the PAX6 enhancers HS5 and NRE are active  we carried out scRNA seq on eyes from NRE eGFP/HS5 mCherry zebrafish reporter embryos. With this technique  we aimed to uncover cell type or transcriptional differences between the two enhancer active populations. We dissected eyes from 48 hpf NRE eGFP/HS5 mCherry embryos and used FACS to enrich for either mCherry positive/HS5 active cells or eGFP positive/NRE active cells. Three samples for each population were processed for scRNA seq using the 10x Genomics Chromium single cell three prime gene expression technology.", null, "pubmed:37643867", null, "mcherry enriched rep2", "GSM7702832", null, "source name:Eye|tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf|geo loc name:missing|collection date:missing", "mcherry enriched rep2", "Cell Ranger v6.1.2 was used to perform alignment  filtering  barcode counting  and UMI counting. A custom reference genome was created for alignment using cellranger mkref  combining the Danio rerio GRCz11 genome assembly with manually annotated eGFP and mCherry sequences. Cell calling and QC: The emptyDrops function from DropletUtils was used to filter out empty droplets/barcodes not corresponding to cells Lun et al.  2019. Mitochondrial and ribosomal genes were excluded from the emptyDrops analysis to improve the filtering of droplets containing ambient RNA or cell fragments. The scater package was used to filter cells based on the QC metrics of library size  detected genes  and mitochondrial reads McCarthy et al.  2017. Cells with detected genes \u2265 500  library size \u2265 800  and mitochondrial reads \u2264 10% were retained. Within the processed dataset  mean reads per cell = 11239  and median genes per cell = 1554. Reference mapping and filtering: The SingleR package was used to annotate cell types based on mapping to the zebrafish single cell transcriptome atlas Aran et al.  2019; Farnsworth et al.  2019. Expression matrix and cell annotation data were downloaded from the UCSC cell browser http://zebrafish dev.cells.ucsc.edu; only the 2 dpf data were used for mapping. Erroneously sorted cells of non retinal identity for example pigmented cell types such as melanocytes with high autofluorescence were filtered out at this stage. This was carried out to improve the resolution of clustering for retinal cell types.  Clustering and cell type annotation: Seurat v4 was used for clustering and further analysis for a total of 6 288 cells Butler et al.  2018. SCTransform was used to perform log normalisation  scaling  and highly variable gene HVG detection on a dataset consisting of the 6 samples merged into one. Standard SCTransform options were used  with regression of mitochondrial expression and cell cycle stage using \u2018vars.to.regress\u2019. We performed Principle Component Analysis PCA on the normalized counts matrix restricted to HVGs  using Seurat's RunPCA function with number of PCs = 50. To enable integration of the samples  we then used Harmony to generate PCs corrected for batch effects between libraries Korsunsky et al.  2019. The Harmony PCs were then used to perform K nearest neighbour analysis k=20 and Louvain clustering using Seurat 15 dimensions and resolution 0.6. Clusters were annotated as retinal cell types based on the highest expressed marker genes  and other known genes for each cell type  using information from the literature and ZFIN Sprague et al.  2008. Cell cycle scoring was performed using the Seurat CellCycleScoring function  using zebrafish genes homologous to the \u2018s.features\u2019 and \u2018g2m.features\u2019 genes provided by Seurat. Assembly: GRCz11 Supplementary files format and content: Tab separated values files  matrix files  Seurat object RDS file", "Eye", null, "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell 3\u2019 gene expression technology v3.1.", null, "tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf", "GSM7702832", "GSM7702832: mcherry enriched rep2; Danio rerio; RNA Seq", "GSM7702832 r1", "GSM7702832", "1", "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell three prime gene expression technology v3.1.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "SINGLE", "ILLUMINA", "NextSeq 2000", null, "SRP454539", null, "loader:fastq load.py", "1907_pos_pos_S1_L002_I1_002.fastq.gz 1907_pos_pos_S1_L002_I2_002.fastq.gz 1907_pos_pos_S1_L002_R1_002.fastq.gz 1907_pos_pos_S1_L002_R2_002.fastq.gz", "fastq fastq fastq fastq", 25609437216.0, 185575632.0, "GSM7702832 r4", "0:10 1:10 2:28 3:90", "A:5015380345;C:3509305882;G:3867598814;T:4308011415;N:1510424", 10, 10, 28, 90, 5015380345, 3509305882, 3867598814, 4308011415, 1510424, "SRX21332625", "SRS18578257", "SRA1702612", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", 1, 0.90907, null, 0.11192, null, 0.81994, null, 0.50902, null, 90, null, "B", null, "usable mapping rate", "illumina", "nextseq_v2", "3prime", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United Kingdom", "2023-08-10", "Hatching", "Embryo", "Eye", "Sensory System"], [25123, "SRR25605440", "SRX21332624", "SRS18578256", "SRP454539", "PRJNA1004255", "Unique activities of two overlapping PAX6 retinal enhancers", "GSE240575", "Transcriptome Analysis", "Enhancers play a critical role in development by precisely modulating spatial  temporal  and cell type specific gene expression. Sequence variants in enhancers have been implicated in disease  however establishing the functional consequences of these variants is challenging due to a lack of understanding of precise cell types and developmental stages where the enhancers are normally active. PAX6 is the master regulator of eye development  with a regulatory landscape containing multiple enhancers driving expression in the eye. Whether these enhancers perform additive  redundant  or distinct functions is unknown. Here we describe the precise cell types and regulatory activity of two PAX6 retinal enhancers  HS5 and NRE. Using a unique combination of live imaging and single cell RNA sequencing in dual enhancer reporter zebrafish embryos  we uncover differences in the spatiotemporal activity of these enhancers. Our results show that although overlapping  these enhancers have distinct activities in different cell types and therefore likely non redundant functions. This work demonstrates that unique cell type specific activities can be uncovered for apparently similar enhancers when investigated at high resolution in vivo. Overall design: In order to define the precise cell types within the retina where the PAX6 enhancers HS5 and NRE are active  we carried out scRNA seq on eyes from NRE eGFP/HS5 mCherry zebrafish reporter embryos. With this technique  we aimed to uncover cell type or transcriptional differences between the two enhancer active populations. We dissected eyes from 48 hpf NRE eGFP/HS5 mCherry embryos and used FACS to enrich for either mCherry positive/HS5 active cells or eGFP positive/NRE active cells. Three samples for each population were processed for scRNA seq using the 10x Genomics Chromium single cell three prime gene expression technology.", null, "pubmed:37643867", null, "gfp enriched rep1", "GSM7702831", null, "source name:Eye|tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf|geo loc name:missing|collection date:missing", "gfp enriched rep1", "Cell Ranger v6.1.2 was used to perform alignment  filtering  barcode counting  and UMI counting. A custom reference genome was created for alignment using cellranger mkref  combining the Danio rerio GRCz11 genome assembly with manually annotated eGFP and mCherry sequences. Cell calling and QC: The emptyDrops function from DropletUtils was used to filter out empty droplets/barcodes not corresponding to cells Lun et al.  2019. Mitochondrial and ribosomal genes were excluded from the emptyDrops analysis to improve the filtering of droplets containing ambient RNA or cell fragments. The scater package was used to filter cells based on the QC metrics of library size  detected genes  and mitochondrial reads McCarthy et al.  2017. Cells with detected genes \u2265 500  library size \u2265 800  and mitochondrial reads \u2264 10% were retained. Within the processed dataset  mean reads per cell = 11239  and median genes per cell = 1554. Reference mapping and filtering: The SingleR package was used to annotate cell types based on mapping to the zebrafish single cell transcriptome atlas Aran et al.  2019; Farnsworth et al.  2019. Expression matrix and cell annotation data were downloaded from the UCSC cell browser http://zebrafish dev.cells.ucsc.edu; only the 2 dpf data were used for mapping. Erroneously sorted cells of non retinal identity for example pigmented cell types such as melanocytes with high autofluorescence were filtered out at this stage. This was carried out to improve the resolution of clustering for retinal cell types.  Clustering and cell type annotation: Seurat v4 was used for clustering and further analysis for a total of 6 288 cells Butler et al.  2018. SCTransform was used to perform log normalisation  scaling  and highly variable gene HVG detection on a dataset consisting of the 6 samples merged into one. Standard SCTransform options were used  with regression of mitochondrial expression and cell cycle stage using \u2018vars.to.regress\u2019. We performed Principle Component Analysis PCA on the normalized counts matrix restricted to HVGs  using Seurat's RunPCA function with number of PCs = 50. To enable integration of the samples  we then used Harmony to generate PCs corrected for batch effects between libraries Korsunsky et al.  2019. The Harmony PCs were then used to perform K nearest neighbour analysis k=20 and Louvain clustering using Seurat 15 dimensions and resolution 0.6. Clusters were annotated as retinal cell types based on the highest expressed marker genes  and other known genes for each cell type  using information from the literature and ZFIN Sprague et al.  2008. Cell cycle scoring was performed using the Seurat CellCycleScoring function  using zebrafish genes homologous to the \u2018s.features\u2019 and \u2018g2m.features\u2019 genes provided by Seurat. Assembly: GRCz11 Supplementary files format and content: Tab separated values files  matrix files  Seurat object RDS file", "Eye", null, "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell 3\u2019 gene expression technology v3.1.", null, "tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf", "GSM7702831", "GSM7702831: gfp enriched rep1; Danio rerio; RNA Seq", "GSM7702831 r1", "GSM7702831", "1", "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell three prime gene expression technology v3.1.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "NextSeq 2000", null, "SRP454539", null, "loader:fastq load.py", "gfp_nre_S1_L001_R2_001.fastq.gz gfp_nre_S1_L001_R1_001.fastq.gz gfp_nre_S1_L001_I2_001.fastq.gz gfp_nre_S1_L001_I1_001.fastq.gz", "fastq fastq fastq fastq", 47873499684.0, 346909418.0, "GSM7702831 r1", "0:10 1:10 2:28 3:90", "A:8912593789;C:6786299583;G:7771099171;T:7737013838;N:14841239", 10, 10, 28, 90, 8912593789, 6786299583, 7771099171, 7737013838, 14841239, "SRX21332624", "SRS18578256", "SRA1690580", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", 1, 0.90717, null, 0.15854, null, 0.80501, null, 0.50927, null, 90, null, "B", null, "usable mapping rate", "illumina", "nextseq_v2", "3prime", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United Kingdom", "2023-08-10", "Hatching", "Embryo", "Eye", "Sensory System"], [25124, "SRR25605441", "SRX21332624", "SRS18578256", "SRP454539", "PRJNA1004255", "Unique activities of two overlapping PAX6 retinal enhancers", "GSE240575", "Transcriptome Analysis", "Enhancers play a critical role in development by precisely modulating spatial  temporal  and cell type specific gene expression. Sequence variants in enhancers have been implicated in disease  however establishing the functional consequences of these variants is challenging due to a lack of understanding of precise cell types and developmental stages where the enhancers are normally active. PAX6 is the master regulator of eye development  with a regulatory landscape containing multiple enhancers driving expression in the eye. Whether these enhancers perform additive  redundant  or distinct functions is unknown. Here we describe the precise cell types and regulatory activity of two PAX6 retinal enhancers  HS5 and NRE. Using a unique combination of live imaging and single cell RNA sequencing in dual enhancer reporter zebrafish embryos  we uncover differences in the spatiotemporal activity of these enhancers. Our results show that although overlapping  these enhancers have distinct activities in different cell types and therefore likely non redundant functions. This work demonstrates that unique cell type specific activities can be uncovered for apparently similar enhancers when investigated at high resolution in vivo. Overall design: In order to define the precise cell types within the retina where the PAX6 enhancers HS5 and NRE are active  we