{"database": "metadata", "table": "run_metadata", "is_view": false, "human_description_en": "where devstage_curation_coarse = \"Adult\" and experiment.library_strategy = \"OTHER\"", "rows": [[28725, "SRR26623262", "SRX22323921", "SRS19374450", "SRP469552", "PRJNA1034159", "Dissecting the spatiotemporal diversity of adult neural stem cells", "GSE246714", "Other", "Adult stem cells are important for tissue turnover and regeneration. However  in most adult systems it remains elusive how stem cells assume different functional states and support spatially patterned tissue architecture. Here  we dissected the diversity of neural stem cells in the adult zebrafish brain  an organ that is characterized by pronounced zonation and high regenerative capacity. We combined single cell transcriptomics of dissected brain regions with massively parallel lineage tracing and in vivo RNA metabolic labeling to analyze regulation of neural stem cells in space and time. We detected a large diversity of neural stem cells  with some subtypes being restricted to a single brain region  while others were found globally across the brain. Global stem cell states are linked to neurogenic differentiation  with different states being involved in proliferative and non proliferative differentiation. Our work reveals principles of adult stem cell organization and establishes a resource for functional manipulation of neural stem cell subtypes. Overall design: Single cell RNA seq of adult zebrafish brain performed using 10x Genomics Gene Expression protocols to explore transcriptomic diversity of adult cell types. The samples were prepared either from whole brain  FACS sorted cells GFP positive cells from gfap:GFP line or a dissected single brain region  as indicated in the sample title. CRISPR based lineage tracing was performed for a subset of samples to dissect developmental lineage relationships between cells. ScSLAM seq was performed in combination with Notch pathway inhibition to assess response of stem cells to perturbation.", null, "pubmed:38365956", null, "Lineage tracing rep1  cirbpb scars", "GSM7875190", null, "source name:adult brain|tissue:adult brain|cell type:mixed tissue dissociation|genotype:Tg[ubi:zebrabow M]|geo loc name:missing|collection date:missing", "Lineage tracing rep1  cirbpb scars", "The transcriptome libraries were demultiplexed and mapped with CellRanger 6.1.1. In order to reduce batch effect  the gene expression matrices were processed with the SoupX tool Young & Behjati  2020 for removing ambient RNA contamination. A subset of libraries was also mapped with Velocyto v0.17.17 La Manno et al  2018 to create count matrices for unspliced and spliced molecules. The targeted lineage tracing libraries were aligned using bwa mem3 v.0.7.12 to individual references of endogenous genes used in the lineage tracing experiment actb1  actb2  cfl1  cirbpb  rpl39 and ube2e1. The scars were filtered with a custom pipeline to eliminate sequences that originate from PCR or sequencing errors. For custom code and further downstream analysis  see: https://github.com/nimitic/radial glia. Assembly: GRCz11 Supplementary files format and content: Tab separated barcode files and matrix files along with the tab separated gene file supplementary file are the output of CellRanger mapping  further processed by the SoupX package for ambient RNA removal. Supplementary files format and content: Loom files are the output of velocyto mapping distinguishing spliced and unspliced mRNAs. Supplementary files format and content: filtered scars.csv files contain the output of a custom scar filtering pipeline.", "adult brain", null, "Adult zebrafish brain tissue was extracted  optionally dissected to select a specific region of interest telencephalon  diencephalon  mesencephalon or rhombencephalon and then dissociated with a trypsin protocol. Briefly  the samples were incubated in 750 \u00b5l of HBSS glucose solution and dissocated with 15 \u00b5l of 0.05% trypsin EDTA Gibco for 30 minutes at 37\u00b0C with intermittent mixing. The disociation was stopped by addition of 750 \u00b5l of a BSA EBSS HEPES solution. Further sample handling steps were carried out on ice and for centrifugation at 4\u00b0C. The sample was filtered through a 100 \u00b5m filter  washed with cold HBSS and resuspended in 100 200 \u00b5l HBSS with 0.05% BSA  then filtered through a 35 \u00b5m filter and loaded on the 10x Chromium Controller. For the scSLAM seq samples  a papain dissociation protocol Worthington kit  according to manufecturer's instructions was used followed by an adapted scSLAM seq protocol for labeling nascent transcripts see sample specific entry. The standard transcriptome libraries were constructed according to the manufacturer's protocol 10X Genomics. For targeted libraries of scars used for lineage tracing  the cDNA obtained during the 10x protocol was used to set up individual PCR reactions for each target  specifically amplifying the sgRNA target site. The libraries for targeted PCR were constructed with primers compatible with the 10X Genomics kit  so they could be sequenced on the same platform.", null, "tissue:adult brain|cell type:mixed tissue dissociation|genotype:Tg[ubi:zebrabow M]", "GSM7875190", "GSM7875190: Lineage tracing rep1  cirbpb scars; Danio rerio; OTHER", "GSM7875190 r1", "GSM7875190", "1", "Adult zebrafish brain tissue was extracted  optionally dissected to select a specific region of interest telencephalon  diencephalon  mesencephalon or rhombencephalon and then dissociated with a trypsin protocol. Briefly  the samples were incubated in 750 \u00b5l of HBSS glucose solution and dissocated with 15 \u00b5l of 0.05% trypsin EDTA Gibco for 30 minutes at 37\u00b0C with intermittent mixing. The disociation was stopped by addition of 750 \u00b5l of a BSA EBSS HEPES solution. Further sample handling steps were carried out on ice and for centrifugation at 4\u00b0C. The sample was filtered through a 100 \u00b5m filter  washed with cold HBSS and resuspended in 100 200 \u00b5l HBSS with 0.05% BSA  then filtered through a 35 \u00b5m filter and loaded on the 10x Chromium Controller. For the scSLAM seq samples  a papain dissociation protocol Worthington kit  according to manufecturer's instructions was used followed by an adapted scSLAM seq protocol for labeling nascent transcripts see sample specific entry. The standard transcriptome libraries were constructed according to the manufacturer's protocol 10X Genomics. For targeted libraries of scars used for lineage tracing  the cDNA obtained during the 10x protocol was used to set up individual PCR reactions for each target  specifically amplifying the sgRNA target site. The libraries for targeted PCR were constructed with primers compatible with the 10X Genomics kit  so they could be sequenced on the same platform.", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP469552", null, "loader:fastq load.py", "lin1_cirbpb_scar_R1.fastq.gz lin1_cirbpb_scar_R2.fastq.gz", "fastq fastq", 157576336.0, 949552.0, "GSM7875190 r1", null, null, null, null, null, null, null, null, null, null, null, "SRX22323921", "SRS19374450", "SRA1743007", "Junker Lab, Berlin Institute for Medical Systems Biology, Max-Delbr\u00fcck-Center for Molecular Medicine", "Junker Lab, Berlin Institute for Medical Systems Biology, Max-Delbr\u00fcck-Center for Molecular Medicine", 2, 0.00141, 0.78069, 0.00053, 0.00877, 0.99857, 0.97822, 0.33536, 0.05199, 28, 120, "T", "B", "sc-like readlen", "illumina", "nextseq", "unknown", "other", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2023-10-31", "Adult", "Adult", "Brain", "Nervous System"], [28726, "SRR26623263", "SRX22323920", "SRS19374449", "SRP469552", "PRJNA1034159", "Dissecting the spatiotemporal diversity of adult neural stem cells", "GSE246714", "Other", "Adult stem cells are important for tissue turnover and regeneration. However  in most adult systems it remains elusive how stem cells assume different functional states and support spatially patterned tissue architecture. Here  we dissected the diversity of neural stem cells in the adult zebrafish brain  an organ that is characterized by pronounced zonation and high regenerative capacity. We combined single cell transcriptomics of dissected brain regions with massively parallel lineage tracing and in vivo RNA metabolic labeling to analyze regulation of neural stem cells in space and time. We detected a large diversity of neural stem cells  with some subtypes being restricted to a single brain region  while others were found globally across the brain. Global stem cell states are linked to neurogenic differentiation  with different states being involved in proliferative and non proliferative differentiation. Our work reveals principles of adult stem cell organization and establishes a resource for functional manipulation of neural stem cell subtypes. Overall design: Single cell RNA seq of adult zebrafish brain performed using 10x Genomics Gene Expression protocols to explore transcriptomic diversity of adult cell types. The samples were prepared either from whole brain  FACS sorted cells GFP positive cells from gfap:GFP line or a dissected single brain region  as indicated in the sample title. CRISPR based lineage tracing was performed for a subset of samples to dissect developmental lineage relationships between cells. ScSLAM seq was performed in combination with Notch pathway inhibition to assess response of stem cells to perturbation.", null, "pubmed:38365956", null, "Lineage tracing rep1  cfl1 scars", "GSM7875189", null, "source name:adult brain|tissue:adult brain|cell type:mixed tissue dissociation|genotype:Tg[ubi:zebrabow M]|geo loc name:missing|collection date:missing", "Lineage tracing rep1  cfl1 scars", "The transcriptome libraries were demultiplexed and mapped with CellRanger 6.1.1. In order to reduce batch effect  the gene expression matrices were processed with the SoupX tool Young & Behjati  2020 for removing ambient RNA contamination. A subset of libraries was also mapped with Velocyto v0.17.17 La Manno et al  2018 to create count matrices for unspliced and spliced molecules. The targeted lineage tracing libraries were aligned using bwa mem3 v.0.7.12 to individual references of endogenous genes used in the lineage tracing experiment actb1  actb2  cfl1  cirbpb  rpl39 and ube2e1. The scars were filtered with a custom pipeline to eliminate sequences that originate from PCR or sequencing errors. For custom code and further downstream analysis  see: https://github.com/nimitic/radial glia. Assembly: GRCz11 Supplementary files format and content: Tab separated barcode files and matrix files along with the tab separated gene file supplementary file are the output of CellRanger mapping  further processed by the SoupX package for ambient RNA removal. Supplementary files format and content: Loom files are the output of velocyto mapping distinguishing spliced and unspliced mRNAs. Supplementary files format and content: filtered scars.csv files contain the output of a custom scar filtering pipeline.", "adult brain", null, "Adult zebrafish brain tissue was extracted  optionally dissected to select a specific region of interest telencephalon  diencephalon  mesencephalon or rhombencephalon and then dissociated with a trypsin protocol. Briefly  the samples were incubated in 750 \u00b5l of HBSS glucose solution and dissocated with 15 \u00b5l of 0.05% trypsin EDTA Gibco for 30 minutes at 37\u00b0C with intermittent mixing. The disociation was stopped by addition of 750 \u00b5l of a BSA EBSS HEPES solution. Further sample handling steps were carried out on ice and for centrifugation at 4\u00b0C. The sample was filtered through a 100 \u00b5m filter  washed with cold HBSS and resuspended in 100 200 \u00b5l HBSS with 0.05% BSA  then filtered through a 35 \u00b5m filter and loaded on the 10x Chromium Controller. For the scSLAM seq samples  a papain dissociation protocol Worthington kit  according to manufecturer's instructions was used followed by an adapted scSLAM seq protocol for labeling nascent transcripts see sample specific entry. The standard transcriptome libraries were constructed according to the manufacturer's protocol 10X Genomics. For targeted libraries of scars used for lineage tracing  the cDNA obtained during the 10x protocol was used to set up individual PCR reactions for each target  specifically amplifying the sgRNA target site. The libraries for targeted PCR were constructed with primers compatible with the 10X Genomics kit  so they could be sequenced on the same platform.", null, "tissue:adult brain|cell type:mixed tissue dissociation|genotype:Tg[ubi:zebrabow M]", "GSM7875189", "GSM7875189: Lineage tracing rep1  cfl1 scars; Danio rerio; OTHER", "GSM7875189 r1", "GSM7875189", "1", "Adult zebrafish brain tissue was extracted  optionally dissected to select a specific region of interest telencephalon  diencephalon  mesencephalon or rhombencephalon and then dissociated with a trypsin protocol. Briefly  the samples were incubated in 750 \u00b5l of HBSS glucose solution and dissocated with 15 \u00b5l of 0.05% trypsin EDTA Gibco for 30 minutes at 37\u00b0C with intermittent mixing. The disociation was stopped by addition of 750 \u00b5l of a BSA EBSS HEPES solution. Further sample handling steps were carried out on ice and for centrifugation at 4\u00b0C. The sample was filtered through a 100 \u00b5m filter  washed with cold HBSS and resuspended in 100 200 \u00b5l HBSS with 0.05% BSA  then filtered through a 35 \u00b5m filter and loaded on the 10x Chromium Controller. For the scSLAM seq samples  a papain dissociation protocol Worthington kit  according to manufecturer's instructions was used followed by an adapted scSLAM seq protocol for labeling nascent transcripts see sample specific entry. The standard transcriptome libraries were constructed according to the manufacturer's protocol 10X Genomics. For targeted libraries of scars used for lineage tracing  the cDNA obtained during the 10x protocol was used to set up individual PCR reactions for each target  specifically amplifying the sgRNA target site. The libraries for targeted PCR were constructed with primers compatible with the 10X Genomics kit  so they could be sequenced on the same platform.", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP469552", null, "loader:fastq load.py", "lin1_cfl1_scar_R2.fastq.gz lin1_cfl1_scar_R1.fastq.gz", "fastq fastq", 381453696.0, 2184402.0, "GSM7875189 r1", null, null, null, null, null, null, null, null, null, null, null, "SRX22323920", "SRS19374449", "SRA1743007", "Junker Lab, Berlin Institute for Medical Systems Biology, Max-Delbr\u00fcck-Center for Molecular Medicine", "Junker Lab, Berlin Institute for Medical Systems Biology, Max-Delbr\u00fcck-Center for Molecular Medicine", 2, 0.0002, 0.91626, 0.00014, 0.00132, 0.99987, 0.99726, 0.16666, 0.56363, 28, 120, "T", "B", "sc-like readlen", "illumina", "nextseq", "unknown", "other", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2023-10-31", "Adult", "Adult", "Brain", "Nervous System"], [28727, "SRR26623264", "SRX22323919", "SRS19374448", "SRP469552", "PRJNA1034159", "Dissecting the spatiotemporal diversity of adult neural stem cells", "GSE246714", "Other", "Adult stem cells are important for tissue turnover and regeneration. However  in most adult systems it remains elusive how stem cells assume different functional states and support spatially patterned tissue architecture. Here  we dissected the diversity of neural stem cells in the adult zebrafish brain  an organ that is characterized by pronounced zonation and high regenerative capacity. We combined single cell transcriptomics of dissected brain regions with massively parallel lineage tracing and in vivo RNA metabolic labeling to analyze regulation of neural stem cells in space and time. We detected a large diversity of neural stem cells  with some subtypes being restricted to a single brain region  while others were found globally across the brain. Global stem cell states are linked to neurogenic differentiation  with different states being involved in proliferative and non proliferative differentiation. Our work reveals principles of adult stem cell organization and establishes a resource for functional manipulation of neural stem cell subtypes. Overall design: Single cell RNA seq of adult zebrafish brain performed using 10x Genomics Gene Expression protocols to explore transcriptomic diversity of adult cell types. The samples were prepared either from whole brain  FACS sorted cells GFP positive cells from gfap:GFP line or a dissected single brain region  as indicated in the sample title. CRISPR based lineage tracing was performed for a subset of samples to dissect developmental lineage relationships between cells. ScSLAM seq was performed in combination with Notch pathway inhibition to assess response of stem cells to perturbation.", null, "pubmed:38365956", null, "Lineage tracing rep1  actb2 scars", "GSM7875188", null, "source name:adult brain|tissue:adult brain|cell type:mixed tissue dissociation|genotype:Tg[ubi:zebrabow M]|geo loc name:missing|collection date:missing", "Lineage tracing rep1  actb2 scars", "The transcriptome libraries were demultiplexed and mapped with CellRanger 6.1.1. In order to reduce batch effect  the gene expression matrices were processed with the SoupX tool Young & Behjati  2020 for removing ambient RNA contamination. A subset of libraries was also mapped with Velocyto v0.17.17 La Manno et al  2018 to create count matrices for unspliced and spliced molecules. The targeted lineage tracing libraries were aligned using bwa mem3 v.0.7.12 to individual references of endogenous genes used in the lineage tracing experiment actb1  actb2  cfl1  cirbpb  rpl39 and ube2e1. The scars were filtered with a custom pipeline to eliminate sequences that originate from PCR or sequencing errors. For custom code and further downstream analysis  see: https://github.com/nimitic/radial glia. Assembly: GRCz11 Supplementary files format and content: Tab separated barcode files and matrix files along with the tab separated gene file supplementary file are the output of CellRanger mapping  further processed by the SoupX package for ambient RNA removal. Supplementary files format and content: Loom files are the output of velocyto mapping distinguishing spliced and unspliced mRNAs. Supplementary files format and content: filtered scars.csv files contain the output of a custom scar filtering pipeline.", "adult brain", null, "Adult zebrafish brain tissue was extracted  optionally dissected to select a specific region of interest telencephalon  diencephalon  mesencephalon or rhombencephalon and then dissociated with a trypsin protocol. Briefly  the samples were incubated in 750 \u00b5l of HBSS glucose solution and dissocated with 15 \u00b5l of 0.05% trypsin EDTA Gibco for 30 minutes at 37\u00b0C with intermittent mixing. The disociation was stopped by addition of 750 \u00b5l of a BSA EBSS HEPES solution. Further sample handling steps were carried out on ice and for centrifugation at 4\u00b0C. The sample was filtered through a 100 \u00b5m filter  washed with cold HBSS and resuspended in 100 200 \u00b5l HBSS with 0.05% BSA  then filtered through a 35 \u00b5m filter and loaded on the 10x Chromium Controller. For the scSLAM seq samples  a papain dissociation protocol Worthington kit  according to manufecturer's instructions was used followed by an adapted scSLAM seq protocol for labeling nascent transcripts see sample specific entry. The standard transcriptome libraries were constructed according to the manufacturer's protocol 10X Genomics. For targeted libraries of scars used for lineage tracing  the cDNA obtained during the 10x protocol was used to set up individual PCR reactions for each target  specifically amplifying the sgRNA target site. The libraries for targeted PCR were constructed with primers compatible with the 10X Genomics kit  so they could be sequenced on the same platform.", null, "tissue:adult brain|cell type:mixed tissue dissociation|genotype:Tg[ubi:zebrabow M]", "GSM7875188", "GSM7875188: Lineage tracing rep1  actb2 scars; Danio rerio; OTHER", "GSM7875188 r1", "GSM7875188", "1", "Adult zebrafish brain tissue was extracted  optionally dissected to select a specific region of interest telencephalon  diencephalon  mesencephalon or rhombencephalon and then dissociated with a trypsin protocol. Briefly  the samples were incubated in 750 \u00b5l of HBSS glucose solution and dissocated with 15 \u00b5l of 0.05% trypsin EDTA Gibco for 30 minutes at 37\u00b0C with intermittent mixing. The disociation was stopped by addition of 750 \u00b5l of a BSA EBSS HEPES solution. Further sample handling steps were carried out on ice and for centrifugation at 4\u00b0C. The sample was filtered through a 100 \u00b5m filter  washed with cold HBSS and resuspended in 100 200 \u00b5l HBSS with 0.05% BSA  then filtered through a 35 \u00b5m filter and loaded on the 10x Chromium Controller. For the scSLAM seq samples  a papain dissociation protocol Worthington kit  according to manufecturer's instructions was used followed by an adapted scSLAM seq protocol for labeling nascent transcripts see sample specific entry. The standard