carried out scRNA seq on eyes from NRE eGFP/HS5 mCherry zebrafish reporter embryos. With this technique  we aimed to uncover cell type or transcriptional differences between the two enhancer active populations. We dissected eyes from 48 hpf NRE eGFP/HS5 mCherry embryos and used FACS to enrich for either mCherry positive/HS5 active cells or eGFP positive/NRE active cells. Three samples for each population were processed for scRNA seq using the 10x Genomics Chromium single cell three prime gene expression technology.", null, "pubmed:37643867", null, "gfp enriched rep1", "GSM7702831", null, "source name:Eye|tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf|geo loc name:missing|collection date:missing", "gfp enriched rep1", "Cell Ranger v6.1.2 was used to perform alignment  filtering  barcode counting  and UMI counting. A custom reference genome was created for alignment using cellranger mkref  combining the Danio rerio GRCz11 genome assembly with manually annotated eGFP and mCherry sequences. Cell calling and QC: The emptyDrops function from DropletUtils was used to filter out empty droplets/barcodes not corresponding to cells Lun et al.  2019. Mitochondrial and ribosomal genes were excluded from the emptyDrops analysis to improve the filtering of droplets containing ambient RNA or cell fragments. The scater package was used to filter cells based on the QC metrics of library size  detected genes  and mitochondrial reads McCarthy et al.  2017. Cells with detected genes \u2265 500  library size \u2265 800  and mitochondrial reads \u2264 10% were retained. Within the processed dataset  mean reads per cell = 11239  and median genes per cell = 1554. Reference mapping and filtering: The SingleR package was used to annotate cell types based on mapping to the zebrafish single cell transcriptome atlas Aran et al.  2019; Farnsworth et al.  2019. Expression matrix and cell annotation data were downloaded from the UCSC cell browser http://zebrafish dev.cells.ucsc.edu; only the 2 dpf data were used for mapping. Erroneously sorted cells of non retinal identity for example pigmented cell types such as melanocytes with high autofluorescence were filtered out at this stage. This was carried out to improve the resolution of clustering for retinal cell types.  Clustering and cell type annotation: Seurat v4 was used for clustering and further analysis for a total of 6 288 cells Butler et al.  2018. SCTransform was used to perform log normalisation  scaling  and highly variable gene HVG detection on a dataset consisting of the 6 samples merged into one. Standard SCTransform options were used  with regression of mitochondrial expression and cell cycle stage using \u2018vars.to.regress\u2019. We performed Principle Component Analysis PCA on the normalized counts matrix restricted to HVGs  using Seurat's RunPCA function with number of PCs = 50. To enable integration of the samples  we then used Harmony to generate PCs corrected for batch effects between libraries Korsunsky et al.  2019. The Harmony PCs were then used to perform K nearest neighbour analysis k=20 and Louvain clustering using Seurat 15 dimensions and resolution 0.6. Clusters were annotated as retinal cell types based on the highest expressed marker genes  and other known genes for each cell type  using information from the literature and ZFIN Sprague et al.  2008. Cell cycle scoring was performed using the Seurat CellCycleScoring function  using zebrafish genes homologous to the \u2018s.features\u2019 and \u2018g2m.features\u2019 genes provided by Seurat. Assembly: GRCz11 Supplementary files format and content: Tab separated values files  matrix files  Seurat object RDS file", "Eye", null, "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell 3\u2019 gene expression technology v3.1.", null, "tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf", "GSM7702831", "GSM7702831: gfp enriched rep1; Danio rerio; RNA Seq", "GSM7702831 r1", "GSM7702831", "1", "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell three prime gene expression technology v3.1.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "NextSeq 2000", null, "SRP454539", null, "loader:fastq load.py", "gfp_nre_S1_L002_I1_001.fastq.gz gfp_nre_S1_L002_I2_001.fastq.gz gfp_nre_S1_L002_R1_001.fastq.gz gfp_nre_S1_L002_R2_001.fastq.gz", "fastq fastq fastq fastq", 48659347860.0, 352603970.0, "GSM7702831 r2", "0:10 1:10 2:28 3:90", "A:9056524463;C:6888387179;G:7922807308;T:7854042793;N:12595557", 10, 10, 28, 90, 9056524463, 6888387179, 7922807308, 7854042793, 12595557, "SRX21332624", "SRS18578256", "SRA1690580", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", 1, 0.90541, null, 0.15686, null, 0.80543, null, 0.51051, null, 90, null, "B", null, "usable mapping rate", "illumina", "nextseq_v2", "3prime", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United Kingdom", "2023-08-10", "Hatching", "Embryo", "Eye", "Sensory System"], [25125, "SRR25605442", "SRX21332623", "SRS18578255", "SRP454539", "PRJNA1004255", "Unique activities of two overlapping PAX6 retinal enhancers", "GSE240575", "Transcriptome Analysis", "Enhancers play a critical role in development by precisely modulating spatial  temporal  and cell type specific gene expression. Sequence variants in enhancers have been implicated in disease  however establishing the functional consequences of these variants is challenging due to a lack of understanding of precise cell types and developmental stages where the enhancers are normally active. PAX6 is the master regulator of eye development  with a regulatory landscape containing multiple enhancers driving expression in the eye. Whether these enhancers perform additive  redundant  or distinct functions is unknown. Here we describe the precise cell types and regulatory activity of two PAX6 retinal enhancers  HS5 and NRE. Using a unique combination of live imaging and single cell RNA sequencing in dual enhancer reporter zebrafish embryos  we uncover differences in the spatiotemporal activity of these enhancers. Our results show that although overlapping  these enhancers have distinct activities in different cell types and therefore likely non redundant functions. This work demonstrates that unique cell type specific activities can be uncovered for apparently similar enhancers when investigated at high resolution in vivo. Overall design: In order to define the precise cell types within the retina where the PAX6 enhancers HS5 and NRE are active  we carried out scRNA seq on eyes from NRE eGFP/HS5 mCherry zebrafish reporter embryos. With this technique  we aimed to uncover cell type or transcriptional differences between the two enhancer active populations. We dissected eyes from 48 hpf NRE eGFP/HS5 mCherry embryos and used FACS to enrich for either mCherry positive/HS5 active cells or eGFP positive/NRE active cells. Three samples for each population were processed for scRNA seq using the 10x Genomics Chromium single cell three prime gene expression technology.", null, "pubmed:37643867", null, "mcherry enriched rep1", "GSM7702830", null, "source name:Eye|tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf|geo loc name:missing|collection date:missing", "mcherry enriched rep1", "Cell Ranger v6.1.2 was used to perform alignment  filtering  barcode counting  and UMI counting. A custom reference genome was created for alignment using cellranger mkref  combining the Danio rerio GRCz11 genome assembly with manually annotated eGFP and mCherry sequences. Cell calling and QC: The emptyDrops function from DropletUtils was used to filter out empty droplets/barcodes not corresponding to cells Lun et al.  2019. Mitochondrial and ribosomal genes were excluded from the emptyDrops analysis to improve the filtering of droplets containing ambient RNA or cell fragments. The scater package was used to filter cells based on the QC metrics of library size  detected genes  and mitochondrial reads McCarthy et al.  2017. Cells with detected genes \u2265 500  library size \u2265 800  and mitochondrial reads \u2264 10% were retained. Within the processed dataset  mean reads per cell = 11239  and median genes per cell = 1554. Reference mapping and filtering: The SingleR package was used to annotate cell types based on mapping to the zebrafish single cell transcriptome atlas Aran et al.  2019; Farnsworth et al.  2019. Expression matrix and cell annotation data were downloaded from the UCSC cell browser http://zebrafish dev.cells.ucsc.edu; only the 2 dpf data were used for mapping. Erroneously sorted cells of non retinal identity for example pigmented cell types such as melanocytes with high autofluorescence were filtered out at this stage. This was carried out to improve the resolution of clustering for retinal cell types.  Clustering and cell type annotation: Seurat v4 was used for clustering and further analysis for a total of 6 288 cells Butler et al.  2018. SCTransform was used to perform log normalisation  scaling  and highly variable gene HVG detection on a dataset consisting of the 6 samples merged into one. Standard SCTransform options were used  with regression of mitochondrial expression and cell cycle stage using \u2018vars.to.regress\u2019. We performed Principle Component Analysis PCA on the normalized counts matrix restricted to HVGs  using Seurat's RunPCA function with number of PCs = 50. To enable integration of the samples  we then used Harmony to generate PCs corrected for batch effects between libraries Korsunsky et al.  2019. The Harmony PCs were then used to perform K nearest neighbour analysis k=20 and Louvain clustering using Seurat 15 dimensions and resolution 0.6. Clusters were annotated as retinal cell types based on the highest expressed marker genes  and other known genes for each cell type  using information from the literature and ZFIN Sprague et al.  2008. Cell cycle scoring was performed using the Seurat CellCycleScoring function  using zebrafish genes homologous to the \u2018s.features\u2019 and \u2018g2m.features\u2019 genes provided by Seurat. Assembly: GRCz11 Supplementary files format and content: Tab separated values files  matrix files  Seurat object RDS file", "Eye", null, "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell 3\u2019 gene expression technology v3.1.", null, "tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf", "GSM7702830", "GSM7702830: mcherry enriched rep1; Danio rerio; RNA Seq", "GSM7702830 r1", "GSM7702830", "1", "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell three prime gene expression technology v3.1.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "NextSeq 2000", null, "SRP454539", null, "loader:fastq load.py", "double_pos_S2_L001_R2_001.fastq.gz double_pos_S2_L001_R1_001.fastq.gz double_pos_S2_L001_I2_001.fastq.gz double_pos_S2_L001_I1_001.fastq.gz", "fastq fastq fastq fastq", 41371188084.0, 299791218.0, "GSM7702830 r1", "0:10 1:10 2:28 3:90", "A:7690531012;C:5787287634;G:6514950407;T:6975618202;N:12822365", 10, 10, 28, 90, 7690531012, 5787287634, 6514950407, 6975618202, 12822365, "SRX21332623", "SRS18578255", "SRA1690580", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", 1, 0.93894, null, 0.17677, null, 0.79926, null, 0.51122, null, 90, null, "B", null, "usable mapping rate", "illumina", "nextseq_v2", "3prime", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United Kingdom", "2023-08-10", "Hatching", "Embryo", "Eye", "Sensory System"], [25126, "SRR25605443", "SRX21332623", "SRS18578255", "SRP454539", "PRJNA1004255", "Unique activities of two overlapping PAX6 retinal enhancers", "GSE240575", "Transcriptome Analysis", "Enhancers play a critical role in development by precisely modulating spatial  temporal  and cell type specific gene expression. Sequence variants in enhancers have been implicated in disease  however establishing the functional consequences of these variants is challenging due to a lack of understanding of precise cell types and developmental stages where the enhancers are normally active. PAX6 is the master regulator of eye development  with a regulatory landscape containing multiple enhancers driving expression in the eye. Whether these enhancers perform additive  redundant  or distinct functions is unknown. Here we describe the precise cell types and regulatory activity of two PAX6 retinal enhancers  HS5 and NRE. Using a unique combination of live imaging and single cell RNA sequencing in dual enhancer reporter zebrafish embryos  we uncover differences in the spatiotemporal activity of these enhancers. Our results show that although overlapping  these enhancers have distinct activities in different cell types and therefore likely non redundant functions. This work demonstrates that unique cell type specific activities can be uncovered for apparently similar enhancers when investigated at high resolution in vivo. Overall design: In order to define the precise cell types within the retina where the PAX6 enhancers HS5 and NRE are active  we carried out scRNA seq on eyes from NRE eGFP/HS5 mCherry zebrafish reporter