transcriptome libraries were constructed according to the manufacturer's protocol 10X Genomics. For targeted libraries of scars used for lineage tracing  the cDNA obtained during the 10x protocol was used to set up individual PCR reactions for each target  specifically amplifying the sgRNA target site. The libraries for targeted PCR were constructed with primers compatible with the 10X Genomics kit  so they could be sequenced on the same platform.", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP469552", null, "loader:fastq load.py", "lin1_actb2_scar_R1.fastq.gz lin1_actb2_scar_R2.fastq.gz", "fastq fastq", 491682118.0, 2851156.0, "GSM7875188 r1", null, null, null, null, null, null, null, null, null, null, null, "SRX22323919", "SRS19374448", "SRA1743007", "Junker Lab, Berlin Institute for Medical Systems Biology, Max-Delbr\u00fcck-Center for Molecular Medicine", "Junker Lab, Berlin Institute for Medical Systems Biology, Max-Delbr\u00fcck-Center for Molecular Medicine", 2, 0.00051, 0.41901, 0.00032, 0.0029, 0.99945, 0.99182, 0.57575, 0.007, 28, 120, "T", "B", "sc-like readlen", "illumina", "nextseq", "unknown", "other", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2023-10-31", "Adult", "Adult", "Brain", "Nervous System"], [28728, "SRR26623265", "SRX22323918", "SRS19374446", "SRP469552", "PRJNA1034159", "Dissecting the spatiotemporal diversity of adult neural stem cells", "GSE246714", "Other", "Adult stem cells are important for tissue turnover and regeneration. However  in most adult systems it remains elusive how stem cells assume different functional states and support spatially patterned tissue architecture. Here  we dissected the diversity of neural stem cells in the adult zebrafish brain  an organ that is characterized by pronounced zonation and high regenerative capacity. We combined single cell transcriptomics of dissected brain regions with massively parallel lineage tracing and in vivo RNA metabolic labeling to analyze regulation of neural stem cells in space and time. We detected a large diversity of neural stem cells  with some subtypes being restricted to a single brain region  while others were found globally across the brain. Global stem cell states are linked to neurogenic differentiation  with different states being involved in proliferative and non proliferative differentiation. Our work reveals principles of adult stem cell organization and establishes a resource for functional manipulation of neural stem cell subtypes. Overall design: Single cell RNA seq of adult zebrafish brain performed using 10x Genomics Gene Expression protocols to explore transcriptomic diversity of adult cell types. The samples were prepared either from whole brain  FACS sorted cells GFP positive cells from gfap:GFP line or a dissected single brain region  as indicated in the sample title. CRISPR based lineage tracing was performed for a subset of samples to dissect developmental lineage relationships between cells. ScSLAM seq was performed in combination with Notch pathway inhibition to assess response of stem cells to perturbation.", null, "pubmed:38365956", null, "Lineage tracing rep1  actb1 scars", "GSM7875187", null, "source name:adult brain|tissue:adult brain|cell type:mixed tissue dissociation|genotype:Tg[ubi:zebrabow M]|geo loc name:missing|collection date:missing", "Lineage tracing rep1  actb1 scars", "The transcriptome libraries were demultiplexed and mapped with CellRanger 6.1.1. In order to reduce batch effect  the gene expression matrices were processed with the SoupX tool Young & Behjati  2020 for removing ambient RNA contamination. A subset of libraries was also mapped with Velocyto v0.17.17 La Manno et al  2018 to create count matrices for unspliced and spliced molecules. The targeted lineage tracing libraries were aligned using bwa mem3 v.0.7.12 to individual references of endogenous genes used in the lineage tracing experiment actb1  actb2  cfl1  cirbpb  rpl39 and ube2e1. The scars were filtered with a custom pipeline to eliminate sequences that originate from PCR or sequencing errors. For custom code and further downstream analysis  see: https://github.com/nimitic/radial glia. Assembly: GRCz11 Supplementary files format and content: Tab separated barcode files and matrix files along with the tab separated gene file supplementary file are the output of CellRanger mapping  further processed by the SoupX package for ambient RNA removal. Supplementary files format and content: Loom files are the output of velocyto mapping distinguishing spliced and unspliced mRNAs. Supplementary files format and content: filtered scars.csv files contain the output of a custom scar filtering pipeline.", "adult brain", null, "Adult zebrafish brain tissue was extracted  optionally dissected to select a specific region of interest telencephalon  diencephalon  mesencephalon or rhombencephalon and then dissociated with a trypsin protocol. Briefly  the samples were incubated in 750 \u00b5l of HBSS glucose solution and dissocated with 15 \u00b5l of 0.05% trypsin EDTA Gibco for 30 minutes at 37\u00b0C with intermittent mixing. The disociation was stopped by addition of 750 \u00b5l of a BSA EBSS HEPES solution. Further sample handling steps were carried out on ice and for centrifugation at 4\u00b0C. The sample was filtered through a 100 \u00b5m filter  washed with cold HBSS and resuspended in 100 200 \u00b5l HBSS with 0.05% BSA  then filtered through a 35 \u00b5m filter and loaded on the 10x Chromium Controller. For the scSLAM seq samples  a papain dissociation protocol Worthington kit  according to manufecturer's instructions was used followed by an adapted scSLAM seq protocol for labeling nascent transcripts see sample specific entry. The standard transcriptome libraries were constructed according to the manufacturer's protocol 10X Genomics. For targeted libraries of scars used for lineage tracing  the cDNA obtained during the 10x protocol was used to set up individual PCR reactions for each target  specifically amplifying the sgRNA target site. The libraries for targeted PCR were constructed with primers compatible with the 10X Genomics kit  so they could be sequenced on the same platform.", null, "tissue:adult brain|cell type:mixed tissue dissociation|genotype:Tg[ubi:zebrabow M]", "GSM7875187", "GSM7875187: Lineage tracing rep1  actb1 scars; Danio rerio; OTHER", "GSM7875187 r1", "GSM7875187", "1", "Adult zebrafish brain tissue was extracted  optionally dissected to select a specific region of interest telencephalon  diencephalon  mesencephalon or rhombencephalon and then dissociated with a trypsin protocol. Briefly  the samples were incubated in 750 \u00b5l of HBSS glucose solution and dissocated with 15 \u00b5l of 0.05% trypsin EDTA Gibco for 30 minutes at 37\u00b0C with intermittent mixing. The disociation was stopped by addition of 750 \u00b5l of a BSA EBSS HEPES solution. Further sample handling steps were carried out on ice and for centrifugation at 4\u00b0C. The sample was filtered through a 100 \u00b5m filter  washed with cold HBSS and resuspended in 100 200 \u00b5l HBSS with 0.05% BSA  then filtered through a 35 \u00b5m filter and loaded on the 10x Chromium Controller. For the scSLAM seq samples  a papain dissociation protocol Worthington kit  according to manufecturer's instructions was used followed by an adapted scSLAM seq protocol for labeling nascent transcripts see sample specific entry. The standard transcriptome libraries were constructed according to the manufacturer's protocol 10X Genomics. For targeted libraries of scars used for lineage tracing  the cDNA obtained during the 10x protocol was used to set up individual PCR reactions for each target  specifically amplifying the sgRNA target site. The libraries for targeted PCR were constructed with primers compatible with the 10X Genomics kit  so they could be sequenced on the same platform.", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP469552", null, "loader:fastq load.py", "lin1_actb1_scar_R1.fastq.gz lin1_actb1_scar_R2.fastq.gz", "fastq fastq", 390405832.0, 2283319.0, "GSM7875187 r1", null, null, null, null, null, null, null, null, null, null, null, "SRX22323918", "SRS19374446", "SRA1743007", "Junker Lab, Berlin Institute for Medical Systems Biology, Max-Delbr\u00fcck-Center for Molecular Medicine", "Junker Lab, Berlin Institute for Medical Systems Biology, Max-Delbr\u00fcck-Center for Molecular Medicine", 2, 0.00038, 0.73548, 0.00017, 0.00057, 0.99963, 0.99571, 0.29729, 0.00243, 28, 120, "T", "B", "sc-like readlen", "illumina", "nextseq", "unknown", "other", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2023-10-31", "Adult", "Adult", "Brain", "Nervous System"], [28729, "SRR26623266", "SRX22323917", "SRS19374447", "SRP469552", "PRJNA1034159", "Dissecting the spatiotemporal diversity of adult neural stem cells", "GSE246714", "Other", "Adult stem cells are important for tissue turnover and regeneration. However  in most adult systems it remains elusive how stem cells assume different functional states and support spatially patterned tissue architecture. Here  we dissected the diversity of neural stem cells in the adult zebrafish brain  an organ that is characterized by pronounced zonation and high regenerative capacity. We combined single cell transcriptomics of dissected brain regions with massively parallel lineage tracing and in vivo RNA metabolic labeling to analyze regulation of neural stem cells in space and time. We detected a large diversity of neural stem cells  with some subtypes being restricted to a single brain region  while others were found globally across the brain. Global stem cell states are linked to neurogenic differentiation  with different states being involved in proliferative and non proliferative differentiation. Our work reveals principles of adult stem cell organization and establishes a resource for functional manipulation of neural stem cell subtypes. Overall design: Single cell RNA seq of adult zebrafish brain performed using 10x Genomics Gene Expression protocols to explore transcriptomic diversity of adult cell types. The samples were prepared either from whole brain  FACS sorted cells GFP positive cells from gfap:GFP line or a dissected single brain region  as indicated in the sample title. CRISPR based lineage tracing was performed for a subset of samples to dissect developmental lineage relationships between cells. ScSLAM seq was performed in combination with Notch pathway inhibition to assess response of stem cells to perturbation.", null, "pubmed:38365956", null, "Brain 23   telencephalon  Notch inhibition  scSLAMseq", "GSM7875186", null, "source name:adult brain|tissue:adult brain|tissue region:telencephalon|cell type:mixed tissue dissociation|genotype:wildtype|treatment:Notch inhibition DAPT|geo loc name:missing|collection date:missing", "Brain 23   telencephalon  Notch inhibition  scSLAMseq", "The transcriptome libraries were demultiplexed and mapped with CellRanger 6.1.1. In order to reduce batch effect  the gene expression matrices were processed with the SoupX tool Young & Behjati  2020 for removing ambient RNA contamination. A subset of libraries was also mapped with Velocyto v0.17.17 La Manno et al  2018 to create count matrices for unspliced and spliced molecules. The targeted lineage tracing libraries were aligned using bwa mem3 v.0.7.12 to individual references of endogenous genes used in the lineage tracing experiment actb1  actb2  cfl1  cirbpb  rpl39 and ube2e1. The scars were filtered with a custom pipeline to eliminate sequences that originate from PCR or sequencing errors. For custom code and further downstream analysis  see: https://github.com/nimitic/radial glia. Assembly: GRCz11 Supplementary files format and content: Tab separated barcode files and matrix files along with the tab separated gene file supplementary file are the output of CellRanger mapping  further processed by the SoupX package for ambient RNA removal. Supplementary files format and content: Loom files are the output of velocyto mapping distinguishing spliced and unspliced mRNAs. Supplementary files format and content: filtered scars.csv files contain the output of a custom scar filtering pipeline. Library strategy: scSLAM seq", "adult brain", "Notch inhibiton: zebrafish were incubated in a water bath containing system water with 50 \u00b5M DAPT Gamma Secretase Inhibitor  Sigma Aldrich for 48 hours.", "The samples were prepared according to a scSLAM seq protocol  adapted from Neuschulz et al 2023. Briefly: in order to label nascent transcripts  200 mM 4sU was delivered to fish brains by intraventricular injection 6 hours prior to sample collection. The brains were then collected  and a single cell suspension was prepared by papain dissociation. The resulting cell suspension was fixed in 80% methanol and a conversion of 4sU using iodoactamide adding 111 \u00b5l 100 mM IAA to 800 \u00b5l fixed sample was done overnight. The following day  the reaction was quanched with a quenching buffer containing 100 mM DTT  post which the sample was washed with a wash buffer and filtered though a 35 \u00b5m filter. The sample was then loaded on a 10X Chromium Controller and processed according to the standard scRNA seq protocol. Adult zebrafish brain tissue was extracted  optionally dissected to select a specific region of interest telencephalon  diencephalon  mesencephalon or rhombencephalon and then dissociated with a trypsin protocol. Briefly  the samples were incubated in 750 \u00b5l of HBSS glucose solution and dissocated with 15 \u00b5l of 0.05% trypsin EDTA Gibco for 30 minutes at 37\u00b0C with intermittent mixing. The disociation was stopped by addition of 750 \u00b5l of a BSA EBSS HEPES solution. Further sample handling steps were carried out on ice and for centrifugation at 4\u00b0C. The sample was filtered through a 100 \u00b5m filter  washed with cold HBSS and resuspended in 100 200 \u00b5l HBSS with 0.05% BSA  then filtered through a 35 \u00b5m filter and loaded on the 10x Chromium Controller. For the scSLAM seq samples  a papain dissociation protocol Worthington kit  according to manufecturer's instructions was used followed by an adapted scSLAM seq protocol for labeling nascent transcripts see sample specific entry. The standard transcriptome libraries were constructed according to the manufacturer's protocol 10X Genomics. For targeted libraries of scars used for lineage tracing  the cDNA obtained during the 10x protocol was used to set up individual PCR reactions for each target  specifically amplifying the sgRNA target site. The libraries for targeted PCR were constructed with primers compatible with the 10X Genomics kit  so they could be sequenced on the same platform.", null, "tissue:adult brain|tissue region:telencephalon|cell type:mixed tissue dissociation|genotype:wildtype|treatment:Notch inhibition DAPT", "GSM7875186", "GSM7875186: Brain 23   telencephalon  Notch inhibition  scSLAMseq; Danio rerio; OTHER", "GSM7875186 r1", "GSM7875186", "1", "The samples were prepared according to a scSLAM seq protocol  adapted from Neuschulz et al 2023. Briefly: in order to label nascent transcripts  200 mM 4sU was delivered to fish brains by intraventricular injection 6 hours prior to sample collection. The brains were then collected  and a single cell suspension was prepared by papain dissociation. The resulting cell suspension was fixed in 80% methanol and a conversion of 4sU using iodoactamide adding 111 \u00b5l 100 mM IAA to 800 \u00b5l fixed sample was done overnight. The following day  the reaction was quanched with a quenching buffer containing 100 mM DTT  post which the sample was washed with a wash buffer and filtered though a 35 \u00b5m filter. The sample was then loaded on a 10X Chromium Controller and processed according to the standard scRNA seq protocol. Adult zebrafish brain tissue was extracted  optionally dissected to select a specific region of interest telencephalon  diencephalon  mesencephalon or rhombencephalon and then dissociated with a trypsin protocol. Briefly  the samples were incubated in 750 \u00b5l of HBSS glucose solution and dissocated with 15 \u00b5l of 0.05% trypsin EDTA Gibco for 30 minutes at 37\u00b0C with intermittent mixing. The disociation was stopped by addition of 750 \u00b5l of a BSA EBSS HEPES solution. Further sample handling steps were carried out on ice and for centrifugation at 4\u00b0C. The sample was filtered through a 100 \u00b5m filter  washed with cold HBSS and resuspended in 100 200 \u00b5l HBSS with 0.05% BSA  then filtered through a 35 \u00b5m filter and loaded on the 10x Chromium Controller. For the scSLAM seq samples  a papain dissociation protocol Worthington kit  according to manufecturer's instructions was used followed by an adapted scSLAM seq protocol for labeling nascent transcripts see sample specific entry. The standard transcriptome libraries were constructed according to the manufacturer's protocol 10X Genomics. For targeted libraries of scars used for lineage tracing  the cDNA obtained during the 10x protocol was used to set up individual PCR reactions for each target  specifically amplifying the sgRNA target site. The libraries for targeted PCR were constructed with primers compatible with the 10X Genomics kit  so they could be sequenced on the same platform.", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP469552", null, "loader:fastq load.py", "b23_ni_tre_R1.fastq.gz b23_ni_tre_R2.fastq.gz", "fastq fastq", 62392458570.0, 271271559.0, "GSM7875186 r1", "0:28 1:202", "A:18682905645;C:13783082970;G:14751373116;T:15161083446;N:14013393", 28, 202, null, null, 18682905645, 13783082970, 14751373116, 15161083446, 14013393, "SRX22323917", "SRS19374447", "SRA1743007", "Junker Lab, Berlin Institute for Medical Systems Biology, Max-Delbr\u00fcck-Center for Molecular Medicine", "Junker Lab, Berlin Institute for Medical Systems Biology, Max-Delbr\u00fcck-Center for Molecular Medicine", 2, 0.01404, 0.82351, 0.00466, 0.1026, 0.99129, 0.86774, 0.36033, 0.67345, 28, 202, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "other", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2023-10-31", "Adult", "Adult", "Brain", "Nervous System"], [28730, "SRR26623267", "SRX22323916", "SRS19374445", "SRP469552", "PRJNA1034159", "Dissecting the spatiotemporal diversity of adult neural stem cells", "GSE246714", "Other", "Adult stem cells are important for tissue turnover and regeneration. However  in most adult systems it remains elusive how stem cells assume different functional states and support spatially patterned tissue architecture. Here  we dissected the diversity of neural stem cells in the adult zebrafish brain  an organ that is characterized by pronounced zonation and high regenerative capacity. We combined single cell transcriptomics of dissected brain regions with massively parallel lineage tracing and in vivo RNA metabolic labeling to analyze regulation of neural stem cells in space and time. We detected a large diversity of neural stem cells  with some subtypes being restricted to a single brain region  while others were found globally across the brain. Global stem cell states are linked to neurogenic differentiation  with different states being involved in proliferative and non proliferative differentiation. Our work reveals principles of adult stem cell organization and establishes a resource for functional manipulation of neural stem cell subtypes. Overall design: Single cell RNA seq of adult zebrafish brain performed using 10x Genomics Gene Expression protocols to explore transcriptomic diversity of adult cell types. The samples were prepared either from whole brain  FACS sorted cells GFP positive cells from gfap:GFP line or a dissected single brain region  as indicated in the sample title. CRISPR based lineage tracing was performed for a subset of samples to dissect developmental lineage relationships between cells. ScSLAM seq was performed in combination with Notch pathway inhibition to assess response of stem cells to perturbation.", null, "pubmed:38365956", null, "Brain 22   telencephalon  control  scSLAMseq", "GSM7875185", null, "source name:adult brain|tissue:adult brain|tissue region:telencephalon|cell type:mixed tissue dissociation|genotype:wildtype|treatment:Control DMSO|geo loc name:missing|collection date:missing", "Brain 22   telencephalon  control  scSLAMseq", "The transcriptome libraries were demultiplexed and mapped with CellRanger 6.1.1. In order to reduce batch effect  the gene expression matrices were processed with the SoupX tool Young & Behjati  2020 for removing ambient RNA contamination. A subset of libraries was also mapped with Velocyto v0.17.17 La Manno et al  2018 to create count matrices for unspliced and spliced molecules. The targeted lineage tracing libraries were aligned using bwa mem3 v.0.7.12 to individual references of endogenous genes used in the lineage tracing experiment actb1  actb2  cfl1  cirbpb  rpl39 and ube2e1. The scars were filtered with a custom pipeline to eliminate sequences that originate from PCR or sequencing errors. For custom code and further downstream analysis  see: https://github.com/nimitic/radial glia. Assembly: GRCz11 Supplementary files format and content: Tab separated barcode files and matrix files along with the tab separated gene file supplementary file are the output of CellRanger mapping  further processed by the SoupX package for ambient RNA removal. Supplementary files format and content: Loom files are the output of velocyto mapping distinguishing spliced and unspliced mRNAs. Supplementary files format and content: filtered scars.csv files contain the output of a custom scar filtering pipeline. Library strategy: scSLAM seq", "adult brain", "Control for Notch inhibition: zebrafish were incubated in a water bath containing system water with 1:200 diluted DMSO for 48 hours.", "The samples were prepared according to a scSLAM seq protocol  adapted from Neuschulz et al 2023. Briefly: in order to label nascent transcripts  200 mM 4sU was delivered to fish brains by intraventricular injection 6 hours prior to sample collection. The brains were then collected  and a single cell suspension was prepared by papain dissociation. The resulting cell suspension was fixed in 80% methanol and a conversion of 4sU using iodoactamide adding 111 \u00b5l 100 mM IAA to 800 \u00b5l fixed sample was done overnight. The following day  the reaction was quanched with a quenching buffer containing 100 mM DTT  post which the sample was washed with a wash buffer and filtered though a 35 \u00b5m filter. The sample was then loaded on a 10X Chromium Controller and processed according to the standard scRNA seq protocol. Adult zebrafish brain tissue was extracted  optionally dissected to select a specific region of interest telencephalon  diencephalon  mesencephalon or rhombencephalon and then dissociated with a trypsin protocol. Briefly  the samples were incubated in 750 \u00b5l of HBSS glucose solution and dissocated with 15 \u00b5l of 0.05% trypsin EDTA Gibco for 30 minutes at 37\u00b0C with intermittent mixing. The disociation was stopped by addition of 750 \u00b5l of a BSA EBSS HEPES solution. Further sample handling steps were carried out on ice and for centrifugation at 4\u00b0C. The sample was filtered through a 100 \u00b5m filter  washed with cold HBSS and resuspended in 100 200 \u00b5l HBSS with 0.05% BSA  then filtered through a 35 \u00b5m filter and loaded on the 10x Chromium Controller. For the scSLAM seq samples  a papain dissociation protocol Worthington kit  according to manufecturer's instructions was used followed by an adapted scSLAM seq protocol for labeling nascent transcripts see sample specific entry. The standard transcriptome libraries were constructed according to the manufacturer's protocol 10X Genomics. For targeted libraries of scars used for lineage tracing  the cDNA obtained during the 10x protocol was used to set up individual PCR reactions for each target  specifically amplifying the sgRNA target site. The libraries for targeted PCR were constructed with primers compatible with the 10X Genomics kit  so they could be sequenced on the same platform.", null, "tissue:adult brain|tissue region:telencephalon|cell type:mixed tissue dissociation|genotype:wildtype|treatment:Control DMSO", "GSM7875185", "GSM7875185: Brain 22   telencephalon  control  scSLAMseq; Danio rerio; OTHER", "GSM7875185 r1", "GSM7875185", "1", "The samples were prepared according to a scSLAM seq protocol  adapted from Neuschulz et al 2023. Briefly: in order to label nascent transcripts  200 mM 4sU was delivered to fish brains by intraventricular injection 6 hours prior to sample collection. The brains were then collected  and a single cell suspension was prepared by papain dissociation. The resulting cell suspension was fixed in 80% methanol and a conversion of 4sU using iodoactamide adding 111 \u00b5l 100 mM IAA to 800 \u00b5l fixed sample was done overnight. The following day  the reaction was quanched with a quenching buffer containing 100 mM DTT  post which the sample was washed with a wash buffer and filtered though a 35 \u00b5m filter. The sample was then loaded on a 10X Chromium Controller and processed according to the standard scRNA seq protocol. Adult zebrafish brain tissue was extracted  optionally dissected to select a specific region of interest telencephalon  diencephalon  mesencephalon or rhombencephalon and then dissociated with a trypsin protocol. Briefly  the samples were incubated in 750 \u00b5l of HBSS glucose solution and dissocated with 15 \u00b5l of 0.05% trypsin EDTA Gibco for 30 minutes at 37\u00b0C with intermittent mixing. The disociation was stopped by addition of 750 \u00b5l of a BSA EBSS HEPES solution. Further sample handling steps were carried out on ice and for centrifugation at 4\u00b0C. The sample was filtered through a 100 \u00b5m filter  washed with cold HBSS and resuspended in 100 200 \u00b5l HBSS with 0.05% BSA  then filtered through a 35 \u00b5m filter and loaded on the 10x Chromium Controller. For the scSLAM seq samples  a papain dissociation protocol Worthington kit  according to manufecturer's instructions was used followed by an adapted scSLAM seq protocol for labeling nascent transcripts see sample specific entry. The standard transcriptome libraries were constructed according to the manufacturer's protocol 10X Genomics. For targeted libraries of scars used for lineage tracing  the cDNA obtained during the 10x protocol was used to set up individual PCR reactions for each target  specifically amplifying the sgRNA target site. The libraries for targeted PCR were constructed with primers compatible with the 10X Genomics kit  so they could be sequenced on the same platform.", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP469552", null, "loader:fastq load.py", "b22_ni_con_R1.fastq.gz b22_ni_con_R2.fastq.gz", "fastq fastq", 59793114490.0, 259970063.0, "GSM7875185 r1", "0:28 1:202", "A:18600519530;C:12714987967;G:14147370465;T:14316863915;N:13372613", 28, 202, null, null, 18600519530, 12714987967, 14147370465, 14316863915, 13372613, "SRX22323916", "SRS19374445", "SRA1743007", "Junker Lab, Berlin Institute for Medical Systems Biology, Max-Delbr\u00fcck-Center for Molecular Medicine", "Junker Lab, Berlin Institute for Medical Systems Biology, Max-Delbr\u00fcck-Center for Molecular Medicine", 2, 0.01402, 0.79448, 0.00498, 0.11405, 0.99074, 0.8518, 0.39874, 0.67082, 28, 202, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "other", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2023-10-31", "Adult", "Adult", "Brain", "Nervous System"], [28754, "SRR26623291", "SRX22323897", "SRS19374426", "SRP469552", "PRJNA1034159", "Dissecting the spatiotemporal diversity of adult neural stem cells", "GSE246714", "Other", "Adult stem cells are important for tissue turnover and regeneration. However  in most adult systems it remains elusive how stem cells assume different functional states and support spatially patterned tissue architecture. Here  we dissected the diversity of neural stem cells in the adult zebrafish brain  an organ that is characterized by pronounced zonation and high regenerative capacity. We combined single cell transcriptomics of dissected brain regions with massively parallel lineage tracing and in vivo RNA metabolic labeling to analyze regulation of neural stem cells in space and time. We detected a large diversity of neural stem cells  with some subtypes being restricted to a single brain region  while others were found globally across the brain. Global stem cell states are linked to neurogenic differentiation  with different states being involved in proliferative and non proliferative differentiation. Our work reveals principles of adult stem cell organization and establishes a resource for functional manipulation of neural stem cell subtypes. Overall design: Single cell RNA seq of adult zebrafish brain performed using 10x Genomics Gene Expression protocols to explore transcriptomic diversity of adult cell types. The samples were prepared either from whole brain  FACS sorted cells GFP positive cells from gfap:GFP line or a dissected single brain region  as indicated in the sample title. CRISPR based lineage tracing was performed for a subset of samples to dissect developmental lineage relationships between cells. ScSLAM seq was performed in combination with Notch pathway inhibition to assess response of stem cells to perturbation.", null, "pubmed:38365956", null, "Lineage tracing rep2  ube2e1 scars", "GSM7875196", null, "source name:adult brain|tissue:adult brain|cell type:mixed tissue dissociation|genotype:Tg[ubi:zebrabow M]|geo loc name:missing|collection date:missing", "Lineage tracing rep2  ube2e1 scars", "The transcriptome libraries were demultiplexed and mapped with CellRanger 6.1.1. In order to reduce batch effect  the gene expression matrices were processed with the SoupX tool Young & Behjati  2020 for removing ambient RNA contamination. A subset of libraries was also mapped with Velocyto v0.17.17 La Manno et al  2018 to create count matrices for unspliced and spliced molecules. The targeted lineage tracing libraries were aligned using bwa mem3 v.0.7.12 to individual references of endogenous genes used in the lineage tracing experiment actb1  actb2  cfl1  cirbpb  rpl39 and ube2e1. The scars were filtered with a custom pipeline to eliminate sequences that originate from PCR or sequencing errors. For custom code and further downstream analysis  see: https://github.com/nimitic/radial glia. Assembly: GRCz11 Supplementary files format and content: Tab separated barcode files and matrix files along with the tab separated gene file supplementary file are the output of CellRanger mapping  further processed by the SoupX package for ambient RNA removal. Supplementary files format and content: Loom files are the output of velocyto mapping distinguishing spliced and unspliced mRNAs. Supplementary files format and content: filtered scars.csv files contain the output of a custom scar filtering pipeline.", "adult brain", null, "Adult zebrafish brain tissue was extracted  optionally dissected to select a specific region of interest telencephalon  diencephalon  mesencephalon or rhombencephalon and then dissociated with a trypsin protocol. Briefly  the samples were incubated in 750 \u00b5l of HBSS glucose solution and dissocated with 15 \u00b5l of 0.05% trypsin EDTA Gibco for 30 minutes at 37\u00b0C with intermittent mixing. The disociation was stopped by addition of 750 \u00b5l of a BSA EBSS HEPES solution. Further sample handling steps were carried out on ice and for centrifugation at 4\u00b0C. The sample was filtered through a 100 \u00b5m filter  washed with cold HBSS and resuspended in 100 200 \u00b5l HBSS with 0.05% BSA  then filtered through a 35 \u00b5m filter and loaded on the 10x Chromium Controller. For the scSLAM seq samples  a papain dissociation protocol Worthington kit  according to manufecturer's instructions was used followed by an adapted scSLAM seq protocol for labeling nascent transcripts see sample specific entry. The standard transcriptome libraries were constructed according to the manufacturer's protocol 10X Genomics. For targeted libraries of scars used for lineage tracing  the cDNA obtained during the 10x protocol was used to set up individual PCR reactions for each target  specifically amplifying the sgRNA target site. The libraries for targeted PCR were constructed with primers compatible with the 10X Genomics kit  so they could be sequenced on the same platform.", null, "tissue:adult brain|cell type:mixed tissue dissociation|genotype:Tg[ubi:zebrabow M]", "GSM7875196", "GSM7875196: Lineage tracing rep2  ube2e1 scars; Danio rerio; OTHER", "GSM7875196 r1", "GSM7875196", "1", "Adult zebrafish brain tissue was extracted  optionally dissected to select a specific region of interest telencephalon  diencephalon  mesencephalon or rhombencephalon and then dissociated with a trypsin protocol. Briefly  the samples were incubated in 750 \u00b5l of HBSS glucose solution and dissocated with 15 \u00b5l of 0.05% trypsin EDTA Gibco for 30 minutes at 37\u00b0C with intermittent mixing. The disociation was stopped by addition of 750 \u00b5l of a BSA EBSS HEPES solution. Further sample handling steps were carried out on ice and for centrifugation at 4\u00b0C. The sample was filtered through a 100 \u00b5m filter  washed with cold HBSS and resuspended in 100 200 \u00b5l HBSS with 0.05% BSA  then filtered through a 35 \u00b5m filter and loaded on the 10x Chromium Controller. For the scSLAM seq samples  a papain dissociation protocol Worthington kit  according to manufecturer's instructions was used followed by an adapted scSLAM seq protocol for labeling nascent transcripts see sample specific entry. The standard transcriptome libraries were constructed according to the manufacturer's protocol 10X Genomics. For targeted libraries of scars used for lineage tracing  the cDNA obtained during the 10x protocol was used to set up individual PCR reactions for each target  specifically amplifying the sgRNA target site. The libraries for targeted PCR were constructed with primers compatible with the 10X Genomics kit  so they could be sequenced on the same platform.", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP469552", null, "loader:fastq load.py", "lin2_ube2e1_scar_R1.fastq.gz lin2_ube2e1_scar_R2.fastq.gz", "fastq fastq", 213092161.0, 1190459.0, "GSM7875196 r1", null, null, null, null, null, null, null, null, null, null, null, "SRX22323897", "SRS19374426", "SRA1743007", "Junker Lab, Berlin Institute for Medical Systems Biology, Max-Delbr\u00fcck-Center for Molecular Medicine", "Junker Lab, Berlin Institute for Medical Systems Biology, Max-Delbr\u00fcck-Center for Molecular Medicine", 2, 0.00752, 0.90776, 0.00286, 0.01739, 0.99346, 0.95444, 0.46002, 0.96817, 28, 151, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "other", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2023-10-31", "Adult", "Adult", "Brain", "Nervous System"], [28755, "SRR26623292", "SRX22323896", "SRS19374425", "SRP469552", "PRJNA1034159", "Dissecting the spatiotemporal diversity of adult neural stem cells", "GSE246714", "Other", "Adult stem cells are important for tissue turnover and regeneration. However  in most adult systems it remains elusive how stem cells assume different functional states and support spatially patterned tissue architecture. Here  we dissected the diversity of neural stem cells in the adult zebrafish brain  an organ that is characterized by pronounced zonation and high regenerative capacity. We combined single cell transcriptomics of dissected brain regions with massively parallel lineage tracing and in vivo RNA metabolic labeling to analyze regulation of neural stem cells in space and time. We detected a large diversity of neural stem cells  with some subtypes being restricted to a single brain region  while others were found globally across the brain. Global stem cell states are linked to neurogenic differentiation  with different states being involved in proliferative and non proliferative differentiation. Our work reveals principles of adult stem cell organization and establishes a resource for functional manipulation of neural stem cell subtypes. Overall design: Single cell RNA seq of adult zebrafish brain performed using 10x Genomics Gene Expression protocols to explore transcriptomic diversity of adult cell types. The samples were prepared either from whole brain  FACS sorted cells GFP positive cells from gfap:GFP line or a dissected single brain region  as indicated in the sample title. CRISPR based lineage tracing was performed for a subset of samples to dissect developmental lineage relationships between cells. ScSLAM seq was performed in combination with Notch pathway inhibition to assess response of stem cells to perturbation.", null, "pubmed:38365956", null, "Lineage tracing rep2  rpl39 scars", "GSM7875195", null, "source name:adult brain|tissue:adult brain|cell type:mixed tissue dissociation|genotype:Tg[ubi:zebrabow M]|geo loc name:missing|collection date:missing", "Lineage tracing rep2  rpl39 scars", "The transcriptome libraries were demultiplexed and mapped with CellRanger 6.1.1. In order to reduce batch effect  the gene expression matrices were processed with the SoupX tool Young & Behjati  2020 for removing ambient RNA contamination. A subset of libraries was also mapped with Velocyto v0.17.17 La Manno et al  2018 to create count matrices for unspliced and spliced molecules. The targeted lineage tracing libraries were aligned using bwa mem3 v.0.7.12 to individual references of endogenous genes used in the lineage tracing experiment actb1  actb2  cfl1  cirbpb  rpl39 and ube2e1. The scars were filtered with a custom pipeline to eliminate sequences that originate from PCR or sequencing errors. For custom code and further downstream analysis  see: https://github.com/nimitic/radial glia. Assembly: GRCz11 Supplementary files format and content: Tab separated barcode files and matrix files along with the tab separated gene file supplementary file are the output of CellRanger mapping  further processed by the SoupX package for ambient RNA removal. Supplementary files format and content: Loom files are the output of velocyto mapping distinguishing spliced and unspliced mRNAs. Supplementary files format and content: filtered scars.csv files contain the output of a custom scar filtering pipeline.", "adult brain", null, "Adult zebrafish brain tissue was extracted  optionally dissected to select a specific region of interest telencephalon  diencephalon  mesencephalon or rhombencephalon and then dissociated with a trypsin protocol. Briefly  the samples were incubated in 750 \u00b5l of HBSS glucose solution and dissocated with 15 \u00b5l of 0.05% trypsin EDTA Gibco for 30 minutes at 37\u00b0C with intermittent mixing. The disociation was stopped by addition of 750 \u00b5l of a BSA EBSS HEPES solution. Further sample handling steps were carried out on ice and for centrifugation at 4\u00b0C. The sample was filtered through a 100 \u00b5m filter  washed with cold HBSS and resuspended in 100 200 \u00b5l HBSS with 0.05% BSA  then filtered through a 35 \u00b5m filter and loaded on the 10x Chromium Controller. For the scSLAM seq samples  a papain dissociation protocol Worthington kit  according to manufecturer's instructions was used followed by an adapted scSLAM seq protocol for labeling nascent transcripts see sample specific entry. The standard transcriptome libraries were constructed according to the manufacturer's protocol 10X Genomics. For targeted libraries of scars used for lineage tracing  the cDNA obtained during the 10x protocol was used to set up individual PCR reactions for each target  specifically amplifying the sgRNA target site. The libraries for targeted PCR were constructed with primers compatible with the 10X Genomics kit  so they could be sequenced on the same platform.", null, "tissue:adult brain|cell type:mixed tissue dissociation|genotype:Tg[ubi:zebrabow M]", "GSM7875195", "GSM7875195: Lineage tracing rep2  rpl39 scars; Danio rerio; OTHER", "GSM7875195 r1", "GSM7875195", "1", "Adult zebrafish brain tissue was extracted  optionally dissected to select a specific region of interest telencephalon  diencephalon  mesencephalon or rhombencephalon and then dissociated with a trypsin protocol. Briefly  the samples were incubated in 750 \u00b5l of HBSS glucose solution and dissocated with 15 \u00b5l of 0.05% trypsin EDTA Gibco for 30 minutes at 37\u00b0C with intermittent mixing. The disociation was stopped by addition of 750 \u00b5l of a BSA EBSS HEPES solution. Further sample handling steps were carried out on ice and for centrifugation at 4\u00b0C. The sample was filtered through a 100 \u00b5m filter  washed with cold HBSS and resuspended in 100 200 \u00b5l HBSS with 0.05% BSA  then filtered through a 35 \u00b5m filter and loaded on the 10x Chromium Controller. For the scSLAM seq samples  a papain dissociation protocol Worthington kit  according to manufecturer's instructions was used followed by an adapted scSLAM seq protocol for labeling nascent transcripts see sample specific entry. The standard transcriptome libraries were constructed according to the manufacturer's protocol 10X Genomics. For targeted libraries of scars used for lineage tracing  the cDNA obtained during the 10x protocol was used to set up individual PCR reactions for each target  specifically amplifying the sgRNA target site. The libraries for targeted PCR were constructed with primers compatible with the 10X Genomics kit  so they could be sequenced on the same platform.", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP469552", null, "loader:fastq load.py", "lin2_rpl39_scar_R2.fastq.gz lin2_rpl39_scar_R1.fastq.gz", "fastq fastq", 1023403502.0, 5717338.0, "GSM7875195 r1", null, null, null, null, null, null, null, null, null, null, null, "SRX22323896", "SRS19374425", "SRA1743007", "Junker Lab, Berlin Institute for Medical Systems Biology, Max-Delbr\u00fcck-Center for Molecular Medicine", "Junker Lab, Berlin Institute for Medical Systems Biology, Max-Delbr\u00fcck-Center for Molecular Medicine", 2, 0.00086, 0.83744, 0.0003, 0.00337, 0.99845, 0.97057, 0.26605, 0.40241, 28, 151, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "other", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2023-10-31", "Adult", "Adult", "Brain", "Nervous