embryos. With this technique  we aimed to uncover cell type or transcriptional differences between the two enhancer active populations. We dissected eyes from 48 hpf NRE eGFP/HS5 mCherry embryos and used FACS to enrich for either mCherry positive/HS5 active cells or eGFP positive/NRE active cells. Three samples for each population were processed for scRNA seq using the 10x Genomics Chromium single cell three prime gene expression technology.", null, "pubmed:37643867", null, "mcherry enriched rep1", "GSM7702830", null, "source name:Eye|tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf|geo loc name:missing|collection date:missing", "mcherry enriched rep1", "Cell Ranger v6.1.2 was used to perform alignment  filtering  barcode counting  and UMI counting. A custom reference genome was created for alignment using cellranger mkref  combining the Danio rerio GRCz11 genome assembly with manually annotated eGFP and mCherry sequences. Cell calling and QC: The emptyDrops function from DropletUtils was used to filter out empty droplets/barcodes not corresponding to cells Lun et al.  2019. Mitochondrial and ribosomal genes were excluded from the emptyDrops analysis to improve the filtering of droplets containing ambient RNA or cell fragments. The scater package was used to filter cells based on the QC metrics of library size  detected genes  and mitochondrial reads McCarthy et al.  2017. Cells with detected genes \u2265 500  library size \u2265 800  and mitochondrial reads \u2264 10% were retained. Within the processed dataset  mean reads per cell = 11239  and median genes per cell = 1554. Reference mapping and filtering: The SingleR package was used to annotate cell types based on mapping to the zebrafish single cell transcriptome atlas Aran et al.  2019; Farnsworth et al.  2019. Expression matrix and cell annotation data were downloaded from the UCSC cell browser http://zebrafish dev.cells.ucsc.edu; only the 2 dpf data were used for mapping. Erroneously sorted cells of non retinal identity for example pigmented cell types such as melanocytes with high autofluorescence were filtered out at this stage. This was carried out to improve the resolution of clustering for retinal cell types.  Clustering and cell type annotation: Seurat v4 was used for clustering and further analysis for a total of 6 288 cells Butler et al.  2018. SCTransform was used to perform log normalisation  scaling  and highly variable gene HVG detection on a dataset consisting of the 6 samples merged into one. Standard SCTransform options were used  with regression of mitochondrial expression and cell cycle stage using \u2018vars.to.regress\u2019. We performed Principle Component Analysis PCA on the normalized counts matrix restricted to HVGs  using Seurat's RunPCA function with number of PCs = 50. To enable integration of the samples  we then used Harmony to generate PCs corrected for batch effects between libraries Korsunsky et al.  2019. The Harmony PCs were then used to perform K nearest neighbour analysis k=20 and Louvain clustering using Seurat 15 dimensions and resolution 0.6. Clusters were annotated as retinal cell types based on the highest expressed marker genes  and other known genes for each cell type  using information from the literature and ZFIN Sprague et al.  2008. Cell cycle scoring was performed using the Seurat CellCycleScoring function  using zebrafish genes homologous to the \u2018s.features\u2019 and \u2018g2m.features\u2019 genes provided by Seurat. Assembly: GRCz11 Supplementary files format and content: Tab separated values files  matrix files  Seurat object RDS file", "Eye", null, "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell 3\u2019 gene expression technology v3.1.", null, "tissue:Eye|genotype:NRE eGFP/HS5 mCherry|developmental stage:48 hpf", "GSM7702830", "GSM7702830: mcherry enriched rep1; Danio rerio; RNA Seq", "GSM7702830 r1", "GSM7702830", "1", "NRE eGFP/HS5 mCherry embryos were collected and treated with PTU from 12 hpf. At 48 hpf  embryos were anaesthetised with Tricaine 20\u201330 mg/l and placed into Danieau's solution. Eyes were dissected from 100 150 embryos using fine forceps Dumont #5SF  and immediately placed into Danieau's solution on ice. Samples were centrifuged at 300g for 1 minute at 4\u00b0C  then washed with Danieau's solution. Washing step was carried out three times with Danieau's solution  and once with FACSmax Amsbio. In a final 500 \u00b5l FACSmax  the samples were passed through a 35 \u00b5m cell strainer to obtain single cell suspension on ice. Samples were sorted for mCherry and eGFP fluorescence using a FACS Aria II BD or CytoFLEX SRT Beckman Coulter machine. Forward and side scatter sorting was used to select single cells from clumps and debris  and DAPI staining was used to exclude dead cells. Libraries were prepared using the 10x Genomics Chromium single cell three prime gene expression technology v3.1.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "NextSeq 2000", null, "SRP454539", null, "loader:fastq load.py", "double_pos_S2_L002_I1_001.fastq.gz double_pos_S2_L002_I2_001.fastq.gz double_pos_S2_L002_R1_001.fastq.gz double_pos_S2_L002_R2_001.fastq.gz", "fastq fastq fastq fastq", 42692812980.0, 309368210.0, "GSM7702830 r2", "0:10 1:10 2:28 3:90", "A:7933061913;C:5964617781;G:6744802923;T:7189579846;N:11076437", 10, 10, 28, 90, 7933061913, 5964617781, 6744802923, 7189579846, 11076437, "SRX21332623", "SRS18578255", "SRA1690580", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", "Wendy Bickmore, MRC Human Genetics Unit, University of Edinburgh", 1, 0.93887, null, 0.17578, null, 0.79825, null, 0.50169, null, 90, null, "B", null, "usable mapping rate", "illumina", "nextseq_v2", "3prime", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United Kingdom", "2023-08-10", "Hatching", "Embryo", "Eye", "Sensory System"], [29174, "SRR27237224", "SRX22915658", "SRS19883761", "SRP478464", "PRJNA1053781", "Single cell gene expression profie of developing photoreceptor cells in larval zebrafish", "GSE250379", "Other", "Molecular underpinnings of vertebrate retinal differentiation and maturation are poorly understood  particularly for non mammalian species. We generated single cell transcriptome data from the larval zebrafish retina and characterized gene expression diversity among photoreceptor subtypes and their progenitors. Overall design: GFP positive differentiating photoreceptor cells and bipolar cells were collected from 4 dpf larval transgenic zebrafish  Tgcrx:EGFPstl887  using fluorescence activated cell sorting.", "parent bioproject:PRJNA1050288", "pubmed:39531499", null, "retina  scRNA seq", "GSM7978132", null, "source name:retina|tissue:retina|genotype:Tgcrx:EGFPstl887|developmental stage:4 dpf|geo loc name:missing|collection date:missing", "retina  scRNA seq", "Read alignment and initial quality control were performed using Cell Ranger software version 7.0.0  10X Genomics. Assembly: GRCz11 Supplementary files format and content: Tab separated value file and matrix file", "retina", null, "Fifty heads were dissected from 4 dpf heterozygous Tgcrx:GFPstl887Tg larvae. Following dissection  eyes were stored in ice cold Hanks\u2019 Balanced Salt Solution HBSS until all eyes were harvested. Once the eyes were collected  HBSS was removed and the eyes were incubated in 400 \u00b5l of calcium/magnesium free HBSS containing 0.4 mg papain Worthington Biochem for 15 min at 37\u00b0C. 800 \u00b5l of 10% fetal bovine serum FBS in Dulbecco's Modified Eagle Medium DMEM containing 5mM MgCl2 and 120 units DNaseI Roche were added to the mixture and incubated for 5 min at 37\u00b0C. Cells were then resuspended in 300 \u00b5l of sorting buffer 2.5 mM EDTA  25 mM HEPES  1% bovine serum albumin BSA in calcium/magnesium free HBSS. Cells were sorted on an Aria II FACS machine BD biosciences with gating based on forward scatter  side scatter  and GFP fluorescence and collected in 700 \u03bcl of D PBS without xxx+ and Mg2+  supplemented with 0.4 % BSA D PBS CMF in 1.5 ml microcentrifuge tubes. The collected cells were then centrifuged at 300\u00d7g for 5 min  washed with D PBS CMF  centrifuged  and supernatant reduced to 80 \u00b5l. Cell density was quantified on a hemocytometer  and  5000 cells were used for single cell library preparation. A library for single cell RNA seq was constructed with the Chromium v3  platform  10X  Genomics   Pleasanton   CA according to the manufacturer protocol.", null, "tissue:retina|genotype:Tgcrx:EGFPstl887|developmental stage:4 dpf", "GSM7978132", "GSM7978132: retina  scRNA seq; Danio rerio; RNA Seq", "GSM7978132 r1", "GSM7978132", "1", "Fifty heads were dissected from 4 dpf heterozygous Tgcrx:GFPstl887Tg larvae. Following dissection  eyes were stored in ice cold Hanks' Balanced Salt Solution HBSS until all eyes were harvested. Once the eyes were collected  HBSS was removed and the eyes were incubated in 400 \u00b5l of calcium/magnesium free HBSS containing 0.4 mg papain Worthington Biochem for 15 min at 37\u00b0C. 800 \u00b5l of 10% fetal bovine serum FBS in Dulbecco's Modified Eagle Medium DMEM containing 5mM MgCl2 and 120 units DNaseI Roche were added to the mixture and incubated for 5 min at 37\u00b0C. Cells were then resuspended in 300 \u00b5l of sorting buffer 2.5 mM EDTA  25 mM HEPES  1% bovine serum albumin BSA in calcium/magnesium free HBSS. Cells were sorted on an Aria II FACS machine BD biosciences with gating based on forward scatter  side scatter  and GFP fluorescence and collected in 700 \u03bcl of D PBS without xxx+ and Mg2+  supplemented with 0.4 % BSA D PBS CMF in 1.5 ml microcentrifuge tubes. The collected cells were then centrifuged at 300\u00d7g for 5 min  washed with D PBS CMF  centrifuged  and supernatant reduced to 80 \u00b5l. Cell density was quantified on a hemocytometer  and  5000 cells were used for single cell library preparation. A library for single cell RNA seq was constructed with the Chromium v3  platform  10X  Genomics   Pleasanton   CA according to the manufacturer protocol.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP478464", null, "loader:fastq load.py", "crx.crx_S1_L003_R1_001.fastq.gz crx.crx_S1_L003_R2_001.fastq.gz", "fastq fastq", 45170138494.0, 253764823.0, "GSM7978132 r1", "0:28 1:150", "A:13826023801;C:9023674621;G:9590649474;T:12728940802;N:849796", 28, 150, null, null, 13826023801, 9023674621, 9590649474, 12728940802, 849796, "SRX22915658", "SRS19883761", "SRA1770358", "Pathology and Immunology, Washington University School of Medicine", "Pathology and Immunology, Washington University School of Medicine", 2, 0.0046, 0.87155, 0.00206, 0.2263, 0.99168, 0.77784, 0.30223, 0.50112, 28, 150, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2023-12-17", "Larval", "Larval", "Eye", "Sensory System"], [32194, "SRR29141332", "SRX24663085", "SRS21398383", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Multiome rgc:ntr preablation wildtype control day 5 RNA", "GSM8287442", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Multiome rgc:ntr preablation wildtype control day 5 RNA", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287442", "GSM8287442: Multiome rgc:ntr preablation wildtype control day 5 RNA; Danio rerio; RNA Seq", "GSM8287442 r1", "GSM8287442", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH182R_S1_L001_R1_001.fastq.gz TH182R_S1_L001_R2_001.fastq.gz", "fastq fastq", 13807554173.0, 116029867.0, "GSM8287442 r1", "0:28 1:91", "A:4079582572;C:2862550576;G:2918085175;T:3947000701;N:335149", 28, 91, null, null, 4079582572, 2862550576, 2918085175, 3947000701, 335149, "SRX24663085", "SRS21398383", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32195, "SRR29141333", "SRX24663085", "SRS21398383", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Multiome rgc:ntr preablation wildtype control day 5 RNA", "GSM8287442", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Multiome rgc:ntr preablation wildtype control day 5 RNA", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287442", "GSM8287442: Multiome rgc:ntr preablation wildtype control day 5 RNA; Danio rerio; RNA Seq", "GSM8287442 r1", "GSM8287442", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH182R_S1_L002_R1_001.fastq.gz TH182R_S1_L002_R2_001.fastq.gz", "fastq fastq", 13803126064.0, 115992656.0, "GSM8287442 r2", "0:28 1:91", "A:4078989982;C:2861718905;G:2916062814;T:3946005912;N:348451", 28, 91, null, null, 4078989982, 2861718905, 2916062814, 3946005912, 348451, "SRX24663085", "SRS21398383", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32196, "SRR29141334", "SRX24663085", "SRS21398383", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Multiome rgc:ntr preablation wildtype control day 5 RNA", "GSM8287442", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Multiome rgc:ntr preablation wildtype control day 5 RNA", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287442", "GSM8287442: Multiome rgc:ntr preablation wildtype control day 5 RNA; Danio rerio; RNA Seq", "GSM8287442 r1", "GSM8287442", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH182R_S1_L003_R1_001.fastq.gz