System"], [28756, "SRR26623293", "SRX22323895", "SRS19374424", "SRP469552", "PRJNA1034159", "Dissecting the spatiotemporal diversity of adult neural stem cells", "GSE246714", "Other", "Adult stem cells are important for tissue turnover and regeneration. However  in most adult systems it remains elusive how stem cells assume different functional states and support spatially patterned tissue architecture. Here  we dissected the diversity of neural stem cells in the adult zebrafish brain  an organ that is characterized by pronounced zonation and high regenerative capacity. We combined single cell transcriptomics of dissected brain regions with massively parallel lineage tracing and in vivo RNA metabolic labeling to analyze regulation of neural stem cells in space and time. We detected a large diversity of neural stem cells  with some subtypes being restricted to a single brain region  while others were found globally across the brain. Global stem cell states are linked to neurogenic differentiation  with different states being involved in proliferative and non proliferative differentiation. Our work reveals principles of adult stem cell organization and establishes a resource for functional manipulation of neural stem cell subtypes. Overall design: Single cell RNA seq of adult zebrafish brain performed using 10x Genomics Gene Expression protocols to explore transcriptomic diversity of adult cell types. The samples were prepared either from whole brain  FACS sorted cells GFP positive cells from gfap:GFP line or a dissected single brain region  as indicated in the sample title. CRISPR based lineage tracing was performed for a subset of samples to dissect developmental lineage relationships between cells. ScSLAM seq was performed in combination with Notch pathway inhibition to assess response of stem cells to perturbation.", null, "pubmed:38365956", null, "Lineage tracing rep2  cirbpb scars", "GSM7875194", null, "source name:adult brain|tissue:adult brain|cell type:mixed tissue dissociation|genotype:Tg[ubi:zebrabow M]|geo loc name:missing|collection date:missing", "Lineage tracing rep2  cirbpb scars", "The transcriptome libraries were demultiplexed and mapped with CellRanger 6.1.1. In order to reduce batch effect  the gene expression matrices were processed with the SoupX tool Young & Behjati  2020 for removing ambient RNA contamination. A subset of libraries was also mapped with Velocyto v0.17.17 La Manno et al  2018 to create count matrices for unspliced and spliced molecules. The targeted lineage tracing libraries were aligned using bwa mem3 v.0.7.12 to individual references of endogenous genes used in the lineage tracing experiment actb1  actb2  cfl1  cirbpb  rpl39 and ube2e1. The scars were filtered with a custom pipeline to eliminate sequences that originate from PCR or sequencing errors. For custom code and further downstream analysis  see: https://github.com/nimitic/radial glia. Assembly: GRCz11 Supplementary files format and content: Tab separated barcode files and matrix files along with the tab separated gene file supplementary file are the output of CellRanger mapping  further processed by the SoupX package for ambient RNA removal. Supplementary files format and content: Loom files are the output of velocyto mapping distinguishing spliced and unspliced mRNAs. Supplementary files format and content: filtered scars.csv files contain the output of a custom scar filtering pipeline.", "adult brain", null, "Adult zebrafish brain tissue was extracted  optionally dissected to select a specific region of interest telencephalon  diencephalon  mesencephalon or rhombencephalon and then dissociated with a trypsin protocol. Briefly  the samples were incubated in 750 \u00b5l of HBSS glucose solution and dissocated with 15 \u00b5l of 0.05% trypsin EDTA Gibco for 30 minutes at 37\u00b0C with intermittent mixing. The disociation was stopped by addition of 750 \u00b5l of a BSA EBSS HEPES solution. Further sample handling steps were carried out on ice and for centrifugation at 4\u00b0C. The sample was filtered through a 100 \u00b5m filter  washed with cold HBSS and resuspended in 100 200 \u00b5l HBSS with 0.05% BSA  then filtered through a 35 \u00b5m filter and loaded on the 10x Chromium Controller. For the scSLAM seq samples  a papain dissociation protocol Worthington kit  according to manufecturer's instructions was used followed by an adapted scSLAM seq protocol for labeling nascent transcripts see sample specific entry. The standard transcriptome libraries were constructed according to the manufacturer's protocol 10X Genomics. For targeted libraries of scars used for lineage tracing  the cDNA obtained during the 10x protocol was used to set up individual PCR reactions for each target  specifically amplifying the sgRNA target site. The libraries for targeted PCR were constructed with primers compatible with the 10X Genomics kit  so they could be sequenced on the same platform.", null, "tissue:adult brain|cell type:mixed tissue dissociation|genotype:Tg[ubi:zebrabow M]", "GSM7875194", "GSM7875194: Lineage tracing rep2  cirbpb scars; Danio rerio; OTHER", "GSM7875194 r1", "GSM7875194", "1", "Adult zebrafish brain tissue was extracted  optionally dissected to select a specific region of interest telencephalon  diencephalon  mesencephalon or rhombencephalon and then dissociated with a trypsin protocol. Briefly  the samples were incubated in 750 \u00b5l of HBSS glucose solution and dissocated with 15 \u00b5l of 0.05% trypsin EDTA Gibco for 30 minutes at 37\u00b0C with intermittent mixing. The disociation was stopped by addition of 750 \u00b5l of a BSA EBSS HEPES solution. Further sample handling steps were carried out on ice and for centrifugation at 4\u00b0C. The sample was filtered through a 100 \u00b5m filter  washed with cold HBSS and resuspended in 100 200 \u00b5l HBSS with 0.05% BSA  then filtered through a 35 \u00b5m filter and loaded on the 10x Chromium Controller. For the scSLAM seq samples  a papain dissociation protocol Worthington kit  according to manufecturer's instructions was used followed by an adapted scSLAM seq protocol for labeling nascent transcripts see sample specific entry. The standard transcriptome libraries were constructed according to the manufacturer's protocol 10X Genomics. For targeted libraries of scars used for lineage tracing  the cDNA obtained during the 10x protocol was used to set up individual PCR reactions for each target  specifically amplifying the sgRNA target site. The libraries for targeted PCR were constructed with primers compatible with the 10X Genomics kit  so they could be sequenced on the same platform.", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP469552", null, "loader:fastq load.py", "lin2_cirbpb_scar_R1.fastq.gz lin2_cirbpb_scar_R2.fastq.gz", "fastq fastq", 276120388.0, 1542572.0, "GSM7875194 r1", null, null, null, null, null, null, null, null, null, null, null, "SRX22323895", "SRS19374424", "SRA1743007", "Junker Lab, Berlin Institute for Medical Systems Biology, Max-Delbr\u00fcck-Center for Molecular Medicine", "Junker Lab, Berlin Institute for Medical Systems Biology, Max-Delbr\u00fcck-Center for Molecular Medicine", 2, 0.00206, 0.80328, 0.00078, 0.00662, 0.9975, 0.98039, 0.55421, 0.0258, 28, 151, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "other", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2023-10-31", "Adult", "Adult", "Brain", "Nervous System"], [28757, "SRR26623294", "SRX22323894", "SRS19374423", "SRP469552", "PRJNA1034159", "Dissecting the spatiotemporal diversity of adult neural stem cells", "GSE246714", "Other", "Adult stem cells are important for tissue turnover and regeneration. However  in most adult systems it remains elusive how stem cells assume different functional states and support spatially patterned tissue architecture. Here  we dissected the diversity of neural stem cells in the adult zebrafish brain  an organ that is characterized by pronounced zonation and high regenerative capacity. We combined single cell transcriptomics of dissected brain regions with massively parallel lineage tracing and in vivo RNA metabolic labeling to analyze regulation of neural stem cells in space and time. We detected a large diversity of neural stem cells  with some subtypes being restricted to a single brain region  while others were found globally across the brain. Global stem cell states are linked to neurogenic differentiation  with different states being involved in proliferative and non proliferative differentiation. Our work reveals principles of adult stem cell organization and establishes a resource for functional manipulation of neural stem cell subtypes. Overall design: Single cell RNA seq of adult zebrafish brain performed using 10x Genomics Gene Expression protocols to explore transcriptomic diversity of adult cell types. The samples were prepared either from whole brain  FACS sorted cells GFP positive cells from gfap:GFP line or a dissected single brain region  as indicated in the sample title. CRISPR based lineage tracing was performed for a subset of samples to dissect developmental lineage relationships between cells. ScSLAM seq was performed in combination with Notch pathway inhibition to assess response of stem cells to perturbation.", null, "pubmed:38365956", null, "Lineage tracing rep2  cfl1 scars", "GSM7875193", null, "source name:adult brain|tissue:adult brain|cell type:mixed tissue dissociation|genotype:Tg[ubi:zebrabow M]|geo loc name:missing|collection date:missing", "Lineage tracing rep2  cfl1 scars", "The transcriptome libraries were demultiplexed and mapped with CellRanger 6.1.1. In order to reduce batch effect  the gene expression matrices were processed with the SoupX tool Young & Behjati  2020 for removing ambient RNA contamination. A subset of libraries was also mapped with Velocyto v0.17.17 La Manno et al  2018 to create count matrices for unspliced and spliced molecules. The targeted lineage tracing libraries were aligned using bwa mem3 v.0.7.12 to individual references of endogenous genes used in the lineage tracing experiment actb1  actb2  cfl1  cirbpb  rpl39 and ube2e1. The scars were filtered with a custom pipeline to eliminate sequences that originate from PCR or sequencing errors. For custom code and further downstream analysis  see: https://github.com/nimitic/radial glia. Assembly: GRCz11 Supplementary files format and content: Tab separated barcode files and matrix files along with the tab separated gene file supplementary file are the output of CellRanger mapping  further processed by the SoupX package for ambient RNA removal. Supplementary files format and content: Loom files are the output of velocyto mapping distinguishing spliced and unspliced mRNAs. Supplementary files format and content: filtered scars.csv files contain the output of a custom scar filtering pipeline.", "adult brain", null, "Adult zebrafish brain tissue was extracted  optionally dissected to select a specific region of interest telencephalon  diencephalon  mesencephalon or rhombencephalon and then dissociated with a trypsin protocol. Briefly  the samples were incubated in 750 \u00b5l of HBSS glucose solution and dissocated with 15 \u00b5l of 0.05% trypsin EDTA Gibco for 30 minutes at 37\u00b0C with intermittent mixing. The disociation was stopped by addition of 750 \u00b5l of a BSA EBSS HEPES solution. Further sample handling steps were carried out on ice and for centrifugation at 4\u00b0C. The sample was filtered through a 100 \u00b5m filter  washed with cold HBSS and resuspended in 100 200 \u00b5l HBSS with 0.05% BSA  then filtered through a 35 \u00b5m filter and loaded on the 10x Chromium Controller. For the scSLAM seq samples  a papain dissociation protocol Worthington kit  according to manufecturer's instructions was used followed by an adapted scSLAM seq protocol for labeling nascent transcripts see sample specific entry. The standard transcriptome libraries were constructed according to the manufacturer's protocol 10X Genomics. For targeted libraries of scars used for lineage tracing  the cDNA obtained during the 10x protocol was used to set up individual PCR reactions for each target  specifically amplifying the sgRNA target site. The libraries for targeted PCR were constructed with primers compatible with the 10X Genomics kit  so they could be sequenced on the same platform.", null, "tissue:adult brain|cell type:mixed tissue dissociation|genotype:Tg[ubi:zebrabow M]", "GSM7875193", "GSM7875193: Lineage tracing rep2  cfl1 scars; Danio rerio; OTHER", "GSM7875193 r1", "GSM7875193", "1", "Adult zebrafish brain tissue was extracted  optionally dissected to select a specific region of interest telencephalon  diencephalon  mesencephalon or rhombencephalon and then dissociated with a trypsin protocol. Briefly  the samples were incubated in 750 \u00b5l of HBSS glucose solution and dissocated with 15 \u00b5l of 0.05% trypsin EDTA Gibco for 30 minutes at 37\u00b0C with intermittent mixing. The disociation was stopped by addition of 750 \u00b5l of a BSA EBSS HEPES solution. Further sample handling steps were carried out on ice and for centrifugation at 4\u00b0C. The sample was filtered through a 100 \u00b5m filter  washed with cold HBSS and resuspended in 100 200 \u00b5l HBSS with 0.05% BSA  then filtered through a 35 \u00b5m filter and loaded on the 10x Chromium Controller. For the scSLAM seq samples  a papain dissociation protocol Worthington kit  according to manufecturer's instructions was used followed by an adapted scSLAM seq protocol for labeling nascent transcripts see sample specific entry. The standard transcriptome libraries were constructed according to the manufacturer's protocol 10X Genomics. For targeted libraries of scars used for lineage tracing  the cDNA obtained during the 10x protocol was used to set up individual PCR reactions for each target  specifically amplifying the sgRNA target site. The libraries for targeted PCR were constructed with primers compatible with the 10X Genomics kit  so they could be sequenced on the same platform.", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP469552", null, "loader:fastq load.py", "lin2_cfl1_scar_R1.fastq.gz lin2_cfl1_scar_R2.fastq.gz", "fastq fastq", 791318009.0, 4420771.0, "GSM7875193 r1", null, null, null, null, null, null, null, null, null, null, null, "SRX22323894", "SRS19374423", "SRA1743007", "Junker Lab, Berlin Institute for Medical Systems Biology, Max-Delbr\u00fcck-Center for Molecular Medicine", "Junker Lab, Berlin Institute for Medical Systems Biology, Max-Delbr\u00fcck-Center for Molecular Medicine", 2, 0.00067, 0.46079, 0.00055, 0.16353, 0.99965, 0.99332, 0.52631, 0.44939, 28, 151, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "other", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2023-10-31", "Adult", "Adult", "Brain", "Nervous System"], [28758, "SRR26623295", "SRX22323893", "SRS19374421", "SRP469552", "PRJNA1034159", "Dissecting the spatiotemporal diversity of adult neural stem cells", "GSE246714", "Other", "Adult stem cells are important for tissue turnover and regeneration. However  in most adult systems it remains elusive how stem cells assume different functional states and support spatially patterned tissue architecture. Here  we dissected the diversity of neural stem cells in the adult zebrafish brain  an organ that is characterized by pronounced zonation and high regenerative capacity. We combined single cell transcriptomics of dissected brain regions with massively parallel lineage tracing and in vivo RNA metabolic labeling to analyze regulation of neural stem cells in space and time. We detected a large diversity of neural stem cells  with some subtypes being restricted to a single brain region  while others were found globally across the brain. Global stem cell states are linked to neurogenic differentiation  with different states being involved in proliferative and non proliferative differentiation. Our work reveals principles of adult stem cell organization and establishes a resource for functional manipulation of neural stem cell subtypes. Overall design: Single cell RNA seq of adult zebrafish brain performed using 10x Genomics Gene Expression protocols to explore transcriptomic diversity of adult cell types. The samples were prepared either from whole brain  FACS sorted cells GFP positive cells from gfap:GFP line or a dissected single brain region  as indicated in the sample title. CRISPR based lineage tracing was performed for a subset of samples to dissect developmental lineage relationships between cells. ScSLAM seq was performed in combination with Notch pathway inhibition to assess response of stem cells to perturbation.", null, "pubmed:38365956", null, "Lineage tracing rep1  ube2e1 scars", "GSM7875192", null, "source name:adult brain|tissue:adult brain|cell type:mixed tissue dissociation|genotype:Tg[ubi:zebrabow M]|geo loc name:missing|collection date:missing", "Lineage tracing rep1  ube2e1 scars", "The transcriptome libraries were demultiplexed and mapped with CellRanger 6.1.1. In order to reduce batch effect  the gene expression matrices were processed with the SoupX tool Young & Behjati  2020 for removing ambient RNA contamination. A subset of libraries was also mapped with Velocyto v0.17.17 La Manno et al  2018 to create count matrices for unspliced and spliced molecules. The targeted lineage tracing libraries were aligned using bwa mem3 v.0.7.12 to individual references of endogenous genes used in the lineage tracing experiment actb1  actb2  cfl1  cirbpb  rpl39 and ube2e1. The scars were filtered with a custom pipeline to eliminate sequences that originate from PCR or sequencing errors. For custom code and further downstream analysis  see: https://github.com/nimitic/radial glia. Assembly: GRCz11 Supplementary files format and content: Tab separated barcode files and matrix files along with the tab separated gene file supplementary file are the output of CellRanger mapping  further processed by the SoupX package for ambient RNA removal. Supplementary files format and content: Loom files are the output of velocyto mapping distinguishing spliced and unspliced mRNAs. Supplementary files format and content: filtered scars.csv files contain the output of a custom scar filtering pipeline.", "adult brain", null, "Adult zebrafish brain tissue was extracted  optionally dissected to select a specific region of interest telencephalon  diencephalon  mesencephalon or rhombencephalon and then dissociated with a trypsin protocol. Briefly  the samples were incubated in 750 \u00b5l of HBSS glucose solution and dissocated with 15 \u00b5l of 0.05% trypsin EDTA Gibco for 30 minutes at 37\u00b0C with intermittent mixing. The disociation was stopped by addition of 750 \u00b5l of a BSA EBSS HEPES solution. Further sample handling steps were carried out on ice and for centrifugation at 4\u00b0C. The sample was filtered through a 100 \u00b5m filter  washed with cold HBSS and resuspended in 100 200 \u00b5l HBSS with 0.05% BSA  then filtered through a 35 \u00b5m filter and loaded on the 10x Chromium Controller. For the scSLAM seq samples  a papain dissociation protocol Worthington kit  according to manufecturer's instructions was used followed by an adapted scSLAM seq protocol for labeling nascent transcripts see sample specific entry. The standard transcriptome libraries were constructed according to the manufacturer's protocol 10X Genomics. For targeted libraries of scars used for lineage tracing  the cDNA obtained during the 10x protocol was used to set up individual PCR reactions for each target  specifically amplifying the sgRNA target site. The libraries for targeted PCR were constructed with primers compatible with the 10X Genomics kit  so they could be sequenced on the same platform.", null, "tissue:adult brain|cell type:mixed tissue dissociation|genotype:Tg[ubi:zebrabow M]", "GSM7875192", "GSM7875192: Lineage tracing rep1  ube2e1 scars; Danio rerio; OTHER", "GSM7875192 r1", "GSM7875192", "1", "Adult zebrafish brain tissue was extracted  optionally dissected to select a specific region of interest telencephalon  diencephalon  mesencephalon or rhombencephalon and then dissociated with a trypsin protocol. Briefly  the samples were incubated in 750 \u00b5l of HBSS glucose solution and dissocated with 15 \u00b5l of 0.05% trypsin EDTA Gibco for 30 minutes at 37\u00b0C with intermittent mixing. The disociation was stopped by addition of 750 \u00b5l of a BSA EBSS HEPES solution. Further sample handling steps were carried out on ice and for centrifugation at 4\u00b0C. The sample was filtered through a 100 \u00b5m filter  washed with cold HBSS and resuspended in 100 200 \u00b5l HBSS with 0.05% BSA  then filtered through a 35 \u00b5m filter and loaded on the 10x Chromium Controller. For the scSLAM seq samples  a papain dissociation protocol Worthington kit  according to manufecturer's instructions was used followed by an adapted scSLAM seq protocol for labeling nascent transcripts see sample specific entry. The standard transcriptome libraries were constructed according to the manufacturer's protocol 10X Genomics. For targeted libraries of scars used for lineage tracing  the cDNA obtained during the 10x protocol was used to set up individual PCR reactions for each target  specifically amplifying the sgRNA target site. The libraries for targeted PCR were constructed with primers compatible with the 10X Genomics kit  so they could be sequenced on the same platform.", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP469552", null, "loader:fastq load.py", "lin1_ube2e1_scar_R1.fastq.gz lin1_ube2e1_scar_R2.fastq.gz", "fastq fastq", 99407618.0, 601781.0, "GSM7875192 r1", null, null, null, null, null, null, null, null, null, null, null, "SRX22323893", "SRS19374421", "SRA1743007", "Junker Lab, Berlin Institute for Medical Systems Biology, Max-Delbr\u00fcck-Center for Molecular Medicine", "Junker Lab, Berlin Institute for Medical Systems Biology, Max-Delbr\u00fcck-Center for Molecular Medicine", 2, 0.00657, 0.84532, 0.00205, 0.03049, 0.99537, 0.95286, 0.43306, 0.19203, 28, 150, "T", "B", "sc-like readlen", "illumina", "nextseq", "unknown", "other", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2023-10-31", "Adult", "Adult", "Brain", "Nervous System"], [28759, "SRR26623296", "SRX22323892", "SRS19374422", "SRP469552", "PRJNA1034159", "Dissecting the spatiotemporal diversity of adult neural stem cells", "GSE246714", "Other", "Adult stem cells are important for tissue turnover and regeneration. However  in most adult systems it remains elusive how stem cells assume different functional states and support spatially patterned tissue architecture. Here  we dissected the diversity of neural stem cells in the adult zebrafish brain  an organ that is characterized by pronounced zonation and high regenerative capacity. We combined single cell transcriptomics of dissected brain regions with massively parallel lineage tracing and in vivo RNA metabolic labeling to analyze regulation of neural stem cells in space and time. We detected a large diversity of neural stem cells  with some subtypes being restricted to a single brain region  while others were found globally across the brain. Global stem cell states are linked to neurogenic differentiation  with different states being involved in proliferative and non proliferative differentiation. Our work reveals principles of adult stem cell organization and establishes a resource for functional manipulation of neural stem cell subtypes. Overall design: Single cell RNA seq of adult zebrafish brain performed using 10x Genomics Gene Expression protocols to explore transcriptomic diversity of adult cell types. The samples were prepared either from whole brain  FACS sorted cells GFP positive cells from gfap:GFP line or a dissected single brain region  as indicated in the sample title. CRISPR based lineage tracing was performed for a subset of samples to dissect developmental lineage relationships between cells. ScSLAM seq was performed in combination with Notch pathway inhibition to assess response of stem cells to perturbation.", null, "pubmed:38365956", null, "Lineage tracing rep1  rpl39 scars", "GSM7875191", null, "source name:adult brain|tissue:adult brain|cell type:mixed tissue dissociation|genotype:Tg[ubi:zebrabow M]|geo loc name:missing|collection date:missing", "Lineage tracing rep1  rpl39 scars", "The transcriptome libraries were demultiplexed and mapped with CellRanger 6.1.1. In order to reduce batch effect  the gene expression matrices were processed with the SoupX tool Young & Behjati  2020 for removing ambient RNA contamination. A subset of libraries was also mapped with Velocyto v0.17.17 La Manno et al  2018 to create count matrices for unspliced and spliced molecules. The targeted lineage tracing libraries were aligned using bwa mem3 v.0.7.12 to individual references of endogenous genes used in the lineage tracing experiment actb1  actb2  cfl1  cirbpb  rpl39 and ube2e1. The scars were filtered with a custom pipeline to eliminate sequences that originate from PCR or sequencing errors. For custom code and further downstream analysis  see: https://github.com/nimitic/radial glia. Assembly: GRCz11 Supplementary files format and content: Tab separated barcode files and matrix files along with the tab separated gene file supplementary file are the output of CellRanger mapping  further processed by the SoupX package for ambient RNA removal. Supplementary files format and content: Loom files are the output of velocyto mapping distinguishing spliced and unspliced mRNAs. Supplementary files format and content: filtered scars.csv files contain the output of a custom scar filtering pipeline.", "adult brain", null, "Adult zebrafish brain tissue was extracted  optionally dissected to select a specific region of interest telencephalon  diencephalon  mesencephalon or rhombencephalon and then dissociated with a trypsin protocol. Briefly  the samples were incubated in 750 \u00b5l of HBSS glucose solution and dissocated with 15 \u00b5l of 0.05% trypsin EDTA Gibco for 30 minutes at 37\u00b0C with intermittent mixing. The disociation was stopped by addition of 750 \u00b5l of a BSA EBSS HEPES solution. Further sample handling steps were carried out on ice and for centrifugation at 4\u00b0C. The sample was filtered through a 100 \u00b5m filter  washed with cold HBSS and resuspended in 100 200 \u00b5l HBSS with 0.05% BSA  then filtered through a 35 \u00b5m filter and loaded on the 10x Chromium Controller. For the scSLAM seq samples  a papain dissociation protocol Worthington kit  according to manufecturer's instructions was used followed by an adapted scSLAM seq protocol for labeling nascent transcripts see sample specific entry. The standard transcriptome libraries were constructed according to the manufacturer's protocol 10X Genomics. For targeted libraries of scars used for lineage tracing  the cDNA obtained during the 10x protocol was used to set up individual PCR reactions for each target  specifically amplifying the sgRNA target site. The libraries for targeted PCR were constructed with primers compatible with the 10X Genomics kit  so they could be sequenced on the same platform.", null, "tissue:adult brain|cell type:mixed tissue dissociation|genotype:Tg[ubi:zebrabow M]", "GSM7875191", "GSM7875191: Lineage tracing rep1  rpl39 scars; Danio rerio; OTHER", "GSM7875191 r1", "GSM7875191", "1", "Adult zebrafish brain tissue was extracted  optionally dissected to select a specific region of interest telencephalon  diencephalon  mesencephalon or rhombencephalon and then dissociated with a trypsin protocol. Briefly  the samples were incubated in 750 \u00b5l of HBSS glucose solution and dissocated with 15 \u00b5l of 0.05% trypsin EDTA Gibco for 30 minutes at 37\u00b0C with intermittent mixing. The disociation was stopped by addition of 750 \u00b5l of a BSA EBSS HEPES solution. Further sample handling steps were carried out on ice and for centrifugation at 4\u00b0C. The sample was filtered through a 100 \u00b5m filter  washed with cold HBSS and resuspended in 100 200 \u00b5l HBSS with 0.05% BSA  then filtered through a 35 \u00b5m filter and loaded on the 10x Chromium Controller. For the scSLAM seq samples  a papain dissociation protocol Worthington kit  according to manufecturer's instructions was used followed by an adapted scSLAM seq protocol for labeling nascent transcripts see sample specific entry. The standard transcriptome libraries were constructed according to the manufacturer's protocol 10X Genomics. For targeted libraries of scars used for lineage tracing  the cDNA obtained during the 10x protocol was used to set up individual PCR reactions for each target  specifically amplifying the sgRNA target site. The libraries for targeted PCR were constructed with primers compatible with the 10X Genomics kit  so they could be sequenced on the same platform.", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP469552", null, "loader:fastq load.py", "lin1_rpl39_scar_R1.fastq.gz lin1_rpl39_scar_R2.fastq.gz", "fastq fastq", 401898718.0, 2276836.0, "GSM7875191 r1", null, null, null, null, null, null, null, null, null, null, null, "SRX22323892", "SRS19374422", "SRA1743007", "Junker Lab, Berlin Institute for Medical Systems Biology, Max-Delbr\u00fcck-Center for Molecular Medicine", "Junker Lab, Berlin Institute for Medical Systems Biology, Max-Delbr\u00fcck-Center for Molecular Medicine", 2, 0.00037, 0.2642, 0.00015, 0.00086, 0.99922, 0.99026, 0.23076, 0.42455, 28, 120, "T", "B", "sc-like readlen", "illumina", "nextseq", "unknown", "other", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2023-10-31", "Adult", "Adult", "Brain", "Nervous System"], [29746, "SRR27467679", "SRX23139227", "SRS20090270", "SRP482074", "PRJNA1061456", "tRAM seq: tRNA abundance and modification analysis during zebrafish embryo development", "PRJNA1061456", "Other", null, null, null, null, null, "ovary BS R2", null, "strain:TLAB fish|isolate:NA|breed:cross of zebrafish AB and the natural variant TL Tupfel Longfin|cultivar:NA|ecotype:NA|dev stage:adult|collection date:2022|geo loc name:Austria|sex:female|tissue:ovary|treatment:BS|BioSampleModel:Model organism or animal", null, null, null, null, null, null, null, null, "tRAM seq of zebrafish: ovary  BS  rep2", "EV02003", "EV02003", "RNA was extracted with Trizol  tRNA isolated by size selection on denaturing polyacrylamide gel  range 50 150 nt. The RNA was end repaired by alkaline deacylation and T4 PNK treatment  three prime adapter ligated with T4 RNA ligase 2  reverse transcribed with TGIRT. The cDNA was circularized with CircLigase and amplified with KAPA HiFi polymerase  using NEB Next indexed primers.", null, null, "OTHER", "TRANSCRIPTOMIC", "size fractionation", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP482074", null, null, "EV02003.R1.fastq.gz EV02003.R2.fastq.gz", "fastq fastq", 1031891720.0, 3416860.0, "EV02003.R1.fastq.gz", "0:151 1:151", "A:264464363;C:153440613;G:408557241;T:205367487;N:62016", 151, 151, null, null, 264464363, 153440613, 408557241, 205367487, 62016, "SRX23139227", "SRS20090270", "SRA1781872", "Medical University of Vienna|Cell and Developmental Biology", "Medical University of Vienna", 2, 0.0, 0.00019, 0.0, 0.00015, 1.0, 0.99993, null, 1.0, 151, 151, "T", "T", "mates < 9% mapping rate", "illumina", "nextseq", "unknown", "size_fractionation", "nebnext", "bulk", "unknown", "unknown", null, "Austria", "2024-01-09", "Adult", "Adult", "Gonad", "Reproductive System"], [29755, "SRR27467688", "SRX23139218", "SRS20090261", "SRP482074", "PRJNA1061456", "tRAM seq: tRNA abundance and modification analysis during zebrafish embryo development", "PRJNA1061456", "Other", null, null, null, null, null, "ovary DM R2", null, "strain:TLAB fish|isolate:NA|breed:cross of zebrafish AB and the natural variant TL Tupfel Longfin|cultivar:NA|ecotype:NA|dev stage:adult|collection date:2022|geo loc name:Austria|sex:female|tissue:ovary|treatment:DM|BioSampleModel:Model organism or animal", null, null, null, null, null, null, null, null, "tRAM seq of zebrafish: ovary  DM  rep2", "EV02002", "EV02002", "RNA was extracted with Trizol  tRNA isolated by size selection on denaturing polyacrylamide gel  range 50 150 nt. The RNA was end repaired by alkaline deacylation and T4 PNK treatment  three prime adapter ligated with T4 RNA ligase 2  reverse transcribed with TGIRT. The cDNA was circularized with CircLigase and amplified with KAPA HiFi polymerase  using NEB Next indexed primers.", null, null, "OTHER", "TRANSCRIPTOMIC", "size fractionation", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP482074", null, null, "EV02002.R1.fastq.gz EV02002.R2.fastq.gz", "fastq fastq", 861320308.0, 2852054.0, "EV02002.R1.fastq.gz", "0:151 1:151", "A:205625519;C:162178974;G:334206312;T:159256900;N:52603", 151, 151, null, null, 205625519, 162178974, 334206312, 159256900, 52603, "SRX23139218", "SRS20090261", "SRA1781872", "Medical University of Vienna|Cell and Developmental Biology", "Medical University of Vienna", 2, 2e-05, 0.00049, 0.0, 0.00027, 1.0, 0.99947, null, 0.44444, 151, 151, "T", "T", "mates < 9% mapping rate", "illumina", "nextseq", "unknown", "size_fractionation", "nebnext", "bulk", "unknown", "unknown", null, "Austria", "2024-01-09", "Adult", "Adult", "Gonad", "Reproductive System"], [29756, "SRR27467689", "SRX23139217", "SRS20090260", "SRP482074", "PRJNA1061456", "tRAM seq: tRNA abundance and modification analysis during zebrafish embryo development", "PRJNA1061456", "Other", null, null, null, null, null, "ovary mock R2", null, "strain:TLAB fish|isolate:NA|breed:cross of zebrafish AB and the natural variant TL Tupfel Longfin|cultivar:NA|ecotype:NA|dev stage:adult|collection date:2022|geo loc name:Austria|sex:female|tissue:ovary|treatment:mock|BioSampleModel:Model organism or animal", null, null, null, null, null, null, null, null, "tRAM seq of zebrafish: ovary  mock  rep2", "EV02001", "EV02001", "RNA was extracted with Trizol  tRNA isolated by size selection on denaturing polyacrylamide gel  range 50 150 nt. The RNA was end repaired by alkaline deacylation and T4 PNK treatment  three prime adapter ligated with T4 RNA ligase 2  reverse transcribed with TGIRT. The cDNA was circularized with CircLigase and amplified with KAPA HiFi polymerase  using NEB Next indexed primers.", null, null, "OTHER", "TRANSCRIPTOMIC", "size fractionation", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP482074", null, null, "EV02001.R1.fastq.gz EV02001.R2.fastq.gz", "fastq fastq", 520371066.0, 1723083.0, "EV02001.R1.fastq.gz", "0:151 1:151", "A:116107273;C:90896560;G:218652568;T:94682244;N:32421", 151, 151, null, null, 116107273, 90896560, 218652568, 94682244, 32421, "SRX23139217", "SRS20090260", "SRA1781872", "Medical University of Vienna|Cell and Developmental Biology", "Medical University of Vienna", 2, 2e-05, 0.00086, 0.0, 0.00078, 0.99995, 0.99981, 0.0, 0.61538, 151, 151, "T", "T", "mates < 9% mapping rate", "illumina", "nextseq", "unknown", "size_fractionation", "nebnext", "bulk", "unknown", "unknown", null, "Austria", "2024-01-09", "Adult", "Adult", "Gonad", "Reproductive System"], [29765, "SRR27437485", "SRX23109812", "SRS20064566", "SRP482074", "PRJNA1061456", "tRAM seq: tRNA abundance and modification analysis during zebrafish embryo development", "PRJNA1061456", "Other", null, null, null, null, null, "ovary BS R3", null, "strain:TLAB fish|breed:cross of zebrafish AB and the natural variant TL Tupfel Longfin|dev stage:adult|collection date:2022|geo loc name:Austria|sex:female|tissue:ovary|treatment:BS|BioSampleModel:Model organism or animal", null, null, null, null, null, null, null, null, "tRAM seq of zebrafish: ovary  BS  rep3", "EV04017", "EV04017", "RNA was extracted with Trizol  tRNA isolated by size selection on denaturing polyacrylamide gel  range 50 150 nt. The RNA was end repaired by alkaline deacylation and T4 PNK treatment  three prime adapter ligated with T4 RNA ligase 2  reverse transcribed with TGIRT. The cDNA was circularized with CircLigase and amplified with KAPA HiFi polymerase  using NEB Next indexed primers.", null, null, "OTHER", "TRANSCRIPTOMIC", "size fractionation", "SINGLE", "ILLUMINA", "NextSeq 500", null, "SRP482074", null, null, "EV04017.R1.fastq.gz", "fastq", 576584540.0, 4118461.0, "EV04017.R1.fastq.gz", "0:140", "A:149516980;C:91163801;G:169046762;T:166831111;N:25886", 140, null, null, null, 149516980, 91163801, 169046762, 166831111, 25886, "SRX23109812", "SRS20064566", "SRA1780298", "Medical University of Vienna|Cell and Developmental Biology", "Medical University of Vienna", 1, 0.0, null, 0.0, null, 1.0, null, null, null, 140, null, "T", null, "under 1.2% mapping rate", "illumina", "nextseq", "unknown", "size_fractionation", "nebnext", "bulk", "unknown", "unknown", null, "Austria", "2024-01-06", "Adult", "Adult", "Gonad", "Reproductive System"], [29776, "SRR27437496", "SRX23109801", "SRS20064555", "SRP482074", "PRJNA1061456", "tRAM seq: tRNA abundance and modification analysis during zebrafish embryo development", "PRJNA1061456", "Other", null, null, null, null, null, "ovary DM R3", null, "strain:TLAB fish|breed:cross of zebrafish AB and the natural variant TL Tupfel Longfin|dev stage:adult|collection date:2022|geo loc name:Austria|sex:female|tissue:ovary|treatment:DM|BioSampleModel:Model organism or animal", null, null, null, null, null, null, null, null, "tRAM seq of zebrafish: ovary  DM  rep3", "EV04016", "EV04016", "RNA was extracted with Trizol  tRNA isolated by size selection on denaturing polyacrylamide gel  range 50 150 nt. The RNA was end repaired by alkaline deacylation and T4 PNK treatment  three prime adapter ligated with T4 RNA ligase 2  reverse transcribed with TGIRT. The cDNA was circularized with CircLigase and amplified with KAPA HiFi polymerase  using NEB Next indexed primers.", null, null, "OTHER", "TRANSCRIPTOMIC", "size fractionation", "SINGLE", "ILLUMINA", "NextSeq 500", null, "SRP482074", null, null, "EV04016.R1.fastq.gz", "fastq", 635752880.0, 4541092.0, "EV04016.R1.fastq.gz", "0:140", "A:160072248;C:143996869;G:189137330;T:142516059;N:30374", 140, null, null, null, 160072248, 143996869, 189137330, 142516059, 30374, "SRX23109801", "SRS20064555", "SRA1780298", "Medical University of Vienna|Cell and Developmental Biology", "Medical University of Vienna", 1, 1e-05, null, 0.0, null, 0.99997, null, 1.0, null, 140, null, "T", null, "under 1.2% mapping rate", "illumina", "nextseq", "unknown", "size_fractionation", "nebnext", "bulk", "unknown", "unknown", null, "Austria", "2024-01-06", "Adult", "Adult", "Gonad", "Reproductive System"], [29777, "SRR27437497", "SRX23109800", "SRS20064554", "SRP482074", "PRJNA1061456", "tRAM seq: tRNA abundance and modification analysis during zebrafish embryo development", "PRJNA1061456", "Other", null, null, null, null, null, "ovary mock R3", null, "strain:TLAB fish|breed:cross of zebrafish AB and the natural variant TL Tupfel Longfin|dev stage:adult|collection date:2022|geo loc name:Austria|sex:female|tissue:ovary|treatment:mock|BioSampleModel:Model organism or animal", null, null, null, null, null, null, null, null, "tRAM seq of zebrafish: ovary  mock  rep3", "EV04015", "EV04015", "RNA was extracted with Trizol  tRNA isolated by size selection on denaturing polyacrylamide gel  range 50 150 nt. The RNA was end repaired by alkaline deacylation and T4 PNK treatment  three prime adapter ligated with T4 RNA ligase 2  reverse transcribed with TGIRT. The cDNA was circularized with CircLigase and amplified with KAPA HiFi polymerase  using NEB Next indexed primers.", null, null, "OTHER", "TRANSCRIPTOMIC", "size fractionation", "SINGLE", "ILLUMINA", "NextSeq 500", null, "SRP482074", null, null, "EV04015.R1.fastq.gz", "fastq", 489700680.0, 3497862.0, "EV04015.R1.fastq.gz", "0:140", "A:126641754;C:126582886;G:130564204;T:105889815;N:22021", 140, null, null, null, 126641754, 126582886, 130564204, 105889815, 22021, "SRX23109800", "SRS20064554", "SRA1780298", "Medical University of Vienna|Cell and Developmental Biology", "Medical University of Vienna", 1, 6e-05, null, 0.0, null, 0.99983, null, 0.55555, null, 140, null, "T", null, "under 1.2% mapping rate", "illumina", "nextseq", "unknown", "size_fractionation", "nebnext", "bulk", "unknown", "unknown", null, "Austria", "2024-01-06", "Adult", "Adult", "Gonad", "Reproductive System"], [29786, "SRR27435871", "SRX23108225", "SRS20063062", "SRP482074", "PRJNA1061456", "tRAM seq: tRNA abundance and modification analysis during zebrafish embryo development", "PRJNA1061456", "Other", null, null, null, null, null, "ovary BS R4", null, "strain:TLAB fish|isolate:NA|breed:cross of zebrafish AB and the natural variant TL Tupfel Longfin|cultivar:NA|ecotype:NA|dev stage:adult|collection date:2022|geo loc name:Austria|sex:female|tissue:ovary|treatment:BS|BioSampleModel:Model organism or animal", null, null, null, null, null, null, null, null, "tRAM seq of zebrafish: ovary  BS  rep4", "EV08003", "EV08003", "RNA was extracted with Trizol  tRNA isolated by size selection on denaturing polyacrylamide gel  range 50 150 nt. The RNA was end repaired by alkaline deacylation and T4 PNK treatment  three prime adapter ligated with T4 RNA ligase 2  reverse transcribed with TGIRT. The cDNA was circularized with CircLigase and amplified with KAPA HiFi polymerase  using NEB Next indexed primers.", null, null, "OTHER", "TRANSCRIPTOMIC", "size fractionation", "SINGLE", "ILLUMINA", "NextSeq 500", null, "SRP482074", null, null, "EV08003.R1.fastq.gz", "fastq", 571689580.0, 4083497.0, "EV08003.R1.fastq.gz", "0:140", "A:141414131;C:88722455;G:138790445;T:202723075;N:39474", 140, null, null, null, 141414131, 88722455, 138790445, 202723075, 39474, "SRX23108225", "SRS20063062", "SRA1780265", "Medical University of Vienna|Cell and Developmental Biology", "Medical University of Vienna", 1, 3e-05, null, 0.0, null, 0.99991, null, 0.75, null, 140, null, "T", null, "under 1.2% mapping rate", "illumina", "nextseq", "unknown", "size_fractionation", "nebnext", "bulk", "unknown", "unknown", null, "Austria", "2024-01-05", "Adult", "Adult", "Gonad", "Reproductive System"], [29797, "SRR27435882", "SRX23108214", "SRS20063050", "SRP482074", "PRJNA1061456", "tRAM seq: tRNA abundance and modification analysis during zebrafish embryo development", "PRJNA1061456", "Other", null, null, null, null, null, "ovary DM R4", null, "strain:TLAB fish|isolate:NA|breed:cross of zebrafish AB and the natural