TH182R_S1_L003_R2_001.fastq.gz", "fastq fastq", 14039364150.0, 117977850.0, "GSM8287442 r3", "0:28 1:91", "A:4148421178;C:2910249087;G:2967774612;T:4012572976;N:346297", 28, 91, null, null, 4148421178, 2910249087, 2967774612, 4012572976, 346297, "SRX24663085", "SRS21398383", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32197, "SRR29141335", "SRX24663085", "SRS21398383", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Multiome rgc:ntr preablation wildtype control day 5 RNA", "GSM8287442", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Multiome rgc:ntr preablation wildtype control day 5 RNA", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287442", "GSM8287442: Multiome rgc:ntr preablation wildtype control day 5 RNA; Danio rerio; RNA Seq", "GSM8287442 r1", "GSM8287442", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH182R_S1_L004_R1_001.fastq.gz TH182R_S1_L004_R2_001.fastq.gz", "fastq fastq", 14396508973.0, 120979067.0, "GSM8287442 r4", "0:28 1:91", "A:4252694309;C:2985039203;G:3045994377;T:4112440375;N:340709", 28, 91, null, null, 4252694309, 2985039203, 3045994377, 4112440375, 340709, "SRX24663085", "SRS21398383", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32198, "SRR29141336", "SRX24663084", "SRS21398382", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 7 24h mtz", "GSM8287437", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 7 24h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287437", "GSM8287437: Ablated rgc:ntr day 7 24h mtz; Danio rerio; RNA Seq", "GSM8287437 r1", "GSM8287437", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH111_S65_R1_001.fastq.gz TH111_S65_R2_001.fastq.gz", "fastq fastq", 10009743191.0, 84115489.0, "GSM8287437 r1", "0:28 1:91", "A:2899067167;C:2137099335;G:2274433670;T:2671820531;N:27322488", 28, 91, null, null, 2899067167, 2137099335, 2274433670, 2671820531, 27322488, "SRX24663084", "SRS21398382", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32199, "SRR29141337", "SRX24663084", "SRS21398382", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 7 24h mtz", "GSM8287437", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 7 24h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287437", "GSM8287437: Ablated rgc:ntr day 7 24h mtz; Danio rerio; RNA Seq", "GSM8287437 r1", "GSM8287437", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH111_S66_R1_001.fastq.gz TH111_S66_R2_001.fastq.gz", "fastq fastq", 10310944686.0, 86646594.0, "GSM8287437 r2", "0:28 1:91", "A:2991162064;C:2200127755;G:2335919653;T:2755298440;N:28436774", 28, 91, null, null, 2991162064, 2200127755, 2335919653, 2755298440, 28436774, "SRX24663084", "SRS21398382", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32200, "SRR29141338", "SRX24663084", "SRS21398382", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 7 24h mtz", "GSM8287437", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 7 24h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287437", "GSM8287437: Ablated rgc:ntr day 7 24h mtz; Danio rerio; RNA Seq", "GSM8287437 r1", "GSM8287437", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH111_S68_R1_001.fastq.gz TH111_S68_R2_001.fastq.gz", "fastq fastq", 13987726480.0, 117543920.0, "GSM8287437 r3", "0:28 1:91", "A:4045259735;C:2989556292;G:3181238633;T:3733480210;N:38191610", 28, 91, null, null, 4045259735, 2989556292, 3181238633, 3733480210, 38191610, "SRX24663084", "SRS21398382", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32201, "SRR29141339", "SRX24663084", "SRS21398382", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 7 24h mtz", "GSM8287437", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 7 24h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287437", "GSM8287437: Ablated rgc:ntr day 7 24h mtz; Danio rerio; RNA Seq", "GSM8287437 r1", "GSM8287437", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH111_S67_R1_001.fastq.gz TH111_S67_R2_001.fastq.gz", "fastq fastq", 11876682069.0, 99804051.0, "GSM8287437 r4", "0:28 1:91", "A:3432787756;C:2538691346;G:2701757248;T:3170892876;N:32552843", 28, 91, null, null, 3432787756, 2538691346, 2701757248, 3170892876, 32552843, "SRX24663084", "SRS21398382", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32202, "SRR29141340", "SRX24663083", "SRS21398381", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 9 72h mtz", "GSM8287441", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 9 72h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287441", "GSM8287441: Ablated rgc:ntr day 9 72h mtz; Danio rerio; RNA Seq", "GSM8287441 r1", "GSM8287441", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH136_S61_L001_R1_001.fastq.gz TH136_S61_L001_R2_001.fastq.gz", "fastq fastq", 4774895706.0, 40125174.0, "GSM8287441 r1", "0:28 1:91", "A:1351265716;C:1042777184;G:1100567875;T:1280161557;N:123374", 28, 91, null, null, 1351265716, 1042777184, 1100567875, 1280161557, 123374, "SRX24663083", "SRS21398381", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32203, "SRR29141341", "SRX24663083", "SRS21398381", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 9 72h mtz", "GSM8287441", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 9 72h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287441", "GSM8287441: Ablated rgc:ntr day 9 72h mtz; Danio rerio; RNA Seq", "GSM8287441 r1", "GSM8287441", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH136_S64_L003_R1_001.fastq.gz TH136_S64_L003_R2_001.fastq.gz", "fastq fastq", 5538657579.0, 46543341.0, "GSM8287441 r10", "0:28 1:91", "A:1567217187;C:1211616483;G:1275241958;T:1484449584;N:132367", 28, 91, null, null, 1567217187, 1211616483, 1275241958, 1484449584, 132367, "SRX24663083", "SRS21398381", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32204, "SRR29141342", "SRX24663083", "SRS21398381", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 9 72h mtz", "GSM8287441", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 9 72h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287441", "GSM8287441: Ablated rgc:ntr day 9 72h mtz; Danio rerio; RNA Seq", "GSM8287441 r1", "GSM8287441", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH136_S64_L004_R1_001.fastq.gz TH136_S64_L004_R2_001.fastq.gz", "fastq fastq", 5403469057.0, 45407303.0, "GSM8287441 r11", "0:28 1:91", "A:1530355512;C:1180686287;G:1242924943;T:1449389493;N:112822", 28, 91, null, null, 1530355512, 1180686287, 1242924943, 1449389493, 112822, "SRX24663083", "SRS21398381", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32205, "SRR29141343", "SRX24663083", "SRS21398381", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 9 72h mtz", "GSM8287441", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 9 72h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287441", "GSM8287441: Ablated rgc:ntr day 9 72h mtz; Danio rerio; RNA Seq", "GSM8287441 r1", "GSM8287441", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH136_S61_L002_R1_001.fastq.gz TH136_S61_L002_R2_001.fastq.gz", "fastq fastq", 4786338627.0, 40221333.0, "GSM8287441 r12", "0:28 1:91", "A:1355122219;C:1044516973;G:1101760300;T:1284824360;N:114775", 28, 91, null, null, 1355122219, 1044516973, 1101760300, 1284824360, 114775, "SRX24663083", "SRS21398381", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32206, "SRR29141344", "SRX24663083", "SRS21398381", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 9 72h mtz", "GSM8287441", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 9 72h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287441", "GSM8287441: Ablated rgc:ntr day 9 72h mtz; Danio rerio; RNA Seq", "GSM8287441 r1", "GSM8287441", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH136_S62_L001_R1_001.fastq.gz TH136_S62_L001_R2_001.fastq.gz", "fastq fastq", 4901760535.0, 41191265.0, "GSM8287441 r13", "0:28 1:91", "A:1391714409;C:1068852387;G:1124767182;T:1316299153;N:127404", 28, 91, null, null, 1391714409, 1068852387, 1124767182, 1316299153, 127404, "SRX24663083", "SRS21398381", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32207, "SRR29141345", "SRX24663083", "SRS21398381", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 9 72h mtz", "GSM8287441", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 9 72h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287441", "GSM8287441: Ablated rgc:ntr day 9 72h mtz; Danio rerio; RNA Seq", "GSM8287441 r1", "GSM8287441", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH136_S62_L004_R1_001.fastq.gz TH136_S62_L004_R2_001.fastq.gz", "fastq fastq", 4937865968.0, 41494672.0, "GSM8287441 r14", "0:28 1:91", "A:1399404530;C:1078622301;G:1134489765;T:1325245845;N:103527", 28, 91, null, null, 1399404530, 1078622301, 1134489765, 1325245845, 103527, "SRX24663083", "SRS21398381", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32208, "SRR29141346", "SRX24663083", "SRS21398381", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 9 72h mtz", "GSM8287441", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 9 72h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287441", "GSM8287441: Ablated rgc:ntr day 9 72h mtz; Danio rerio; RNA Seq", "GSM8287441 r1", "GSM8287441", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH136_S63_L003_R1_001.fastq.gz TH136_S63_L003_R2_001.fastq.gz", "fastq fastq", 4497873940.0, 37797260.0, "GSM8287441 r15", "0:28 1:91", "A:1271859460;C:985043807;G:1034974096;T:1205889617;N:106960", 28, 91, null, null, 1271859460, 985043807, 1034974096, 1205889617, 106960, "SRX24663083", "SRS21398381", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32209, "SRR29141347", "SRX24663083", "SRS21398381", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 9 72h mtz", "GSM8287441", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 9 72h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287441", "GSM8287441: Ablated rgc:ntr day 9 72h mtz; Danio rerio; RNA Seq", "GSM8287441 r1", "GSM8287441", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH136_S64_L002_R1_001.fastq.gz TH136_S64_L002_R2_001.fastq.gz", "fastq fastq", 5236234787.0, 44001973.0, "GSM8287441 r16", "0:28 1:91", "A:1486231119;C:1141729846;G:1201608482;T:1406539690;N:125650", 28, 91, null, null, 1486231119, 1141729846, 1201608482, 1406539690, 125650, "SRX24663083", "SRS21398381", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32210, "SRR29141348", "SRX24663083", "SRS21398381", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 9 72h mtz", "GSM8287441", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 9 72h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287441", "GSM8287441: Ablated rgc:ntr day 9 72h mtz; Danio rerio; RNA Seq", "GSM8287441 r1", "GSM8287441", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH136_S61_L003_R1_001.fastq.gz TH136_S61_L003_R2_001.fastq.gz", "fastq fastq", 5047989877.0, 42420083.0, "GSM8287441 r2", "0:28 1:91", "A:1424658452;C:1105197562;G:1165585488;T:1352428003;N:120372", 28, 91, null, null, 1424658452, 1105197562, 1165585488, 1352428003, 120372, "SRX24663083", "SRS21398381", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32211, "SRR29141349", "SRX24663083", "SRS21398381", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 9 72h mtz", "GSM8287441", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 9 72h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287441", "GSM8287441: Ablated rgc:ntr day 9 72h mtz; Danio rerio; RNA Seq", "GSM8287441 r1", "GSM8287441", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH136_S61_L004_R1_001.fastq.gz TH136_S61_L004_R2_001.fastq.gz", "fastq fastq", 4922634682.0, 41366678.0, "GSM8287441 r3", "0:28 1:91", "A:1390880945;C:1076385249;G:1135254796;T:1320011695;N:101997", 28, 91, null, null, 1390880945, 1076385249, 1135254796, 1320011695, 101997, "SRX24663083", "SRS21398381", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32212, "SRR29141350", "SRX24663083", "SRS21398381", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 9 72h mtz", "GSM8287441", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 9 72h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287441", "GSM8287441: Ablated rgc:ntr day 9 72h mtz; Danio rerio; RNA Seq", "GSM8287441 r1", "GSM8287441", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH136_S62_L002_R1_001.fastq.gz TH136_S62_L002_R2_001.fastq.gz", "fastq fastq", 4903434746.0, 41205334.0, "GSM8287441 r4", "0:28 1:91", "A:1392700449;C:1068492247;G:1123677701;T:1318447188;N:117161", 28, 91, null, null, 1392700449, 1068492247, 1123677701, 1318447188, 117161, "SRX24663083", "SRS21398381", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32213, "SRR29141351", "SRX24663083", "SRS21398381", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 9 72h mtz", "GSM8287441", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 9 72h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287441", "GSM8287441: Ablated rgc:ntr day 9 72h mtz; Danio rerio; RNA Seq", "GSM8287441 r1", "GSM8287441", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH136_S62_L003_R1_001.fastq.gz TH136_S62_L003_R2_001.fastq.gz", "fastq