variant TL Tupfel Longfin|cultivar:NA|ecotype:NA|dev stage:adult|collection date:2022|geo loc name:Austria|sex:female|tissue:ovary|treatment:DM|BioSampleModel:Model organism or animal", null, null, null, null, null, null, null, null, "tRAM seq of zebrafish: ovary  DM  rep4", "EV08002", "EV08002", "RNA was extracted with Trizol  tRNA isolated by size selection on denaturing polyacrylamide gel  range 50 150 nt. The RNA was end repaired by alkaline deacylation and T4 PNK treatment  three prime adapter ligated with T4 RNA ligase 2  reverse transcribed with TGIRT. The cDNA was circularized with CircLigase and amplified with KAPA HiFi polymerase  using NEB Next indexed primers.", null, null, "OTHER", "TRANSCRIPTOMIC", "size fractionation", "SINGLE", "ILLUMINA", "NextSeq 500", null, "SRP482074", null, null, "EV08002.R1.fastq.gz", "fastq", 668593800.0, 4775670.0, "EV08002.R1.fastq.gz", "0:140", "A:164584224;C:175789134;G:175538168;T:152637106;N:45168", 140, null, null, null, 164584224, 175789134, 175538168, 152637106, 45168, "SRX23108214", "SRS20063050", "SRA1780265", "Medical University of Vienna|Cell and Developmental Biology", "Medical University of Vienna", 1, 0.00525, null, 2e-05, null, 0.99192, null, 0.63501, null, 140, null, "T", null, "under 1.2% mapping rate", "illumina", "nextseq", "unknown", "size_fractionation", "nebnext", "bulk", "unknown", "unknown", null, "Austria", "2024-01-05", "Adult", "Adult", "Gonad", "Reproductive System"], [29798, "SRR27435883", "SRX23108213", "SRS20063051", "SRP482074", "PRJNA1061456", "tRAM seq: tRNA abundance and modification analysis during zebrafish embryo development", "PRJNA1061456", "Other", null, null, null, null, null, "ovary mock R4", null, "strain:TLAB fish|isolate:NA|breed:cross of zebrafish AB and the natural variant TL Tupfel Longfin|cultivar:NA|ecotype:NA|dev stage:adult|collection date:2022|geo loc name:Austria|sex:female|tissue:ovary|treatment:mock|BioSampleModel:Model organism or animal", null, null, null, null, null, null, null, null, "tRAM seq of zebrafish: ovary  mock  rep4", "EV08001", "EV08001", "RNA was extracted with Trizol  tRNA isolated by size selection on denaturing polyacrylamide gel  range 50 150 nt. The RNA was end repaired by alkaline deacylation and T4 PNK treatment  three prime adapter ligated with T4 RNA ligase 2  reverse transcribed with TGIRT. The cDNA was circularized with CircLigase and amplified with KAPA HiFi polymerase  using NEB Next indexed primers.", null, null, "OTHER", "TRANSCRIPTOMIC", "size fractionation", "SINGLE", "ILLUMINA", "NextSeq 500", null, "SRP482074", null, null, "EV08001.R1.fastq.gz", "fastq", 753247460.0, 5380339.0, "EV08001.R1.fastq.gz", "0:140", "A:183862675;C:196453674;G:197604061;T:175275086;N:51964", 140, null, null, null, 183862675, 196453674, 197604061, 175275086, 51964, "SRX23108213", "SRS20063051", "SRA1780265", "Medical University of Vienna|Cell and Developmental Biology", "Medical University of Vienna", 1, 0.00754, null, 4e-05, null, 0.98957, null, 0.51048, null, 140, null, "T", null, "under 1.2% mapping rate", "illumina", "nextseq", "unknown", "size_fractionation", "nebnext", "bulk", "unknown", "unknown", null, "Austria", "2024-01-05", "Adult", "Adult", "Gonad", "Reproductive System"], [32508, "SRR29290248", "SRX24807391", "SRS21522263", "SRP511901", "PRJNA1120203", "Study of liver 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exposed to small car tire wear particles", null, null, "30 days experimental group parallel 3", "liver transcriptome", "L3 3", null, "strain:not applicable|isolate:not applicable|breed:zebrafish|cultivar:not applicable|ecotype:not applicable|age:3 month|dev stage:3 month|collection date:2023 08 23|geo loc name:China|sex:not collected|tissue:liver|birth date:2023 05 13|experiment description:Exposed to tire wear particles above 120 mesh excretion for 15 days|BioSampleModel:Model organism or animal", null, null, null, null, null, null, null, null, "Zebrafish liver", "L3 3", "L3 3", "Total RNA was extracted from the zebrafish liver tissue using a commercial RNA extraction kit following the manufacturer's instructions.The prepared library was sequenced on an Illumina HiSeq platform  generating paired end reads.", null, null, "OTHER", "METATRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP511901", null, null, "TLSC-5L.R1.fq.gz TLSC-5L.R2.fq.gz", "fastq 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description:Exposed to tire wear particles 80 100 mesh excretion for 15 days|BioSampleModel:Model organism or animal", null, null, null, null, null, null, null, null, "Zebrafish liver", "L5 3", "L5 3", "Total RNA was extracted from the zebrafish liver tissue using a commercial RNA extraction kit following the manufacturer's instructions.The prepared library was sequenced on an Illumina HiSeq platform  generating paired end reads.", null, null, "OTHER", "METATRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP511901", null, null, "TMSC-5L.R1.fq.gz TMSC-5L.R2.fq.gz", "fastq fastq", 6227549100.0, 20758497.0, "TMSC 5L.R1.fq.gz", "0:150 1:150", "A:1601663321;C:1467885504;G:1549957271;T:1607796578;N:246426", 150, 150, null, null, 1601663321, 1467885504, 1549957271, 1607796578, 246426, "SRX24807377", "SRS21522249", "SRA1889615", "Qingdao University of Science and technology|College of marine science and biological engineeri", "Qingdao University of Science and technology", null, null, null, null, null, null, null, null, null, null, null, "B", "B", "biological fallback assumption", "illumina", "novaseq_era", "unknown", "other", "unknown", "bulk", "unknown", "unknown", null, "China", "2024-06-05", "Adult", "Adult", "Liver", "Liver and Biliary System"], [32523, "SRR29290263", "SRX24807376", "SRS21522248", "SRP511901", "PRJNA1120203", "Study of liver transcriptome in zebrafish  May 29 '24", "PRJNA1120203", "Other", "Liver of the transcriptome data from zebrafish exposed to small car tire wear particles", null, null, "30 days experimental group parallel 2", "liver transcriptome", "L5 2", null, "strain:not applicable|isolate:not applicable|breed:zebrafish|cultivar:not applicable|ecotype:not applicable|age:3 month|dev stage:3 month|collection date:2023 08 24|geo loc name:China|sex:not collected|tissue:liver|birth date:2023 05 12|experiment description:Exposed to tire wear particles 80 100 mesh excretion for 15 days|BioSampleModel:Model organism or animal", null, null, null, null, null, null, null, null, "Zebrafish liver", "L5 2", "L5 2", "Total RNA was extracted from the zebrafish liver tissue using a commercial RNA extraction kit following the manufacturer's instructions.The prepared library was sequenced on an Illumina HiSeq platform  generating paired end reads.", null, null, "OTHER", "METATRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP511901", null, null, "TMSB-3L.R1.fq.gz TMSB-3L.R2.fq.gz", "fastq fastq", 5889087600.0, 19630292.0, "TMSB 3L.R1.fq.gz", "0:150 1:150", "A:1507527640;C:1395223794;G:1475557797;T:1510549619;N:228750", 150, 150, null, null, 1507527640, 1395223794, 1475557797, 1510549619, 228750, "SRX24807376", "SRS21522248", "SRA1889615", "Qingdao University of Science and technology|College of marine science and biological engineeri", "Qingdao University of Science and technology", null, null, null, null, null, null, null, null, null, null, null, "B", "B", "biological fallback assumption", "illumina", "novaseq_era", "unknown", "other", "unknown", "bulk", "unknown", "unknown", null, "China", "2024-06-05", "Adult", "Adult", "Liver", "Liver and Biliary System"], [32524, "SRR29290264", "SRX24807375", "SRS21522247", "SRP511901", "PRJNA1120203", "Study of liver transcriptome in zebrafish  May 29 '24", "PRJNA1120203", "Other", "Liver of the transcriptome data from zebrafish exposed to small car tire wear particles", null, null, "30 days experimental group parallel 1", "liver transcriptome", "L5 1", null, "strain:not applicable|isolate:not applicable|breed:zebrafish|cultivar:not applicable|ecotype:not applicable|age:3 month|dev stage:3 month|collection date:2023 08 24|geo loc name:China|sex:not collected|tissue:liver|birth date:2023 05 11|experiment description:Exposed to tire wear particles 80 100 mesh excretion for 15 days|BioSampleModel:Model organism or animal", null, null, null, null, null, null, null, null, "Zebrafish liver", "L5 1", "L5 1", "Total RNA was extracted from the zebrafish liver tissue using a commercial RNA extraction kit following the manufacturer's instructions.The prepared library was sequenced on an Illumina HiSeq platform  generating paired end reads.", null, null, "OTHER", "METATRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP511901", null, null, "TMSA-1L.R1.fq.gz TMSA-1L.R2.fq.gz", "fastq fastq", 6438780300.0, 21462601.0, "TMSA 1L.R1.fq.gz", "0:150 1:150", "A:1651115385;C:1542448300;G:1589631411;T:1655336061;N:249143", 150, 150, null, null, 1651115385, 1542448300, 1589631411, 1655336061, 249143, "SRX24807375", "SRS21522247", "SRA1889615", "Qingdao University of Science and technology|College of marine science and biological engineeri", "Qingdao University of Science and technology", null, null, null, null, null, null, null, null, null, null, null, "B", "B", "biological fallback assumption", "illumina", "novaseq_era", "unknown", "other", "unknown", "bulk", "unknown", "unknown", null, "China", "2024-06-05", "Adult", "Adult", "Liver", "Liver and Biliary System"], [32525, "SRR29290265", "SRX24807374", "SRS21522246", "SRP511901", "PRJNA1120203", "Study of liver transcriptome in zebrafish  May 29 '24", "PRJNA1120203", "Other", "Liver of the transcriptome data from zebrafish exposed to small car tire wear particles", null, null, "15 days experimental group parallel 3", "liver transcriptome", "L4 3", null, "strain:not applicable|isolate:not applicable|breed:zebrafish|cultivar:not applicable|ecotype:not applicable|age:3 month|dev stage:3 month|collection date:2023 08 09|geo loc name:China|sex:not collected|tissue:liver|birth date:2023 05 16|experiment description:Exposure to 80 100 mesh tire wear particles for 15 days|BioSampleModel:Model organism or animal", null, null, null, null, null, null, null, null, "Zebrafish liver", "L4 3", "L4 3", "Total RNA was extracted from the zebrafish liver tissue using a commercial RNA extraction kit following the manufacturer's instructions.The prepared library was sequenced on an Illumina HiSeq platform  generating paired end reads.", null, null, "OTHER", "METATRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP511901", null, null, "TMFC1-3L.R1.fq.gz TMFC1-3L.R2.fq.gz", "fastq fastq", 6083883300.0, 20279611.0, "TMFC1 3L.R1.fq.gz", "0:150 1:150", "A:1510698562;C:1511134044;G:1540128451;T:1521679717;N:242526", 150, 150, null, null, 1510698562, 1511134044, 1540128451, 1521679717, 242526, "SRX24807374", "SRS21522246", "SRA1889615", "Qingdao University of Science and technology|College of marine science and biological engineeri", "Qingdao University of Science and technology", null, null, null, null, null, null, null, null, null, null, null, "B", "B", "biological fallback assumption", "illumina", "novaseq_era", "unknown", "other", "unknown", "bulk", "unknown", "unknown", null, "China", "2024-06-05", "Adult", "Adult", "Liver", "Liver and Biliary System"], [32526, "SRR29290266", "SRX24807373", "SRS21522245", "SRP511901", "PRJNA1120203", "Study of liver transcriptome in zebrafish  May 29 '24", "PRJNA1120203", "Other", "Liver of the transcriptome data from zebrafish exposed to small car tire wear particles", null, null, "15 days experimental group parallel 2", "liver transcriptome", "L4 2", null, "strain:not applicable|isolate:not applicable|breed:zebrafish|cultivar:not applicable|ecotype:not applicable|age:3 month|dev stage:3 month|collection date:2023 08 09|geo loc name:China|sex:not collected|tissue:liver|birth date:2023 05 15|experiment description:Exposure to 80 100 mesh tire wear particles for 15 days|BioSampleModel:Model organism or animal", null, null, null, null, null, null, null, null, "Zebrafish liver", "L4 2", "L4 2", "Total RNA was extracted from the zebrafish liver tissue using a commercial RNA extraction kit following the manufacturer's instructions.The prepared library was sequenced on an Illumina HiSeq platform  generating paired end reads.", null, null, "OTHER", "METATRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP511901", null, null, "TMFB1-3L.R1.fq.gz TMFB1-3L.R2.fq.gz", "fastq fastq", 5908013700.0, 19693379.0, "TMFB1 3L.R1.fq.gz", "0:150 1:150", "A:1507137134;C:1415511620;G:1463261753;T:1521838130;N:265063", 150, 150, null, null, 1507137134, 1415511620, 1463261753, 1521838130, 265063, "SRX24807373", "SRS21522245", "SRA1889615", "Qingdao University of Science and technology|College of marine science and biological engineeri", "Qingdao University of Science and technology", null, null, null, null, null, null, null, null, null, null, null, "B", "B", "biological fallback assumption", "illumina", "novaseq_era", "unknown", "other", "unknown", "bulk", "unknown", "unknown", null, "China", "2024-06-05", "Adult", "Adult", "Liver", "Liver and Biliary System"], [32527, "SRR29290267", "SRX24807372", "SRS21522244", "SRP511901", "PRJNA1120203", "Study of liver transcriptome in zebrafish  May 29 '24", "PRJNA1120203", "Other", "Liver of the transcriptome data from zebrafish exposed to small car tire wear particles", null, null, "Control parallel 2", "liver transcriptome", "L1 2", null, "strain:not applicable|isolate:not applicable|breed:zebrafish|cultivar:not applicable|ecotype:not applicable|age:3 month|dev stage:3 month|collection date:2023 08 11|geo loc name:China|sex:not collected|tissue:liver|birth date:2023 05 12|experiment description:Sample from control group|BioSampleModel:Model organism or animal", null, null, null, null, null, null, null, null, "Zebrafish liver", "L1 2", "L1 2", "Total RNA was extracted from the zebrafish liver tissue using a commercial RNA extraction kit following the manufacturer's instructions.The prepared library was sequenced on an Illumina HiSeq platform  generating paired end reads.", null, null, "OTHER", "METATRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP511901", null, null, "FCFB1-3L.R1.fq.gz FCFB1-3L.R2.fq.gz", "fastq fastq", 6637856700.0, 22126189.0, "FCFB1 3L.R1.fq.gz", "0:150 1:150", "A:1714779556;C:1575842801;G:1628771136;T:1718209685;N:253522", 150, 150, null, null, 1714779556, 1575842801, 1628771136, 1718209685, 253522, "SRX24807372", "SRS21522244", "SRA1889615", "Qingdao University of Science and technology|College of marine science and biological engineeri", "Qingdao University of Science and technology", null, null, null, null, null, null, null, null, null, null, null, "B", "B", "biological fallback assumption", "illumina", "novaseq_era", "unknown", "other", "unknown", "bulk", "unknown", "unknown", null, "China", "2024-06-05", "Adult", "Adult", "Liver", "Liver and Biliary System"], [32528, "SRR29290268", "SRX24807371", "SRS21522243", "SRP511901", "PRJNA1120203", "Study of liver transcriptome in zebrafish  May 29 '24", "PRJNA1120203", "Other", "Liver of the transcriptome data from zebrafish exposed to small car tire wear particles", null, null, "Control parallel 1", "liver transcriptome", "L1 1", null, "strain:not applicable|isolate:not applicable|breed:zebrafish|cultivar:not applicable|ecotype:not applicable|age:3 month|dev stage:3 month|collection date:2023 08 11|geo loc name:China|sex:not collected|tissue:liver|birth date:2023 05 11|experiment description:Sample from control group|BioSampleModel:Model organism or animal", null, null, null, null, null, null, null, null, "Zebrafish liver", "L1 1", "L1 1", "Total RNA was extracted from the zebrafish liver tissue using a commercial RNA extraction kit following the manufacturer's instructions.The prepared library was sequenced on an Illumina HiSeq platform  generating paired end reads.", null, null, "OTHER", "METATRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP511901", null, null, "FCFA1-3L.R1.fq.gz FCFA1-3L.R2.fq.gz", "fastq fastq", 7360809900.0, 24536033.0, "FCFA1 3L.R1.fq.gz", "0:150 1:150", "A:1885247052;C:1777296186;G:1818891778;T:1879185198;N:189686", 150, 150, null, null, 1885247052, 1777296186, 1818891778, 1879185198, 189686, "SRX24807371", "SRS21522243", "SRA1889615", "Qingdao University of Science and technology|College of marine science and biological engineeri", "Qingdao University of Science and technology", null, null, null, null, null, null, null, null, null, null, null, "B", "B", "biological fallback assumption", "illumina", "novaseq_era", "unknown", "other", "unknown", "bulk", "unknown", "unknown", null, "China", "2024-06-05", "Adult", "Adult", "Liver", "Liver and Biliary System"], [32858, "SRR29482326", "SRX24993370", "SRS21694834", "SRP515140", "PRJNA1126247", "Specific oncogene activation of the cell of origin in mucosal melanoma [SORT seq]", "GSE270356", "Other", "Mucosal melanoma MM is a deadly cancer derived from mucosal melanocytes. To test the consequences of MM genetics  we develop a zebrafish model in which all melanocytes experience CCND1 expression and loss of PTEN and TP53. Surprisingly  melanoma only develops from melanocytes lining internal organs  analogous to the location of patient MM. We find that zebrafish MMs have a unique chromatin landscape from cutaneous melanoma. Internal melanocytes are labeled using a MM specific transcriptional enhancer. Normal zebrafish internal melanocytes share a gene expression signature with MMs. Patient and zebrafish MMs show increased migratory neural crest gene and decreased antigen presentation gene expression  consistent with the increased metastatic behavior and decreased immunotherapy sensitivity of MM. Our work suggests the cell state of the originating melanocyte influences the behavior of derived melanomas. Our animal model phenotypically and transcriptionally mimics patient tumors  allowing this model to be used for MM therapeutic discovery. As this is a non MAPK driven genetically engineered model of melanoma  our work also has implications for the 15% of cutaneous melanoma patients who lack MAPK driving mutations.  Overall design: Single cell RNA sequencing was done on internal vs. external normal adult zebrafish melanocytes using the SORT seq platform.", null, null, null, "Internal melanocytes", "GSM8340241", null, "source name:Internal melanocytes|tissue:Internal melanocytes|cell type:melanocytes|genotype:mitfa / ; roy /  fish injected with mitfa:GFP|geo loc name:missing|collection date:missing", "Internal melanocytes", "BWA was used to align paired end read to danRer11. Count tables were generated using MapAndGo. Count tables were corrected using UMI to remove duplicate reads. Transcript counts were adjusted using Poissonian counting statistics to yield the number of UMIs detected per cell. Counts were imported into R using the Seurat suite version 3.0 Assembly: danRer11 Supplementary files format and content: .tsv file contains count matrix file used for data normalization and visualization using Seurat Library strategy: SORT seq", "Internal melanocytes", null, "Respective tissues were mechanically dissociated  digested in TrypLE for 45 min Invitrogen  12563011  40uM filtered  spun down  and resuspended in FACs buffer dPBS Mg+/Ca+ free  with 2% FBS  pen/strep. Cells were heat lysed at 65\u00b0C followed by cDNA synthesis with barcodes. All the barcoded material from one plate was pooled into one library and amplified using in vitro transcription. Following amplification  library preparation was done following the CEL Seq2 protocol to prepare a cDNA library for sequencing using TruSeq small RNA primers Illumina.", "mitfa / ; roy /  zebrafish injected with mitfa:GFP were Raised to maturity to obtain tissues", "tissue:Internal melanocytes|cell type:melanocytes|genotype:mitfa / ; roy /  fish injected with mitfa:GFP", "GSM8340241", "GSM8340241: Internal melanocytes; Danio rerio; OTHER", "GSM8340241 r1", "GSM8340241", "1", "Respective tissues were mechanically dissociated  digested in TrypLE for 45 min Invitrogen  12563011  40uM filtered  spun down  and resuspended in FACs buffer dPBS Mg+/Ca+ free  with 2% FBS  pen/strep. Cells were heat lysed at 65\u00b0C followed by cDNA synthesis with barcodes. All the barcoded material from one plate was pooled into one library and amplified using in vitro transcription. Following amplification  library preparation was done following the CEL Seq2 protocol to prepare a cDNA library for sequencing using TruSeq small RNA primers Illumina.", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP515140", null, null, "HAR-MI-002_H5GCWBGXF_R2.fastq.gz HAR-MI-002_H5GCWBGXF_R1.fastq.gz", "fastq fastq", 2957975418.0, 34395063.0, "GSM8340241 r1", "0:26 1:60", "A:738954503;C:560052455;G:520746060;T:1137116132;N:1106268", 26, 60, null, null, 738954503, 560052455, 520746060, 1137116132, 1106268, "SRX24993370", "SRS21694834", "SRA1904773", "Insco Lab, Medical Oncology, Dana Farber Cancer Institute", "Insco Lab, Medical Oncology, Dana Farber Cancer Institute", 2, 0.11637, 0.84116, 0.10894, 0.31188, 0.98851, 0.71526, 0.6688, 0.60221, 26, 60, "T", "B", "sc-like readlen", "illumina", "nextseq", "unknown", "small_rna", "trueseq", "sc", "single_cell_plate", "celseq", null, "United States", "2024-06-20", "Undetermined", "Adult", "Skin", "Surface Structure"], [32859, "SRR29482327", "SRX24993369", "SRS21694833", "SRP515140", "PRJNA1126247", "Specific oncogene activation of the cell of origin in mucosal melanoma [SORT seq]", "GSE270356", "Other", "Mucosal melanoma MM is a deadly cancer derived from mucosal melanocytes. To test the consequences of MM genetics  we develop a zebrafish model in which all melanocytes experience CCND1 expression and loss of PTEN and TP53. Surprisingly  melanoma only develops from melanocytes lining internal organs  analogous to the location of patient MM. We find that zebrafish MMs have a unique chromatin landscape from cutaneous melanoma. Internal melanocytes are labeled using a MM specific transcriptional enhancer. Normal zebrafish internal melanocytes share a gene expression signature with MMs. Patient and zebrafish MMs show increased migratory neural crest gene and decreased antigen presentation gene expression  consistent with the increased metastatic behavior and decreased immunotherapy sensitivity of MM. Our work suggests the cell state of the originating melanocyte influences the behavior of derived melanomas. Our animal model phenotypically and transcriptionally mimics patient tumors  allowing this model to be used for MM therapeutic discovery. As this is a non MAPK driven genetically engineered model of melanoma  our work also has implications for the 15% of cutaneous melanoma patients who lack MAPK driving mutations.  Overall design: Single cell RNA sequencing was done on internal vs. external normal adult zebrafish melanocytes using the SORT seq platform.", null, null, null, "Cutaneous melanocytes", "GSM8340240", null, "source name:Cutaneous melanocytes|tissue:Cutaneous melanocytes|cell type:melanocytes|genotype:mitfa / ; roy /  fish injected with mitfa:GFP|geo loc name:missing|collection date:missing", "Cutaneous melanocytes", "BWA was used to align paired end read to danRer11. Count tables were generated using MapAndGo. Count tables were corrected using UMI to remove duplicate reads. Transcript counts were adjusted using Poissonian counting statistics to yield the number of UMIs detected per cell. Counts were imported into R using the Seurat suite version 3.0 Assembly: danRer11 Supplementary files format and content: .tsv file contains count matrix file used for data normalization and visualization using Seurat Library strategy: SORT seq", "Cutaneous melanocytes", null, "Respective tissues were mechanically dissociated  digested in TrypLE for 45 min Invitrogen  12563011  40uM filtered  spun down  and resuspended in FACs buffer dPBS Mg+/Ca+ free  with 2% FBS  pen/strep. Cells were heat lysed at 65\u00b0C followed by cDNA synthesis with barcodes. All the barcoded material from one plate was pooled into one library and amplified using in vitro transcription. Following amplification  library preparation was done following the CEL Seq2 protocol to prepare a cDNA library for sequencing using TruSeq small RNA primers Illumina.", "mitfa / ; roy /  zebrafish injected with mitfa:GFP were Raised to maturity to obtain tissues", "tissue:Cutaneous melanocytes|cell type:melanocytes|genotype:mitfa / ; roy /  fish injected with mitfa:GFP", "GSM8340240", "GSM8340240: Cutaneous melanocytes; Danio rerio; OTHER", "GSM8340240 r1", "GSM8340240", "1", "Respective tissues were mechanically dissociated  digested in TrypLE for 45 min Invitrogen  12563011  40uM filtered  spun down  and resuspended in FACs buffer dPBS Mg+/Ca+ free  with 2% FBS  pen/strep. Cells were heat lysed at 65\u00b0C followed by cDNA synthesis with barcodes. All the barcoded material from one plate was pooled into one library and amplified using in vitro transcription. Following amplification  library preparation was done following the CEL Seq2 protocol to prepare a cDNA library for sequencing using TruSeq small RNA primers Illumina.", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP515140", null, null, "HAR-MI-001_H5GCWBGXF_R2.fastq.gz HAR-MI-001_H5GCWBGXF_R1.fastq.gz", "fastq fastq", 2680460212.0, 31168142.0, "GSM8340240 r1", "0:26 1:60", "A:704357434;C:519158361;G:467098420;T:988838604;N:1007393", 26, 60, null, null, 704357434, 519158361, 467098420, 988838604, 1007393, "SRX24993369", "SRS21694833", "SRA1904773", "Insco Lab, Medical Oncology, Dana Farber Cancer Institute", "Insco Lab, Medical Oncology, Dana Farber Cancer Institute", 2, 0.11679, 0.81545, 0.10693, 0.5033, 0.9808, 0.76404, 0.44749, 0.57623, 26, 60, "T", "B", "sc-like readlen", "illumina", "nextseq", "unknown", "small_rna", "trueseq", "sc", "single_cell_plate", "celseq", null, "United States", "2024-06-20", "Undetermined", "Adult", "Skin", "Surface Structure"], [43987, "SRR6811828", "SRX3768868", "SRS3023414", "SRP121343", "PRJNA415636", "Simultaneous lineage tracing and cell type identification using CRISPR/Cas9 induced genetic scars", "GSE106121", "Other", "A key goal of developmental biology is to understand how a single cell transforms into a full grown organism consisting of many different cell types. Single cell RNA sequencing scRNA seq has become a widely used method due to its ability to identify all cell types in a tissue or organ in a systematic manner. However  a major challenge is to organize the resulting taxonomy of cell types into lineage trees revealing the developmental origin of cells. Here  we present a strategy for simultaneous lineage tracing and transcriptome profiling in thousands of single cells. By combining scRNA seq with computational analysis of lineage barcodes generated by genome editing of transgenic reporter genes  we reconstruct developmental lineage trees in zebrafish larvae and adult fish. In future analyses  LINNAEUS LINeage tracing by Nuclease Activated Editing of Ubiquitous Sequences can be used as a systematic approach for identifying the lineage origin of novel cell types  or of known cell types under different conditions. Overall design: Combining scRNA seq with computational analysis of lineage barcodes generated by genome editing of transgenic reporter genes.", null, "pubmed:29644996", null, "Pancreas 3 exo scar", "GSM3032171", null, "source name:Pancreas except primary islet  liver|strain/background:Zebrabow M|tissue:Pancreas except primary islet  liver|developmental stage:Adult", "Pancreas 3 exo scar", "Library strategy: Targeted amplification Scar reads have the same structure as transcript reads: they consist of a barcode  a UMI and a scar. The scar sequences were aligned using bwa mem6 to a reference of RFP. We defined a cell as a barcode with at least 500 reads. We removed reads that were unmapped  had an incorrect barcode  or did not start with the exact PCR primer we used. We truncated all scar sequences to 75 nucleotides and filtered out shorter sequences. To correct for sequencing errors  we implemented several rounds of scar filtering Supplementary Fig. 2 in publication. We started by counting the number of times each molecule was sequenced. Sequencing errors will typically have fewer reads than the actual scars they originate from. As a first filtering step  we therefore removed all molecules only seen once to reduce the complexity in the dataset for consecutive filtering steps. In the second filtering step  we aimed to remove easily recognizable sequencing errors. To this end  we consecutively considered scar sequences that have the same cellular barcode and UMI  UMIs that have the same cellular barcode and scar sequence  and cellular barcodes that have the same UMI and scar sequence. In each step  we kept only the molecule with the highest number of reads. The rationale behind this is that it is very improbable to have two valid scar sequences in the same cell with the same UMI  or to have a scar sequence with the same UMI appear in two different cells. The observation of two different UMIs for the same scar in the same cell is much more likely and corresponds to detection of multiple transcripts from the same locus  but information about scar expression levels was not required in our downstream analysis. In the third filtering step  we specifically targeted sequencing errors within each cell. We compared the scar sequences found within a cell to each other. We filtered out sequences that had a Hamming distance of 2 or less to another scar sequence in the same cell that occurred in at least eight times as many reads. Scar sequences in the same cell that were one Hamming distance apart but had a read ratio less than eight were tested on three criteria if both of them occurred at least twice in the scar library: Do both scars have more than one transcript?  Do both scars occur in cells independently from each other?  Do the UMIs of both scars have Hamming distance of two or more? If two of these criteria were true  the scars were kept and the sequences were placed on a list of validated scars that  if they occurred in the same cell in another library  did not have to be tested anymore. If one or zero criteria were true  the scar that had only one transcript  or the scar that did not occur independently  were filtered out. Genome build: N/A Supplementary files format and content: List of scar transcripts with cell barcode  scar name  cell type  scar probability and number of organisms that have this cell.", "Pancreas except primary islet  liver", null, "Single cell dissociation. 10X Genomics Chromium", null, "strain/background:Zebrabow M|tissue:Pancreas except primary islet  liver|developmental stage:Adult", "GSM3032171", "GSM3032171: Pancreas 3 exo scar; Danio rerio; OTHER", "GSM3032171", null, "1", "Single cell dissociation. 10X Genomics Chromium", "GEO Accession:GSM3032171", "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP121343", null, null, "P7exo_scar_R1.fastq.gz P7exo_scar_R2.fastq.gz", "fastq fastq", 4291410352.0, 34608148.0, "GSM3032171 r1", "0:26 1:98", "A:1266869162;C:1345773385;G:950601988;T:726078376;N:2087441", 26, 98, null, null, 1266869162, 1345773385, 950601988, 726078376, 2087441, "SRX3768868", "SRS3023414", "SRA623333", "GEO", "Max Delbr\u00fcck Center", 2, 0.00014, 0.00241, 0.00012, 0.00024, 0.99995, 0.99691, 0.0, 0.65306, 26, 98, "T", "T", "mates < 9% mapping rate", "illumina", "nextseq", "unknown", "other", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2018-03-06", "Adult", "Adult", "Multi-tissue", "Multi-system"], [43988, "SRR6811827", "SRX3768867", "SRS3023384", "SRP121343", "PRJNA415636", "Simultaneous lineage tracing and cell type identification using CRISPR/Cas9 induced genetic scars", "GSE106121", "Other", "A key goal of developmental biology is to understand how a single cell transforms into a full grown organism consisting of many different cell types. Single cell RNA sequencing scRNA seq has become a widely used method due to its ability to identify all cell types in a tissue or organ in a systematic manner. However  a major challenge is to organize the resulting taxonomy of cell types into lineage trees revealing the developmental origin of cells. Here  we present a strategy for simultaneous lineage tracing and transcriptome profiling in thousands of single cells. By combining scRNA seq with computational analysis of lineage barcodes generated by genome editing of transgenic reporter genes  we reconstruct developmental lineage trees in zebrafish larvae and adult fish. In future analyses  LINNAEUS LINeage tracing by Nuclease Activated Editing of Ubiquitous Sequences can be used as a systematic approach for identifying the lineage origin of novel cell types  or of known cell types under different conditions. Overall design: Combining scRNA seq with computational analysis of lineage barcodes generated by genome editing of transgenic reporter genes.", null, "pubmed:29644996", null, "Pancreas 3 endo scar", "GSM3032170", null, "source name:Primary pancreatic islet|strain/background:Zebrabow M|tissue:Primary pancreatic islet|developmental stage:Adult", "Pancreas 3 endo scar", "Library strategy: Targeted amplification Scar reads have the same structure as transcript reads: they consist of a barcode  a UMI and a scar. The scar sequences were aligned using bwa mem6 to a reference of RFP. We defined a cell as a barcode with at least 500 reads. We removed reads that were unmapped  had an incorrect barcode  or did not start with the exact PCR primer we used. We truncated all scar sequences to 75 nucleotides and filtered out shorter sequences. To correct for sequencing errors  we implemented several rounds of scar filtering Supplementary Fig. 2 in publication. We started by counting the number of times each molecule was sequenced. Sequencing errors will typically have fewer reads than the actual scars they originate from. As a first filtering step  we therefore removed all molecules only seen once to reduce the complexity in the dataset for consecutive filtering steps. In the second filtering step  we aimed to remove easily recognizable sequencing errors. To this end  we consecutively considered scar sequences that have the same cellular barcode and UMI  UMIs that have the same cellular barcode and scar sequence  and cellular barcodes that have the same UMI and scar sequence. In each step  we kept only the molecule with the highest number of reads. The rationale behind this is that it is very improbable to have two valid scar sequences in the same cell with the same UMI  or to have a scar sequence with the same UMI appear in two different cells. The observation of two different UMIs for the same scar in the same cell is much more likely and corresponds to detection of multiple transcripts from the same locus  but information about scar expression levels was not required in our downstream analysis. In the third filtering step  we specifically targeted sequencing errors within each cell. We compared the scar sequences found within a cell to each other. We filtered out sequences that had a Hamming distance of 2 or less to another scar sequence in the same cell that occurred in at least eight times as many reads. Scar sequences in the same cell that were one Hamming distance apart but had a read ratio less than eight were tested on three criteria if both of them occurred at least twice in the scar library: Do both scars have more than one transcript?  Do both scars occur in cells independently from each other?  Do the UMIs of both scars have Hamming distance of two or more? If two of these criteria were true  the scars were kept and the sequences were placed on a list of validated scars that  if they occurred in the same cell in another library  did not have to be tested anymore. If one or zero criteria were true  the scar that had only one transcript  or the scar that did not occur independently  were filtered out. Genome build: N/A Supplementary files format and content: List of scar transcripts with cell barcode  scar name  cell type  scar probability and number of organisms that have this cell.", "Primary pancreatic islet", null, "Single cell dissociation. 10X Genomics Chromium", null, "strain/background:Zebrabow M|tissue:Primary pancreatic islet|developmental stage:Adult", "GSM3032170", "GSM3032170: Pancreas 3 endo scar; Danio rerio; OTHER", "GSM3032170", null, "1", "Single cell dissociation. 10X Genomics Chromium", "GEO Accession:GSM3032170", "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP121343", null, null, "P7endo_scar_R1.fastq.gz P7endo_scar_R2.fastq.gz", "fastq fastq", 2537781396.0, 20465979.0, "GSM3032170 r1", "0:26 1:98", "A:741745261;C:801599713;G:561531527;T:431666561;N:1238334", 26, 98, null, null, 741745261, 801599713, 561531527, 431666561, 1238334, "SRX3768867", "SRS3023384", "SRA623333", "GEO", "Max Delbr\u00fcck Center", 2, 0.00014, 0.00289, 0.00012, 0.00028, 0.99995, 0.99602, 1.0, 0.68478, 26, 98, "T", "T", "mates < 9% mapping rate", "illumina", "nextseq", "unknown", "other", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2018-03-06", "Adult", "Adult", "Pancreas", "Endocrine System"], [43989, "SRR6811826", "SRX3768866", "SRS3023382", "SRP121343", "PRJNA415636", "Simultaneous lineage tracing and cell type identification using CRISPR/Cas9 induced genetic scars", "GSE106121", "Other", "A key goal of developmental biology is to understand how a single cell transforms into a full grown organism consisting of many different cell types. Single cell RNA sequencing scRNA seq has become a widely used method due to its ability to identify all cell types in a tissue or organ in a systematic manner. However  a major challenge is to organize the resulting taxonomy of cell types into lineage trees revealing the developmental origin of cells. Here  we present a strategy for simultaneous lineage tracing and transcriptome profiling in thousands of single cells. By combining scRNA seq with computational analysis of lineage barcodes generated by genome editing of transgenic reporter genes  we reconstruct developmental lineage trees in zebrafish larvae and adult fish. In future analyses  LINNAEUS LINeage tracing by Nuclease Activated Editing of Ubiquitous Sequences can be used as a systematic approach for identifying the lineage origin of novel cell types  or of known cell types under different conditions. Overall design: Combining scRNA seq with computational analysis of lineage barcodes generated by genome editing of transgenic reporter genes.", null, "pubmed:29644996", null, "Heart 3 scar", "GSM3032169", null, "source name:Heart and blood|strain/background:Zebrabow M|tissue:Heart and blood|developmental stage:Adult", "Heart 3 scar", "Library strategy: Targeted amplification Scar reads have the same structure as transcript reads: they consist of a barcode  a UMI and a scar. The scar sequences were aligned using bwa mem6 to a reference of RFP. We defined a cell as a barcode with at least 500 reads. We removed reads that were unmapped  had an incorrect barcode  or did not start with the exact PCR primer we used. We truncated all scar sequences to 75 nucleotides and filtered out shorter sequences. To correct for sequencing errors  we implemented several rounds of scar filtering Supplementary Fig. 2 in publication. We started by counting the number of times each molecule was sequenced. Sequencing errors will typically have fewer reads than the actual scars they originate from. As a first filtering step  we therefore removed all molecules only seen once to reduce the complexity in the dataset for consecutive filtering steps. In the second filtering step  we aimed to remove easily recognizable sequencing errors. To this end  we consecutively considered scar sequences that have the same cellular barcode and UMI  UMIs that have the same cellular barcode and scar sequence  and cellular barcodes that have the same UMI and scar sequence. In each step  we kept only the molecule with the highest number of reads. The rationale behind this is that it is very improbable to have two valid scar sequences in the same cell with the same UMI  or to have a scar sequence with the same UMI appear in two different cells. The observation of two different UMIs for the same scar in the same cell is much more likely and corresponds to detection of multiple transcripts from the same locus  but information about scar expression levels was not required in our downstream analysis. In the third filtering step  we specifically targeted sequencing errors within each cell. We compared the scar sequences found within a cell to each other. We filtered out sequences that had a Hamming distance of 2 or less to another scar sequence in the same cell that occurred in at least eight times as many reads. Scar sequences in the same cell that were one Hamming distance apart but had a read ratio less than eight were tested on three criteria if both of them occurred at least twice in the scar library: Do both scars have more than one transcript?  Do both scars occur in cells independently from each other?  Do the UMIs of both scars have Hamming distance of two or more? If two of these criteria were true  the scars were kept and the sequences were placed on a list of validated scars that  if they occurred in the same cell in another library  did not have to be tested anymore. If one or zero criteria were true  the scar that had only one transcript  or the scar that did not occur independently  were filtered out. Genome build: N/A Supplementary files format and content: List of scar transcripts with cell barcode  scar name  cell type  scar probability and number of organisms that have this cell.", "Heart and blood", null, "Single cell dissociation. 10X Genomics Chromium", null, "strain/background:Zebrabow M|tissue:Heart and blood|developmental stage:Adult", "GSM3032169", "GSM3032169: Heart 3 scar; Danio rerio; OTHER", "GSM3032169", null, "1", "Single cell dissociation. 