fastq", 5079175136.0, 42682144.0, "GSM8287441 r5", "0:28 1:91", "A:1438032514;C:1110731492;G:1168141629;T:1362147196;N:122305", 28, 91, null, null, 1438032514, 1110731492, 1168141629, 1362147196, 122305, "SRX24663083", "SRS21398381", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32214, "SRR29141352", "SRX24663083", "SRS21398381", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 9 72h mtz", "GSM8287441", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 9 72h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287441", "GSM8287441: Ablated rgc:ntr day 9 72h mtz; Danio rerio; RNA Seq", "GSM8287441 r1", "GSM8287441", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH136_S63_L001_R1_001.fastq.gz TH136_S63_L001_R2_001.fastq.gz", "fastq fastq", 4248222293.0, 35699347.0, "GSM8287441 r6", "0:28 1:91", "A:1204282194;C:928219300;G:975617558;T:1139994829;N:108412", 28, 91, null, null, 1204282194, 928219300, 975617558, 1139994829, 108412, "SRX24663083", "SRS21398381", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32215, "SRR29141353", "SRX24663083", "SRS21398381", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 9 72h mtz", "GSM8287441", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 9 72h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287441", "GSM8287441: Ablated rgc:ntr day 9 72h mtz; Danio rerio; RNA Seq", "GSM8287441 r1", "GSM8287441", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH136_S63_L002_R1_001.fastq.gz TH136_S63_L002_R2_001.fastq.gz", "fastq fastq", 4256614411.0, 35769869.0, "GSM8287441 r7", "0:28 1:91", "A:1207165748;C:929375627;G:976155057;T:1143817351;N:100628", 28, 91, null, null, 1207165748, 929375627, 976155057, 1143817351, 100628, "SRX24663083", "SRS21398381", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32216, "SRR29141354", "SRX24663083", "SRS21398381", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 9 72h mtz", "GSM8287441", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 9 72h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287441", "GSM8287441: Ablated rgc:ntr day 9 72h mtz; Danio rerio; RNA Seq", "GSM8287441 r1", "GSM8287441", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH136_S63_L004_R1_001.fastq.gz TH136_S63_L004_R2_001.fastq.gz", "fastq fastq", 4376437534.0, 36776786.0, "GSM8287441 r8", "0:28 1:91", "A:1238798346;C:957263182;G:1005958070;T:1174327377;N:90559", 28, 91, null, null, 1238798346, 957263182, 1005958070, 1174327377, 90559, "SRX24663083", "SRS21398381", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32217, "SRR29141355", "SRX24663083", "SRS21398381", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 9 72h mtz", "GSM8287441", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 9 72h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287441", "GSM8287441: Ablated rgc:ntr day 9 72h mtz; Danio rerio; RNA Seq", "GSM8287441 r1", "GSM8287441", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH136_S64_L001_R1_001.fastq.gz TH136_S64_L001_R2_001.fastq.gz", "fastq fastq", 5222497546.0, 43886534.0, "GSM8287441 r9", "0:28 1:91", "A:1481856778;C:1139695420;G:1200133908;T:1400676121;N:135319", 28, 91, null, null, 1481856778, 1139695420, 1200133908, 1400676121, 135319, "SRX24663083", "SRS21398381", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32218, "SRR29141356", "SRX24663082", "SRS21398380", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 6 12h mtz", "GSM8287440", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 6 12h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287440", "GSM8287440: Ablated rgc:ntr day 6 12h mtz; Danio rerio; RNA Seq", "GSM8287440 r1", "GSM8287440", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH135_S57_L001_R1_001.fastq.gz TH135_S57_L001_R2_001.fastq.gz", "fastq fastq", 4775761788.0, 40132452.0, "GSM8287440 r1", "0:28 1:91", "A:1364997508;C:1030536901;G:1087120578;T:1292982564;N:124237", 28, 91, null, null, 1364997508, 1030536901, 1087120578, 1292982564, 124237, "SRX24663082", "SRS21398380", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32219, "SRR29141357", "SRX24663082", "SRS21398380", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 6 12h mtz", "GSM8287440", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 6 12h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287440", "GSM8287440: Ablated rgc:ntr day 6 12h mtz; Danio rerio; RNA Seq", "GSM8287440 r1", "GSM8287440", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH135_S60_L002_R1_001.fastq.gz TH135_S60_L002_R2_001.fastq.gz", "fastq fastq", 5081243356.0, 42699524.0, "GSM8287440 r10", "0:28 1:91", "A:1453763884;C:1095418883;G:1154387721;T:1377550690;N:122178", 28, 91, null, null, 1453763884, 1095418883, 1154387721, 1377550690, 122178, "SRX24663082", "SRS21398380", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32220, "SRR29141358", "SRX24663082", "SRS21398380", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 6 12h mtz", "GSM8287440", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 6 12h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287440", "GSM8287440: Ablated rgc:ntr day 6 12h mtz; Danio rerio; RNA Seq", "GSM8287440 r1", "GSM8287440", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH135_S60_L004_R1_001.fastq.gz TH135_S60_L004_R2_001.fastq.gz", "fastq fastq", 5258119482.0, 44185878.0, "GSM8287440 r11", "0:28 1:91", "A:1501504527;C:1135881534;G:1197368112;T:1423254847;N:110462", 28, 91, null, null, 1501504527, 1135881534, 1197368112, 1423254847, 110462, "SRX24663082", "SRS21398380", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32221, "SRR29141359", "SRX24663082", "SRS21398380", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 6 12h mtz", "GSM8287440", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 6 12h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287440", "GSM8287440: Ablated rgc:ntr day 6 12h mtz; Danio rerio; RNA Seq", "GSM8287440 r1", "GSM8287440", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH135_S57_L003_R1_001.fastq.gz TH135_S57_L003_R2_001.fastq.gz", "fastq fastq", 5008964184.0, 42092136.0, "GSM8287440 r12", "0:28 1:91", "A:1428212274;C:1083563490;G:1142704874;T:1354362571;N:120975", 28, 91, null, null, 1428212274, 1083563490, 1142704874, 1354362571, 120975, "SRX24663082", "SRS21398380", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32222, "SRR29141360", "SRX24663082", "SRS21398380", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 6 12h mtz", "GSM8287440", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 6 12h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287440", "GSM8287440: Ablated rgc:ntr day 6 12h mtz; Danio rerio; RNA Seq", "GSM8287440 r1", "GSM8287440", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH135_S58_L002_R1_001.fastq.gz TH135_S58_L002_R2_001.fastq.gz", "fastq fastq", 5035503207.0, 42315153.0, "GSM8287440 r13", "0:28 1:91", "A:1440077950;C:1086334843;G:1144377517;T:1364592460;N:120437", 28, 91, null, null, 1440077950, 1086334843, 1144377517, 1364592460, 120437, "SRX24663082", "SRS21398380", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32223, "SRR29141361", "SRX24663082", "SRS21398380", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 6 12h mtz", "GSM8287440", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 6 12h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287440", "GSM8287440: Ablated rgc:ntr day 6 12h mtz; Danio rerio; RNA Seq", "GSM8287440 r1", "GSM8287440", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH135_S59_L001_R1_001.fastq.gz TH135_S59_L001_R2_001.fastq.gz", "fastq fastq", 5387099536.0, 45269744.0, "GSM8287440 r14", "0:28 1:91", "A:1537849058;C:1163912984;G:1227124886;T:1458073621;N:138987", 28, 91, null, null, 1537849058, 1163912984, 1227124886, 1458073621, 138987, "SRX24663082", "SRS21398380", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32224, "SRR29141362", "SRX24663082", "SRS21398380", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 6 12h mtz", "GSM8287440", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 6 12h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287440", "GSM8287440: Ablated rgc:ntr day 6 12h mtz; Danio rerio; RNA Seq", "GSM8287440 r1", "GSM8287440", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH135_S59_L004_R1_001.fastq.gz TH135_S59_L004_R2_001.fastq.gz", "fastq fastq", 5512521490.0, 46323710.0, "GSM8287440 r15", "0:28 1:91", "A:1571984524;C:1192238932;G:1256792838;T:1491389888;N:115308", 28, 91, null, null, 1571984524, 1192238932, 1256792838, 1491389888, 115308, "SRX24663082", "SRS21398380", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32225, "SRR29141363", "SRX24663082", "SRS21398380", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 6 12h mtz", "GSM8287440", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 6 12h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287440", "GSM8287440: Ablated rgc:ntr day 6 12h mtz; Danio rerio; RNA Seq", "GSM8287440 r1", "GSM8287440", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH135_S60_L003_R1_001.fastq.gz TH135_S60_L003_R2_001.fastq.gz", "fastq fastq", 5376169386.0, 45177894.0, "GSM8287440 r16", "0:28 1:91", "A:1533658425;C:1162739111;G:1225658907;T:1453983443;N:129500", 28, 91, null, null, 1533658425, 1162739111, 1225658907, 1453983443, 129500, "SRX24663082", "SRS21398380", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32226, "SRR29141364", "SRX24663082", "SRS21398380", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 6 12h mtz", "GSM8287440", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 6 12h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287440", "GSM8287440: Ablated rgc:ntr day 6 12h mtz; Danio rerio; RNA Seq", "GSM8287440 r1", "GSM8287440", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH135_S57_L002_R1_001.fastq.gz TH135_S57_L002_R2_001.fastq.gz", "fastq fastq", 4787380115.0, 40230085.0, "GSM8287440 r2", "0:28 1:91", "A:1368967190;C:1032261634;G:1088378612;T:1297658513;N:114166", 28, 91, null, null, 1368967190, 1032261634, 1088378612, 1297658513, 114166, "SRX24663082", "SRS21398380", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32227, "SRR29141365", "SRX24663082", "SRS21398380", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 6 12h mtz", "GSM8287440", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 6 12h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287440", "GSM8287440: Ablated rgc:ntr day 6 12h mtz; Danio rerio; RNA Seq", "GSM8287440 r1", "GSM8287440", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH135_S57_L004_R1_001.fastq.gz TH135_S57_L004_R2_001.fastq.gz", "fastq fastq", 4885123145.0, 41051455.0, "GSM8287440 r3", "0:28 1:91", "A:1394450278;C:1055564129;G:1113114189;T:1321891090;N:103459", 28, 91, null, null, 1394450278, 1055564129, 1113114189, 1321891090, 103459, "SRX24663082", "SRS21398380", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32228, "SRR29141366", "SRX24663082", "SRS21398380", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 6 12h mtz", "GSM8287440", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 6 12h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287440", "GSM8287440: Ablated rgc:ntr day 6 12h mtz; Danio rerio; RNA Seq", "GSM8287440 r1", "GSM8287440", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH135_S58_L001_R1_001.fastq.gz TH135_S58_L001_R2_001.fastq.gz", "fastq fastq", 5060757982.0, 42527378.0, "GSM8287440 r4", "0:28 1:91", "A:1446313544;C:1092878434;G:1151738503;T:1369695242;N:132259", 28, 91, null, null, 1446313544, 1092878434, 1151738503, 1369695242, 132259, "SRX24663082", "SRS21398380", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32229, "SRR29141367", "SRX24663082", "SRS21398380", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 6 12h mtz", "GSM8287440", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 6 12h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287440", "GSM8287440: Ablated rgc:ntr day 6 12h mtz; Danio rerio; RNA Seq", "GSM8287440 r1", "GSM8287440", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH135_S58_L003_R1_001.fastq.gz TH135_S58_L003_R2_001.fastq.gz", "fastq fastq", 5322898560.0, 44730240.0, "GSM8287440 r5", "0:28 1:91", "A:1517934750;C:1151967941;G:1213786668;T:1439081677;N:127524", 28, 91, null, null, 1517934750, 1151967941, 1213786668, 1439081677, 127524, "SRX24663082", "SRS21398380", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32230, "SRR29141368", "SRX24663082", "SRS21398380", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 6 12h mtz", "GSM8287440", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 6 12h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287440", "GSM8287440: Ablated rgc:ntr day 6 12h mtz; Danio rerio; RNA Seq", "GSM8287440 r1", "GSM8287440", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH135_S58_L004_R1_001.fastq.gz TH135_S58_L004_R2_001.fastq.gz", "fastq fastq", 5160850786.0, 43368494.0, "GSM8287440 r6", "0:28 1:91", "A:1473328102;C:1115516878;G:1175502159;T:1396395641;N:108006", 28, 91, null, null, 1473328102, 1115516878, 1175502159, 1396395641, 108006, "SRX24663082", "SRS21398380", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32231, "SRR29141369", "SRX24663082", "SRS21398380", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 6 12h mtz", "GSM8287440", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 6 12h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287440", "GSM8287440: Ablated rgc:ntr day 6 12h mtz; Danio rerio; RNA Seq", "GSM8287440 r1", "GSM8287440", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH135_S59_L002_R1_001.fastq.gz TH135_S59_L002_R2_001.fastq.gz", "fastq fastq", 5381504513.0, 45222727.0, "GSM8287440 r7", "0:28 1:91", "A:1537238062;C:1161721381;G:1224135102;T:1458280892;N:129076", 28, 91, null, null, 1537238062, 1161721381, 1224135102, 1458280892, 129076, "SRX24663082", "SRS21398380", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32232, "SRR29141370", "SRX24663082", "SRS21398380", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 6 12h mtz", "GSM8287440", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 6 12h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287440", "GSM8287440: Ablated rgc:ntr day 6 12h mtz; Danio rerio; RNA Seq", "GSM8287440 r1", "GSM8287440", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH135_S59_L003_R1_001.fastq.gz TH135_S59_L003_R2_001.fastq.gz", "fastq fastq", 5665367827.0, 47608133.0, "GSM8287440 r8", "0:28 1:91", "A:1613897652;C:1226812698;G:1293000098;T:1531521187;N:136192", 28, 91, null, null, 1613897652, 1226812698, 1293000098, 1531521187, 136192, "SRX24663082", "SRS21398380", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32233, "SRR29141371", "SRX24663082", "SRS21398380", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Ablated rgc:ntr day 6 12h mtz", "GSM8287440", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz|geo loc name:missing|collection date:missing", "Ablated rgc:ntr day 6 12h mtz", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz", "GSM8287440", "GSM8287440: Ablated rgc:ntr day 6 12h mtz; Danio rerio; RNA Seq", "GSM8287440 r1", "GSM8287440", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH135_S60_L001_R1_001.fastq.gz TH135_S60_L001_R2_001.fastq.gz", "fastq fastq", 5045550377.0, 42399583.0, "GSM8287440 r9", "0:28 1:91", "A:1442885146;C:1088672739;G:1147630180;T:1366230521;N:131791", 28, 91, null, null, 1442885146, 1088672739, 1147630180, 1366230521, 131791, "SRX24663082", "SRS21398380", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32234, "SRR29141372", "SRX24663081", "SRS21398379", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 9", "GSM8287439", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 9", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287439", "GSM8287439: Unablated rgc:ntr day 9; Danio rerio; RNA Seq", "GSM8287439 r1", "GSM8287439", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH134_S53_L001_R1_001.fastq.gz TH134_S53_L001_R2_001.fastq.gz", "fastq fastq", 4566870378.0, 38377062.0, "GSM8287439 r1", "0:28 1:91", "A:1300193484;C:990777876;G:1047244494;T:1228536400;N:118124", 28, 91, null, null, 1300193484, 990777876, 1047244494, 1228536400, 118124, "SRX24663081", "SRS21398379", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32235, "SRR29141373", "SRX24663081", "SRS21398379", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 9", "GSM8287439", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 9", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287439", "GSM8287439: Unablated rgc:ntr day 9; Danio rerio; RNA Seq", "GSM8287439 r1", "GSM8287439", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH134_S55_L002_R1_001.fastq.gz TH134_S55_L002_R2_001.fastq.gz", "fastq fastq", 4872575309.0, 40946011.0, "GSM8287439 r10", "0:28 1:91", "A:1388373514;C:1056698672;G:1113330484;T:1314056163;N:116476", 28, 91, null, null, 1388373514, 1056698672, 1113330484, 1314056163, 116476, "SRX24663081", "SRS21398379", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32236, "SRR29141374", "SRX24663081", "SRS21398379", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 9", "GSM8287439", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 9", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287439", "GSM8287439: Unablated rgc:ntr day 9; Danio rerio; RNA Seq", "GSM8287439 r1", "GSM8287439", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH134_S55_L003_R1_001.fastq.gz TH134_S55_L003_R2_001.fastq.gz", "fastq fastq", 5138052528.0, 43176912.0, "GSM8287439 r11", "0:28 1:91", "A:1459926271;C:1117597394;G:1177808023;T:1382597761;N:123079", 28, 91, null, null, 1459926271, 1117597394, 1177808023, 1382597761, 123079, "SRX24663081", "SRS21398379", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32237, "SRR29141375", "SRX24663081", "SRS21398379", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 9", "GSM8287439", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 9", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287439", "GSM8287439: Unablated rgc:ntr day 9; Danio rerio; RNA Seq", "GSM8287439 r1", "GSM8287439", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH134_S55_L004_R1_001.fastq.gz TH134_S55_L004_R2_001.fastq.gz", "fastq fastq", 5022868263.0, 42208977.0, "GSM8287439 r12", "0:28 1:91", "A:1428914798;C:1091192534;G:1150147876;T:1352508063;N:104992", 28, 91, null, null, 1428914798, 1091192534, 1150147876, 1352508063, 104992, "SRX24663081", "SRS21398379", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32238, "SRR29141376", "SRX24663081", "SRS21398379", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 9", "GSM8287439", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 9", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287439", "GSM8287439: Unablated rgc:ntr day 9; Danio rerio; RNA Seq", "GSM8287439 r1", "GSM8287439", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH134_S56_L001_R1_001.fastq.gz TH134_S56_L001_R2_001.fastq.gz", "fastq fastq", 4569776953.0, 38401487.0, "GSM8287439 r13", "0:28 1:91", "A:1299842950;C:992232187;G:1048131188;T:1229452715;N:117913", 28, 91, null, null, 1299842950, 992232187, 1048131188, 1229452715, 117913, "SRX24663081", "SRS21398379", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32239, "SRR29141377", "SRX24663081", "SRS21398379", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 9", "GSM8287439", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 9", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287439", "GSM8287439: Unablated rgc:ntr day 9; Danio rerio; RNA Seq", "GSM8287439 r1", "GSM8287439", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH134_S56_L002_R1_001.fastq.gz TH134_S56_L002_R2_001.fastq.gz", "fastq fastq", 4604427135.0, 38692665.0, "GSM8287439 r14", "0:28 1:91", "A:1310481305;C:998823194;G:1054488359;T:1240523819;N:110458", 28, 91, null, null, 1310481305, 998823194, 1054488359, 1240523819, 110458, "SRX24663081", "SRS21398379", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32240, "SRR29141378", "SRX24663081", "SRS21398379", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 9", "GSM8287439", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 9", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287439", "GSM8287439: Unablated rgc:ntr day 9; Danio rerio; RNA Seq", "GSM8287439 r1", "GSM8287439", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH134_S56_L003_R1_001.fastq.gz TH134_S56_L003_R2_001.fastq.gz", "fastq fastq", 4894210580.0, 41127820.0, "GSM8287439 r15", "0:28 1:91", "A:1389263901;C:1064650503;G:1124176385;T:1316003245;N:116546", 28, 91, null, null, 1389263901, 1064650503, 1124176385, 1316003245, 116546, "SRX24663081", "SRS21398379", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32241, "SRR29141379", "SRX24663081", "SRS21398379", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 9", "GSM8287439", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 9", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287439", "GSM8287439: Unablated rgc:ntr day 9; Danio rerio; RNA Seq", "GSM8287439 r1", "GSM8287439", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH134_S56_L004_R1_001.fastq.gz TH134_S56_L004_R2_001.fastq.gz", "fastq fastq", 4782327494.0, 40187626.0, "GSM8287439 r16", "0:28 1:91", "A:1359054303;C:1039048484;G:1097178265;T:1286945985;N:100457", 28, 91, null, null, 1359054303, 1039048484, 1097178265, 1286945985, 100457, "SRX24663081", "SRS21398379", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32242, "SRR29141380", "SRX24663081", "SRS21398379", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 9", "GSM8287439", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 9", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287439", "GSM8287439: Unablated rgc:ntr day 9; Danio rerio; RNA Seq", "GSM8287439 r1", "GSM8287439", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH134_S53_L002_R1_001.fastq.gz TH134_S53_L002_R2_001.fastq.gz", "fastq fastq", 4587896012.0, 38553748.0, "GSM8287439 r2", "0:28 1:91", "A:1307093057;C:994483546;G:1050434019;T:1235776211;N:109179", 28, 91, null, null, 1307093057, 994483546, 1050434019, 1235776211, 109179, "SRX24663081", "SRS21398379", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32243, "SRR29141381", "SRX24663081", "SRS21398379", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 9", "GSM8287439", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 9", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287439", "GSM8287439: Unablated rgc:ntr day 9; Danio rerio; RNA Seq", "GSM8287439 r1", "GSM8287439", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH134_S53_L003_R1_001.fastq.gz TH134_S53_L003_R2_001.fastq.gz", "fastq fastq", 4853618728.0, 40786712.0, "GSM8287439 r3", "0:28 1:91", "A:1378590543;C:1055361040;G:1114790969;T:1304760000;N:116176", 28, 91, null, null, 1378590543, 1055361040, 1114790969, 1304760000, 116176, "SRX24663081", "SRS21398379", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32244, "SRR29141382", "SRX24663081", "SRS21398379", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 9", "GSM8287439", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 9", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287439", "GSM8287439: Unablated rgc:ntr day 9; Danio rerio; RNA Seq", "GSM8287439 r1", "GSM8287439", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH134_S53_L004_R1_001.fastq.gz TH134_S53_L004_R2_001.fastq.gz", "fastq fastq", 4736870803.0, 39805637.0, "GSM8287439 r4", "0:28 1:91", "A:1346988869;C:1028744736;G:1086568704;T:1274469646;N:98848", 28, 91, null, null, 1346988869, 1028744736, 1086568704, 1274469646, 98848, "SRX24663081", "SRS21398379", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32245, "SRR29141383", "SRX24663081", "SRS21398379", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 9", "GSM8287439", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 9", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287439", "GSM8287439: Unablated rgc:ntr day 9; Danio rerio; RNA Seq", "GSM8287439 r1", "GSM8287439", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH134_S54_L001_R1_001.fastq.gz TH134_S54_L001_R2_001.fastq.gz", "fastq fastq", 5319795040.0, 44704160.0, "GSM8287439 r5", "0:28 1:91", "A:1516665110;C:1153199308;G:1216078023;T:1433713315;N:139284", 28, 91, null, null, 1516665110, 1153199308, 1216078023, 1433713315, 139284, "SRX24663081", "SRS21398379", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32246, "SRR29141384", "SRX24663081", "SRS21398379", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 9", "GSM8287439", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 9", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287439", "GSM8287439: Unablated rgc:ntr day 9; Danio rerio; RNA Seq", "GSM8287439 r1", "GSM8287439", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH134_S54_L002_R1_001.fastq.gz TH134_S54_L002_R2_001.fastq.gz", "fastq fastq", 5330566682.0, 44794678.0, "GSM8287439 r6", "0:28 1:91", "A:1520480633;C:1154635844;G:1217037822;T:1438283496;N:128887", 28, 91, null, null, 1520480633, 1154635844, 1217037822, 1438283496, 128887, "SRX24663081", "SRS21398379", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32247, "SRR29141385", "SRX24663081", "SRS21398379", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 9", "GSM8287439", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 9", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287439", "GSM8287439: Unablated rgc:ntr day 9; Danio rerio; RNA Seq", "GSM8287439 r1", "GSM8287439", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH134_S54_L003_R1_001.fastq.gz TH134_S54_L003_R2_001.fastq.gz", "fastq fastq", 5561785705.0, 46737695.0, "GSM8287439 r7", "0:28 1:91", "A:1581477655;C:1208929874;G:1274395111;T:1496847765;N:135300", 28, 91, null, null, 1581477655, 1208929874, 1274395111, 1496847765, 135300, "SRX24663081", "SRS21398379", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32248, "SRR29141386", "SRX24663081", "SRS21398379", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 9", "GSM8287439", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 9", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287439", "GSM8287439: Unablated rgc:ntr day 9; Danio rerio; RNA Seq", "GSM8287439 r1", "GSM8287439", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH134_S54_L004_R1_001.fastq.gz TH134_S54_L004_R2_001.fastq.gz", "fastq fastq", 5423072403.0, 45572037.0, "GSM8287439 r8", "0:28 1:91", "A:1543580201;C:1177607853;G:1241277315;T:1460492382;N:114652", 28, 91, null, null, 1543580201, 1177607853, 1241277315, 1460492382, 114652, "SRX24663081", "SRS21398379", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32249, "SRR29141387", "SRX24663081", "SRS21398379", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 9", "GSM8287439", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 9", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287439", "GSM8287439: Unablated rgc:ntr day 9; Danio rerio; RNA Seq", "GSM8287439 r1", "GSM8287439", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH134_S55_L001_R1_001.fastq.gz TH134_S55_L001_R2_001.fastq.gz", "fastq fastq", 4848214105.0, 40741295.0, "GSM8287439 r9", "0:28 1:91", "A:1380197121;C:1052472596;G:1109522284;T:1305896718;N:125386", 28, 91, null, null, 1380197121, 1052472596, 1109522284, 1305896718, 125386, "SRX24663081", "SRS21398379", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32250, "SRR29141388", "SRX24663080", "SRS21398378", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 6", "GSM8287438", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 6", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287438", "GSM8287438: Unablated rgc:ntr day 6; Danio rerio; RNA Seq", "GSM8287438 r1", "GSM8287438", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH133_S49_L001_R1_001.fastq.gz TH133_S49_L001_R2_001.fastq.gz", "fastq fastq", 4633962102.0, 38940858.0, "GSM8287438 r1", "0:28 1:91", "A:1297725412;C:1024809339;G:1076904995;T:1234401645;N:120711", 28, 91, null, null, 1297725412, 1024809339, 1076904995, 1234401645, 120711, "SRX24663080", "SRS21398378", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32251, "SRR29141389", "SRX24663080", "SRS21398378", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 6", "GSM8287438", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 6", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287438", "GSM8287438: Unablated rgc:ntr day 6; Danio rerio; RNA Seq", "GSM8287438 r1", "GSM8287438", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH133_S52_L003_R1_001.fastq.gz TH133_S52_L003_R2_001.fastq.gz", "fastq fastq", 4989425217.0, 41927943.0, "GSM8287438 r10", "0:28 1:91", "A:1391245093;C:1106917719;G:1165216341;T:1325928222;N:117842", 28, 91, null, null, 1391245093, 1106917719, 1165216341, 1325928222, 117842, "SRX24663080", "SRS21398378", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32252, "SRR29141390", "SRX24663080", "SRS21398378", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 6", "GSM8287438", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 6", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287438", "GSM8287438: Unablated rgc:ntr day 6; Danio rerio; RNA Seq", "GSM8287438 r1", "GSM8287438", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH133_S52_L004_R1_001.fastq.gz TH133_S52_L004_R2_001.fastq.gz", "fastq fastq", 4854872155.0, 40797245.0, "GSM8287438 r11", "0:28 1:91", "A:1355524409;C:1075673845;G:1132295861;T:1291276543;N:101497", 28, 91, null, null, 1355524409, 1075673845, 1132295861, 1291276543, 101497, "SRX24663080", "SRS21398378", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32253, "SRR29141391", "SRX24663080", "SRS21398378", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 6", "GSM8287438", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 6", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287438", "GSM8287438: Unablated rgc:ntr day 6; Danio rerio; RNA Seq", "GSM8287438 r1", "GSM8287438", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH133_S49_L002_R1_001.fastq.gz TH133_S49_L002_R2_001.fastq.gz", "fastq fastq", 4657232314.0, 39136406.0, "GSM8287438 r12", "0:28 1:91", "A:1305512663;C:1028718382;G:1080733287;T:1242157091;N:110891", 28, 91, null, null, 1305512663, 1028718382, 1080733287, 1242157091, 110891, "SRX24663080", "SRS21398378", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32254, "SRR29141392", "SRX24663080", "SRS21398378", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 6", "GSM8287438", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 6", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287438", "GSM8287438: Unablated rgc:ntr day 6; Danio rerio; RNA Seq", "GSM8287438 r1", "GSM8287438", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH133_S50_L001_R1_001.fastq.gz TH133_S50_L001_R2_001.fastq.gz", "fastq fastq", 4932588794.0, 41450326.0, "GSM8287438 r13", "0:28 1:91", "A:1379015030;C:1091338503;G:1149356127;T:1312752653;N:126481", 28, 91, null, null, 1379015030, 1091338503, 1149356127, 1312752653, 126481, "SRX24663080", "SRS21398378", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32255, "SRR29141393", "SRX24663080", "SRS21398378", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 6", "GSM8287438", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 6", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287438", "GSM8287438: Unablated rgc:ntr day 6; Danio rerio; RNA Seq", "GSM8287438 r1", "GSM8287438", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH133_S50_L004_R1_001.fastq.gz TH133_S50_L004_R2_001.fastq.gz", "fastq fastq", 5077097277.0, 42664683.0, "GSM8287438 r14", "0:28 1:91", "A:1418123656;C:1124378298;G:1183528228;T:1350962964;N:104131", 28, 91, null, null, 1418123656, 1124378298, 1183528228, 1350962964, 104131, "SRX24663080", "SRS21398378", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32256, "SRR29141394", "SRX24663080", "SRS21398378", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 6", "GSM8287438", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 6", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287438", "GSM8287438: Unablated rgc:ntr day 6; Danio rerio; RNA Seq", "GSM8287438 r1", "GSM8287438", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH133_S51_L003_R1_001.fastq.gz TH133_S51_L003_R2_001.fastq.gz", "fastq fastq", 4923689498.0, 41375542.0, "GSM8287438 r15", "0:28 1:91", "A:1375204406;C:1090796811;G:1149080188;T:1308491701;N:116392", 28, 91, null, null, 1375204406, 1090796811, 1149080188, 1308491701, 116392, "SRX24663080", "SRS21398378", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32257, "SRR29141395", "SRX24663080", "SRS21398378", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 6", "GSM8287438", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 6", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287438", "GSM8287438: Unablated rgc:ntr day 6; Danio rerio; RNA Seq", "GSM8287438 r1", "GSM8287438", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH133_S52_L002_R1_001.fastq.gz TH133_S52_L002_R2_001.fastq.gz", "fastq fastq", 4696383909.0, 39465411.0, "GSM8287438 r16", "0:28 1:91", "A:1313674940;C:1038514326;G:1093116030;T:1250967700;N:110913", 28, 91, null, null, 1313674940, 1038514326, 1093116030, 1250967700, 110913, "SRX24663080", "SRS21398378", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32258, "SRR29141396", "SRX24663080", "SRS21398378", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 6", "GSM8287438", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 6", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287438", "GSM8287438: Unablated rgc:ntr day 6; Danio rerio; RNA Seq", "GSM8287438 r1", "GSM8287438", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH133_S49_L003_R1_001.fastq.gz TH133_S49_L003_R2_001.fastq.gz", "fastq fastq", 4935093863.0, 41471377.0, "GSM8287438 r2", "0:28 1:91", "A:1378860058;C:1094061046;G:1149630737;T:1312423104;N:118918", 28, 91, null, null, 1378860058, 1094061046, 1149630737, 1312423104, 118918, "SRX24663080", "SRS21398378", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32259, "SRR29141397", "SRX24663080", "SRS21398378", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 6", "GSM8287438", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 6", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287438", "GSM8287438: Unablated rgc:ntr day 6; Danio rerio; RNA Seq", "GSM8287438 r1", "GSM8287438", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH133_S49_L004_R1_001.fastq.gz TH133_S49_L004_R2_001.fastq.gz", "fastq fastq", 4820025147.0, 40504413.0, "GSM8287438 r3", "0:28 1:91", "A:1348394661;C:1067282812;G:1121376379;T:1282869478;N:101817", 28, 91, null, null, 1348394661, 1067282812, 1121376379, 1282869478, 101817, "SRX24663080", "SRS21398378", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32260, "SRR29141398", "SRX24663080", "SRS21398378", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 6", "GSM8287438", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 6", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287438", "GSM8287438: Unablated rgc:ntr day 6; Danio rerio; RNA Seq", "GSM8287438 r1", "GSM8287438", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH133_S50_L002_R1_001.fastq.gz TH133_S50_L002_R2_001.fastq.gz", "fastq fastq", 4931460079.0, 41440841.0, "GSM8287438 r4", "0:28 1:91", "A:1379937889;C:1089994166;G:1147241148;T:1314171218;N:115658", 28, 91, null, null, 1379937889, 1089994166, 1147241148, 1314171218, 115658, "SRX24663080", "SRS21398378", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32261, "SRR29141399", "SRX24663080", "SRS21398378", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 6", "GSM8287438", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 6", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287438", "GSM8287438: Unablated rgc:ntr day 6; Danio rerio; RNA Seq", "GSM8287438 r1", "GSM8287438", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH133_S50_L003_R1_001.fastq.gz TH133_S50_L003_R2_001.fastq.gz", "fastq fastq", 5229270193.0, 43943447.0, "GSM8287438 r5", "0:28 1:91", "A:1458651163;C:1159571989;G:1220750194;T:1390173862;N:122985", 28, 91, null, null, 1458651163, 1159571989, 1220750194, 1390173862, 122985, "SRX24663080", "SRS21398378", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32262, "SRR29141400", "SRX24663080", "SRS21398378", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 6", "GSM8287438", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 6", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287438", "GSM8287438: Unablated rgc:ntr day 6; Danio rerio; RNA Seq", "GSM8287438 r1", "GSM8287438", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH133_S51_L001_R1_001.fastq.gz TH133_S51_L001_R2_001.fastq.gz", "fastq fastq", 4636122190.0, 38959010.0, "GSM8287438 r6", "0:28 1:91", "A:1298955001;C:1023834288;G:1079293988;T:1233918757;N:120156", 28, 91, null, null, 1298955001, 1023834288, 1079293988, 1233918757, 120156, "SRX24663080", "SRS21398378", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32263, "SRR29141401", "SRX24663080", "SRS21398378", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 6", "GSM8287438", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 6", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287438", "GSM8287438: Unablated rgc:ntr day 6; Danio rerio; RNA Seq", "GSM8287438 r1", "GSM8287438", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH133_S51_L002_R1_001.fastq.gz TH133_S51_L002_R2_001.fastq.gz", "fastq fastq", 4651974894.0, 39092226.0, "GSM8287438 r7", "0:28 1:91", "A:1304274716;C:1026606682;G:1081394365;T:1239588507;N:110624", 28, 91, null, null, 1304274716, 1026606682, 1081394365, 1239588507, 110624, "SRX24663080", "SRS21398378", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32264, "SRR29141402", "SRX24663080", "SRS21398378", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 6", "GSM8287438", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 6", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287438", "GSM8287438: Unablated rgc:ntr day 6; Danio rerio; RNA Seq", "GSM8287438 r1", "GSM8287438", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH133_S51_L004_R1_001.fastq.gz TH133_S51_L004_R2_001.fastq.gz", "fastq fastq", 4797101463.0, 40311777.0, "GSM8287438 r8", "0:28 1:91", "A:1341600660;C:1061361282;G:1117958236;T:1276080791;N:100494", 28, 91, null, null, 1341600660, 1061361282, 1117958236, 1276080791, 100494, "SRX24663080", "SRS21398378", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32265, "SRR29141403", "SRX24663080", "SRS21398378", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 6", "GSM8287438", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 6", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287438", "GSM8287438: Unablated rgc:ntr day 6; Danio rerio; RNA Seq", "GSM8287438 r1", "GSM8287438", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH133_S52_L001_R1_001.fastq.gz TH133_S52_L001_R2_001.fastq.gz", "fastq fastq", 4697283787.0, 39472973.0, "GSM8287438 r9", "0:28 1:91", "A:1312647560;C:1039809509;G:1095056786;T:1249648802;N:121130", 28, 91, null, null, 1312647560, 1039809509, 1095056786, 1249648802, 121130, "SRX24663080", "SRS21398378", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32266, "SRR29141404", "SRX24663079", "SRS21398377", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 7", "GSM8287436", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 7", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287436", "GSM8287436: Unablated rgc:ntr day 7; Danio rerio; RNA Seq", "GSM8287436 r1", "GSM8287436", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH110_S62_R1_001.fastq.gz TH110_S62_R2_001.fastq.gz", "fastq fastq", 7832538588.0, 65819652.0, "GSM8287436 r1", "0:28 1:91", "A:2264636103;C:1687265841;G:1826367106;T:2032749605;N:21519933", 28, 91, null, null, 2264636103, 1687265841, 1826367106, 2032749605, 21519933, "SRX24663079", "SRS21398377", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32267, "SRR29141405", "SRX24663079", "SRS21398377", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 7", "GSM8287436", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 7", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287436", "GSM8287436: Unablated rgc:ntr day 7; Danio rerio; RNA Seq", "GSM8287436 r1", "GSM8287436", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH110_S63_R1_001.fastq.gz TH110_S63_R2_001.fastq.gz", "fastq fastq", 166170767.0, 1396393.0, "GSM8287436 r2", "0:28 1:91", "A:48248797;C:35717941;G:38752344;T:42997083;N:454602", 28, 91, null, null, 48248797, 35717941, 38752344, 42997083, 454602, "SRX24663079", "SRS21398377", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32268, "SRR29141406", "SRX24663079", "SRS21398377", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 7", "GSM8287436", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 7", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287436", "GSM8287436: Unablated rgc:ntr day 7; Danio rerio; RNA Seq", "GSM8287436 r1", "GSM8287436", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH110_S61_R1_001.fastq.gz TH110_S61_R2_001.fastq.gz", "fastq fastq", 8485930460.0, 71310340.0, "GSM8287436 r3", "0:28 1:91", "A:2462428503;C:1828880092;G:1970877358;T:2200821838;N:22922669", 28, 91, null, null, 2462428503, 1828880092, 1970877358, 2200821838, 22922669, "SRX24663079", "SRS21398377", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32269, "SRR29141407", "SRX24663079", "SRS21398377", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Unablated rgc:ntr day 7", "GSM8287436", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz|geo loc name:missing|collection date:missing", "Unablated rgc:ntr day 7", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:no mtz", "GSM8287436", "GSM8287436: Unablated rgc:ntr day 7; Danio rerio; RNA Seq", "GSM8287436 r1", "GSM8287436", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "TH110_S64_R1_001.fastq.gz TH110_S64_R2_001.fastq.gz", "fastq fastq", 16842320614.0, 141532106.0, "GSM8287436 r4", "0:28 1:91", "A:5877167251;C:2818424553;G:4717101041;T:3385003561;N:44624208", 28, 91, null, null, 5877167251, 2818424553, 4717101041, 3385003561, 44624208, "SRX24663079", "SRS21398377", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32270, "SRR29141408", "SRX24663078", "SRS21398376", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Multiome rgc:ntr 24h ablation ascl1a KO day 7 RNA", "GSM8287448", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz  ascl1a gRNAs|geo loc name:missing|collection date:missing", "Multiome rgc:ntr 24h ablation ascl1a KO day 7 RNA", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz  ascl1a gRNAs", "GSM8287448", "GSM8287448: Multiome rgc:ntr 24h ablation ascl1a KO day 7 RNA; Danio rerio; RNA Seq", "GSM8287448 r1", "GSM8287448", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "JM-M-R_S5_L001_R1_001.fastq.gz JM-M-R_S5_L001_R2_001.fastq.gz", "fastq fastq", 16128997724.0, 135537796.0, "GSM8287448 r1", "0:28 1:91", "A:4730995900;C:3379548236;G:3457738129;T:4560498122;N:217337", 28, 91, null, null, 4730995900, 3379548236, 3457738129, 4560498122, 217337, "SRX24663078", "SRS21398376", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32271, "SRR29141409", "SRX24663078", "SRS21398376", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Multiome rgc:ntr 24h ablation ascl1a KO day 7 RNA", "GSM8287448", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz  ascl1a gRNAs|geo loc name:missing|collection date:missing", "Multiome rgc:ntr 24h ablation ascl1a KO day 7 RNA", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz  ascl1a gRNAs", "GSM8287448", "GSM8287448: Multiome rgc:ntr 24h ablation ascl1a KO day 7 RNA; Danio rerio; RNA Seq", "GSM8287448 r1", "GSM8287448", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "JM-M-R_S5_L002_R1_001.fastq.gz JM-M-R_S5_L002_R2_001.fastq.gz", "fastq fastq", 16319960475.0, 137142525.0, "GSM8287448 r2", "0:28 1:91", "A:4785034443;C:3421478325;G:3500876324;T:4612346844;N:224539", 28, 91, null, null, 4785034443, 3421478325, 3500876324, 4612346844, 224539, "SRX24663078", "SRS21398376", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"], [32272, "SRR29141410", "SRX24663078", "SRS21398376", "SRP509393", "PRJNA1115053", "Large scale screen of novel zebrafish retinal ganglion cell ablation model reveals genetic regulation of retinal regeneration is context specific", "GSE268179", "Other", "Many genes are known to regulate M\u00fcller glia MG dependent retinal regeneration following widespread tissue damage. Conversely  genes controlling regeneration following limited retinal cell loss  per degenerative disease  are undefined. Studying regeneration in the context of selective cell loss is important as evidence suggests injury specifics inform the regenerative process. Here  transgenic zebrafish enabling inducible selective retinal ganglion cell RGC ablation were combined with single cell multiomics and CRISPR/Cas9 based knockout methods to screen 101 genes for effects on RGC regeneration. We identified 18 regulators of RGC regeneration  seven knockouts inhibited and eleven promoted RGC regeneration. Surprisingly  35 of 36 known/implicated regulators of retinal tissue regeneration following widespread damage were not required for RGC regeneration  and seven of these knockouts actually enhanced RGC replacement kinetics  including sox2  olig2  and ascl1a. Mechanistic analyses revealed ascl1a knockout increased the propensity of progenitor cells to produce RGCs; i.e.  biased progenitor cell fate. These data demonstrate plasticity in how MG can convert to a stem like state and context specificity in how genes function during regeneration. Increased understanding of how disease relevant cell types can be selectively regenerated will  support the development of disease tailored regenerative therapeutics. Overall design: We performed single cell RNA sequencing in larval zebrafish eyes following multiple paradigms of retinal damage including ablation of retinal ganglion cells RGCs  4 timepoints and ablation of rod photoreceptors  and multiome sequencing following ablation of RGCs in fish with the ascl1a gene knocked out via CRISPR/Cas9.", null, "pubmed:39007397", null, "Multiome rgc:ntr 24h ablation ascl1a KO day 7 RNA", "GSM8287448", null, "source name:Eye|tissue:Eye|transgenic line:rgc:ntr|treatment:mtz  ascl1a gRNAs|geo loc name:missing|collection date:missing", "Multiome rgc:ntr 24h ablation ascl1a KO day 7 RNA", "scRNAseq: Raw reads were mapped to the Danio rerio GRCz10 using Cell Ranger v7.0 from 10x genomics. Aligned genomic reads were then read into the published Seurat pipeline v4.3.0.1 and quality control was performed by removing any cells with <200 detected genes or 1000 UMIs  and genes detected in fewer than 3 cells per experiment. Clustering steps were performed using steps from the pbmc Seurat tutorial available online. Briefly  the top 2 000 variable genes were identified and used to identify principal components PCs of the data. The top 30 PCs were used to produce a UMAP and clusters were annotated with known zebrafish marker genes. Differentially expressed genes DEGs were identified using the FindAllMarkers function between each control and ablation timepoint in each retinal cell cluster minimum log2 foldchange cutoff of 0.25. scMultiomeseq: RNA expression data was processed as above. Peak calling from single nuclei ATAC seq reads was performed using MACS2 in the ArchR package v1.0.2. ATAC seq data was then processed using the pbmc scATAC seq workflow with the Signac v1.10.0 and Seurat v4.3.0.1 packages for quality control  normalization and producing an integrated UMAP. Differential expression and accessibility was then calculated for both gene RNA expression and chromatin peak accessibility. Next  the ChromVar package v1.18.0 was used to identify differentially accessible transcription factor motifs between wildtype and ascl1a mutant cells. Assembly: GRCz11 Supplementary files format and content: Cellular expression data varies in format either as h5 standalone files or barcodes  features and matrix files to be used together. ATAC data is available as standalone fragment.tsv files", "Eye", null, "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "tissue:Eye|transgenic line:rgc:ntr|treatment:mtz  ascl1a gRNAs", "GSM8287448", "GSM8287448: Multiome rgc:ntr 24h ablation ascl1a KO day 7 RNA; Danio rerio; RNA Seq", "GSM8287448 r1", "GSM8287448", "1", "scRNAseq: 40 60 eyes were dissected from sibling fish and subsequently placed in 20 U/ml papain 10 eyes per 1 ml Worthington  and incubated at 28\u00b0C for 30 min with gentle agitation. Cells were pelleted and resuspended in PBS containing 0.1 mg/ml leupeptin Sigma Aldrich and 10 U/ml DNaseI Roche. Cells were filtered through a 70 \u03bcm filter Miltenyi Biotec  kept on ice until 10X genomics processing. scMultiomeseq: 40 60 eyes were dissected and flash frozen in dry ice for 15min before being transferred to a  80 C freezer for storage. Nuclei were extracted from frozen retinal tissues according to 10xMultiome ATAC + Gene Expression GEX protocol CGOOO338. Briefly  frozen retinal tissues were lysed in ice cold 500ml of 0.1X Lysis buffer using a pestle and incubated on ice for 6 min totally. Nuclei were centrifuged  washed 3 times and resuspended in 10xMultiome nuclei buffer at a concentration of 3000 5000 nuclei/ml and kept on ice until 10x genomics processing. Library preparation was then performed according to 10x genomics protocols.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP509393", null, "loader:fastq load.py", "JM-M-R_S5_L003_R1_001.fastq.gz JM-M-R_S5_L003_R2_001.fastq.gz", "fastq fastq", 16272530526.0, 136743954.0, "GSM8287448 r3", "0:28 1:91", "A:4772770822;C:3409933317;G:3489014394;T:4600600715;N:211278", 28, 91, null, null, 4772770822, 3409933317, 3489014394, 4600600715, 211278, "SRX24663078", "SRS21398376", "SRA1875751", "Jeff Mumm, Ophthalmology, Johns Hopkins University", "Jeff Mumm, Ophthalmology, Johns Hopkins University", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-05-23", "Undetermined", "Larval", "Eye", "Sensory System"]], "truncated": false, "filtered_table_rows_count": 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[experiment.platform], [experiment.instrument_model], [experiment.spot_descriptor], [experiment.study_ref], [run.title], [run.attributes], [run.filename], [run.semantic_name], [run.total_bases], [run.total_spots], [run.alias], [run.read_lengths], [run.base_counts], [run.r1_length], [run.r2_length], [run.r3_length], [run.r4_length], [run.Acount], [run.Ccount], [run.Gcount], [run.Tcount], [run.Ncount], [run.experiment], [run.pool_member], [submission.accession], [submission.srasource], [submission.bioprojectsource], [seqdetective.n_mates], [seqdetective.mapping_rate.mate1], [seqdetective.mapping_rate.mate2], [seqdetective.nofeature_rate.mate1], [seqdetective.nofeature_rate.mate2], [seqdetective.sparsity.mate1], [seqdetective.sparsity.mate2], [seqdetective.pos_strand_rate.mate1], [seqdetective.pos_strand_rate.mate2], [seqdetective.readlen.mate1], [seqdetective.readlen.mate2], [seqdetective.judgement.mate1], [seqdetective.judgement.mate2], [seqdetective.judgement.reason], platform_family, 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"/metadata/run_metadata.json?technology=10x&tissue_curation_coarse=Sensory+System", "results": [{"value": "ILLUMINA", "label": "ILLUMINA", "count": 353, "toggle_url": "http://metadata.rnaquarium.org/metadata/run_metadata.json?technology=10x&tissue_curation_coarse=Sensory+System&experiment.platform=ILLUMINA", "selected": false}], "truncated": false}, "devstage_curation_coarse": {"name": "devstage_curation_coarse", "type": "column", "hideable": false, "toggle_url": "/metadata/run_metadata.json?technology=10x&tissue_curation_coarse=Sensory+System", "results": [{"value": "Larval", "label": "Larval", "count": 217, "toggle_url": "http://metadata.rnaquarium.org/metadata/run_metadata.json?technology=10x&tissue_curation_coarse=Sensory+System&devstage_curation_coarse=Larval", "selected": false}, {"value": "Adult", "label": "Adult", "count": 84, "toggle_url": 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