10X Genomics Chromium", "GEO Accession:GSM3032169", "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP121343", null, null, "H7_scar_R1.fastq.gz H7_scar_R2.fastq.gz", "fastq fastq", 3999397296.0, 32253204.0, "GSM3032169 r1", "0:26 1:98", "A:1170970784;C:1255843391;G:881154893;T:689473188;N:1955040", 26, 98, null, null, 1170970784, 1255843391, 881154893, 689473188, 1955040, "SRX3768866", "SRS3023382", "SRA623333", "GEO", "Max Delbr\u00fcck Center", 2, 0.00018, 0.00228, 0.00015, 0.00019, 0.99991, 0.99659, 0.8, 0.67235, 26, 98, "T", "T", "mates < 9% mapping rate", "illumina", "nextseq", "unknown", "other", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2018-03-06", "Adult", "Adult", "Multi-tissue", "Multi-system"], [43990, "SRR6811825", "SRX3768865", "SRS3023383", "SRP121343", "PRJNA415636", "Simultaneous lineage tracing and cell type identification using CRISPR/Cas9 induced genetic scars", "GSE106121", "Other", "A key goal of developmental biology is to understand how a single cell transforms into a full grown organism consisting of many different cell types. Single cell RNA sequencing scRNA seq has become a widely used method due to its ability to identify all cell types in a tissue or organ in a systematic manner. However  a major challenge is to organize the resulting taxonomy of cell types into lineage trees revealing the developmental origin of cells. Here  we present a strategy for simultaneous lineage tracing and transcriptome profiling in thousands of single cells. By combining scRNA seq with computational analysis of lineage barcodes generated by genome editing of transgenic reporter genes  we reconstruct developmental lineage trees in zebrafish larvae and adult fish. In future analyses  LINNAEUS LINeage tracing by Nuclease Activated Editing of Ubiquitous Sequences can be used as a systematic approach for identifying the lineage origin of novel cell types  or of known cell types under different conditions. Overall design: Combining scRNA seq with computational analysis of lineage barcodes generated by genome editing of transgenic reporter genes.", null, "pubmed:29644996", null, "Brain 3 scar", "GSM3032168", null, "source name:Brain|strain/background:Zebrabow M|tissue:Brain|developmental stage:Adult", "Brain 3 scar", "Library strategy: Targeted amplification Scar reads have the same structure as transcript reads: they consist of a barcode  a UMI and a scar. The scar sequences were aligned using bwa mem6 to a reference of RFP. We defined a cell as a barcode with at least 500 reads. We removed reads that were unmapped  had an incorrect barcode  or did not start with the exact PCR primer we used. We truncated all scar sequences to 75 nucleotides and filtered out shorter sequences. To correct for sequencing errors  we implemented several rounds of scar filtering Supplementary Fig. 2 in publication. We started by counting the number of times each molecule was sequenced. Sequencing errors will typically have fewer reads than the actual scars they originate from. As a first filtering step  we therefore removed all molecules only seen once to reduce the complexity in the dataset for consecutive filtering steps. In the second filtering step  we aimed to remove easily recognizable sequencing errors. To this end  we consecutively considered scar sequences that have the same cellular barcode and UMI  UMIs that have the same cellular barcode and scar sequence  and cellular barcodes that have the same UMI and scar sequence. In each step  we kept only the molecule with the highest number of reads. The rationale behind this is that it is very improbable to have two valid scar sequences in the same cell with the same UMI  or to have a scar sequence with the same UMI appear in two different cells. The observation of two different UMIs for the same scar in the same cell is much more likely and corresponds to detection of multiple transcripts from the same locus  but information about scar expression levels was not required in our downstream analysis. In the third filtering step  we specifically targeted sequencing errors within each cell. We compared the scar sequences found within a cell to each other. We filtered out sequences that had a Hamming distance of 2 or less to another scar sequence in the same cell that occurred in at least eight times as many reads. Scar sequences in the same cell that were one Hamming distance apart but had a read ratio less than eight were tested on three criteria if both of them occurred at least twice in the scar library: Do both scars have more than one transcript?  Do both scars occur in cells independently from each other?  Do the UMIs of both scars have Hamming distance of two or more? If two of these criteria were true  the scars were kept and the sequences were placed on a list of validated scars that  if they occurred in the same cell in another library  did not have to be tested anymore. If one or zero criteria were true  the scar that had only one transcript  or the scar that did not occur independently  were filtered out. Genome build: N/A Supplementary files format and content: List of scar transcripts with cell barcode  scar name  cell type  scar probability and number of organisms that have this cell.", "Brain", null, "Single cell dissociation. 10X Genomics Chromium", null, "strain/background:Zebrabow M|tissue:Brain|developmental stage:Adult", "GSM3032168", "GSM3032168: Brain 3 scar; Danio rerio; OTHER", "GSM3032168", null, "1", "Single cell dissociation. 10X Genomics Chromium", "GEO Accession:GSM3032168", "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP121343", null, null, "B7_scar_R2.fastq.gz B7_scar_R1.fastq.gz", "fastq fastq", 1359725968.0, 10965532.0, "GSM3032168 r1", "0:26 1:98", "A:397239266;C:429529094;G:288126336;T:244165622;N:665650", 26, 98, null, null, 397239266, 429529094, 288126336, 244165622, 665650, "SRX3768865", "SRS3023383", "SRA623333", "GEO", "Max Delbr\u00fcck Center", 2, 0.00032, 0.00295, 0.00026, 0.0003, 0.99991, 0.99642, 0.3, 0.64327, 26, 98, "T", "T", "mates < 9% mapping rate", "illumina", "nextseq", "unknown", "other", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2018-03-06", "Adult", "Adult", "Brain", "Nervous System"], [44008, "SRR6211484", "SRX3320759", "SRS2626332", "SRP121343", "PRJNA415636", "Simultaneous lineage tracing and cell type identification using CRISPR/Cas9 induced genetic scars", "GSE106121", "Other", "A key goal of developmental biology is to understand how a single cell transforms into a full grown organism consisting of many different cell types. Single cell RNA sequencing scRNA seq has become a widely used method due to its ability to identify all cell types in a tissue or organ in a systematic manner. However  a major challenge is to organize the resulting taxonomy of cell types into lineage trees revealing the developmental origin of cells. Here  we present a strategy for simultaneous lineage tracing and transcriptome profiling in thousands of single cells. By combining scRNA seq with computational analysis of lineage barcodes generated by genome editing of transgenic reporter genes  we reconstruct developmental lineage trees in zebrafish larvae and adult fish. In future analyses  LINNAEUS LINeage tracing by Nuclease Activated Editing of Ubiquitous Sequences can be used as a systematic approach for identifying the lineage origin of novel cell types  or of known cell types under different conditions. Overall design: Combining scRNA seq with computational analysis of lineage barcodes generated by genome editing of transgenic reporter genes.", null, "pubmed:29644996", null, "Heart 2 scar", "GSM2830055", null, "source name:Heart and blood|strain/background:Zebrabow M|tissue:Heart and blood|developmental stage:Adult", "Heart 2 scar", "Library strategy: Targeted amplification Scar reads have the same structure as transcript reads: they consist of a barcode  a UMI and a scar. The scar sequences were aligned using bwa mem6 to a reference of RFP. We defined a cell as a barcode with at least 500 reads. We removed reads that were unmapped  had an incorrect barcode  or did not start with the exact PCR primer we used. We truncated all scar sequences to 75 nucleotides and filtered out shorter sequences. To correct for sequencing errors  we implemented several rounds of scar filtering Supplementary Fig. 2 in publication. We started by counting the number of times each molecule was sequenced. Sequencing errors will typically have fewer reads than the actual scars they originate from. As a first filtering step  we therefore removed all molecules only seen once to reduce the complexity in the dataset for consecutive filtering steps. In the second filtering step  we aimed to remove easily recognizable sequencing errors. To this end  we consecutively considered scar sequences that have the same cellular barcode and UMI  UMIs that have the same cellular barcode and scar sequence  and cellular barcodes that have the same UMI and scar sequence. In each step  we kept only the molecule with the highest number of reads. The rationale behind this is that it is very improbable to have two valid scar sequences in the same cell with the same UMI  or to have a scar sequence with the same UMI appear in two different cells. The observation of two different UMIs for the same scar in the same cell is much more likely and corresponds to detection of multiple transcripts from the same locus  but information about scar expression levels was not required in our downstream analysis. In the third filtering step  we specifically targeted sequencing errors within each cell. We compared the scar sequences found within a cell to each other. We filtered out sequences that had a Hamming distance of 2 or less to another scar sequence in the same cell that occurred in at least eight times as many reads. Scar sequences in the same cell that were one Hamming distance apart but had a read ratio less than eight were tested on three criteria if both of them occurred at least twice in the scar library: Do both scars have more than one transcript?  Do both scars occur in cells independently from each other?  Do the UMIs of both scars have Hamming distance of two or more? If two of these criteria were true  the scars were kept and the sequences were placed on a list of validated scars that  if they occurred in the same cell in another library  did not have to be tested anymore. If one or zero criteria were true  the scar that had only one transcript  or the scar that did not occur independently  were filtered out. In the fourth filtering step  we determined the distribution of reads for the scars we had kept so far. Based on this distribution  we set a cut off and filtered out the scars that did not have at least this number of reads. Finally  for each cell type  we determined the distribution of different scars seen per cell and set a maximum number of scars a cell of that type can have. We filtered out cells in which we observed more than this maximum number as possible doublets. Genome build: N/A Supplementary files format and content: List of scar transcripts with cell barcode  scar name  cell type  scar probability and number of organisms that have this cell.", "Heart and blood", null, "Single cell dissociation. 10X Genomics Chromium", null, "strain/background:Zebrabow M|tissue:Heart and blood|developmental stage:Adult", "GSM2830055", "GSM2830055: Heart 2 scar; Danio rerio; OTHER", "GSM2830055", null, "1", "Single cell dissociation. 10X Genomics Chromium", "GEO Accession:GSM2830055", "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP121343", null, null, "H6_scar_R1.fastq.gz H6_scar_R2.fastq.gz", "fastq fastq", 2079107172.0, 15065994.0, "GSM2830055 r1", "0:28 1:110", "A:580640871;C:641740953;G:501505035;T:355092832;N:127481", 28, 110, null, null, 580640871, 641740953, 501505035, 355092832, 127481, "SRX3320759", "SRS2626332", "SRA623333", "GEO", "Max Delbr\u00fcck Center", 2, 5e-05, 0.00253, 4e-05, 0.00023, 1.0, 0.99778, null, 0.58419, 28, 110, "T", "T", "mates < 9% mapping rate", "illumina", "nextseq", "unknown", "other", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2017-10-24", "Adult", "Adult", "Multi-tissue", "Multi-system"], [44009, "SRR6211483", "SRX3320758", "SRS2626348", "SRP121343", "PRJNA415636", "Simultaneous lineage tracing and cell type identification using CRISPR/Cas9 induced genetic scars", "GSE106121", "Other", "A key goal of developmental biology is to understand how a single cell transforms into a full grown organism consisting of many different cell types. Single cell RNA sequencing scRNA seq has become a widely used method due to its ability to identify all cell types in a tissue or organ in a systematic manner. However  a major challenge is to organize the resulting taxonomy of cell types into lineage trees revealing the developmental origin of cells. Here  we present a strategy for simultaneous lineage tracing and transcriptome profiling in thousands of single cells. By combining scRNA seq with computational analysis of lineage barcodes generated by genome editing of transgenic reporter genes  we reconstruct developmental lineage trees in zebrafish larvae and adult fish. In future analyses  LINNAEUS LINeage tracing by Nuclease Activated Editing of Ubiquitous Sequences can be used as a systematic approach for identifying the lineage origin of novel cell types  or of known cell types under different conditions. Overall design: Combining scRNA seq with computational analysis of lineage barcodes generated by genome editing of transgenic reporter genes.", null, "pubmed:29644996", null, "Pancreas 2 scar", "GSM2830054", null, "source name:Pancreas and liver|strain/background:Zebrabow M|tissue:Pancreas and liver|developmental stage:Adult", "Pancreas 2 scar", "Library strategy: Targeted amplification Scar reads have the same structure as transcript reads: they consist of a barcode  a UMI and a scar. The scar sequences were aligned using bwa mem6 to a reference of RFP. We defined a cell as a barcode with at least 500 reads. We removed reads that were unmapped  had an incorrect barcode  or did not start with the exact PCR primer we used. We truncated all scar sequences to 75 nucleotides and filtered out shorter sequences. To correct for sequencing errors  we implemented several rounds of scar filtering Supplementary Fig. 2 in publication. We started by counting the number of times each molecule was sequenced. Sequencing errors will typically have fewer reads than the actual scars they originate from. As a first filtering step  we therefore removed all molecules only seen once to reduce the complexity in the dataset for consecutive filtering steps. In the second filtering step  we aimed to remove easily recognizable sequencing errors. To this end  we consecutively considered scar sequences that have the same cellular barcode and UMI  UMIs that have the same cellular barcode and scar sequence  and cellular barcodes that have the same UMI and scar sequence. In each step  we kept only the molecule with the highest number of reads. The rationale behind this is that it is very improbable to have two valid scar sequences in the same cell with the same UMI  or to have a scar sequence with the same UMI appear in two different cells. The observation of two different UMIs for the same scar in the same cell is much more likely and corresponds to detection of multiple transcripts from the same locus  but information about scar expression levels was not required in our downstream analysis. In the third filtering step  we specifically targeted sequencing errors within each cell. We compared the scar sequences found within a cell to each other. We filtered out sequences that had a Hamming distance of 2 or less to another scar sequence in the same cell that occurred in at least eight times as many reads. Scar sequences in the same cell that were one Hamming distance apart but had a read ratio less than eight were tested on three criteria if both of them occurred at least twice in the scar library: Do both scars have more than one transcript?  Do both scars occur in cells independently from each other?  Do the UMIs of both scars have Hamming distance of two or more? If two of these criteria were true  the scars were kept and the sequences were placed on a list of validated scars that  if they occurred in the same cell in another library  did not have to be tested anymore. If one or zero criteria were true  the scar that had only one transcript  or the scar that did not occur independently  were filtered out. In the fourth filtering step  we determined the distribution of reads for the scars we had kept so far. Based on this distribution  we set a cut off and filtered out the scars that did not have at least this number of reads. Finally  for each cell type  we determined the distribution of different scars seen per cell and set a maximum number of scars a cell of that type can have. We filtered out cells in which we observed more than this maximum number as possible doublets. Genome build: N/A Supplementary files format and content: List of scar transcripts with cell barcode  scar name  cell type  scar probability and number of organisms that have this cell.", "Pancreas and liver", null, "Single cell dissociation. 10X Genomics Chromium", null, "strain/background:Zebrabow M|tissue:Pancreas and liver|developmental stage:Adult", "GSM2830054", "GSM2830054: Pancreas 2 scar; Danio rerio; OTHER", "GSM2830054", null, "1", "Single cell dissociation. 10X Genomics Chromium", "GEO Accession:GSM2830054", "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP121343", null, null, "P6_scar_R1.fastq.gz P6_scar_R2.fastq.gz", "fastq fastq", 1026715860.0, 7439970.0, "GSM2830054 r1", "0:28 1:110", "A:287816843;C:320879355;G:243598630;T:174359452;N:61580", 28, 110, null, null, 287816843, 320879355, 243598630, 174359452, 61580, "SRX3320758", "SRS2626348", "SRA623333", "GEO", "Max Delbr\u00fcck Center", 2, 0.00029, 0.00123, 0.00028, 6e-05, 1.0, 0.99914, null, 0.25714, 28, 110, "T", "T", "mates < 9% mapping rate", "illumina", "nextseq", "unknown", "other", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2017-10-24", "Adult", "Adult", "Multi-tissue", "Multi-system"], [44010, "SRR6211482", "SRX3320757", "SRS2626331", "SRP121343", "PRJNA415636", "Simultaneous lineage tracing and cell type identification using CRISPR/Cas9 induced genetic scars", "GSE106121", "Other", "A key goal of developmental biology is to understand how a single cell transforms into a full grown organism consisting of many different cell types. Single cell RNA sequencing scRNA seq has become a widely used method due to its ability to identify all cell types in a tissue or organ in a systematic manner. However  a major challenge is to organize the resulting taxonomy of cell types into lineage trees revealing the developmental origin of cells. Here  we present a strategy for simultaneous lineage tracing and transcriptome profiling in thousands of single cells. By combining scRNA seq with computational analysis of lineage barcodes generated by genome editing of transgenic reporter genes  we reconstruct developmental lineage trees in zebrafish larvae and adult fish. In future analyses  LINNAEUS LINeage tracing by Nuclease Activated Editing of Ubiquitous Sequences can be used as a systematic approach for identifying the lineage origin of novel cell types  or of known cell types under different conditions. Overall design: Combining scRNA seq with computational analysis of lineage barcodes generated by genome editing of transgenic reporter genes.", null, "pubmed:29644996", null, "Heart 1 scar", "GSM2830053", null, "source name:Heart and blood|strain/background:Zebrabow M|tissue:Heart and blood|developmental stage:Adult", "Heart 1 scar", "Library strategy: Targeted amplification Scar reads have the same structure as transcript reads: they consist of a barcode  a UMI and a scar. The scar sequences were aligned using bwa mem6 to a reference of RFP. We defined a cell as a barcode with at least 500 reads. We removed reads that were unmapped  had an incorrect barcode  or did not start with the exact PCR primer we used. We truncated all scar sequences to 75 nucleotides and filtered out shorter sequences. To correct for sequencing errors  we implemented several rounds of scar filtering Supplementary Fig. 2 in publication. We started by counting the number of times each molecule was sequenced. Sequencing errors will typically have fewer reads than the actual scars they originate from. As a first filtering step  we therefore removed all molecules only seen once to reduce the complexity in the dataset for consecutive filtering steps. In the second filtering step  we aimed to remove easily recognizable sequencing errors. To this end  we consecutively considered scar sequences that have the same cellular barcode and UMI  UMIs that have the same cellular barcode and scar sequence  and cellular barcodes that have the same UMI and scar sequence. In each step  we kept only the molecule with the highest number of reads. The rationale behind this is that it is very improbable to have two valid scar sequences in the same cell with the same UMI  or to have a scar sequence with the same UMI appear in two different cells. The observation of two different UMIs for the same scar in the same cell is much more likely and corresponds to detection of multiple transcripts from the same locus  but information about scar expression levels was not required in our downstream analysis. In the third filtering step  we specifically targeted sequencing errors within each cell. We compared the scar sequences found within a cell to each other. We filtered out sequences that had a Hamming distance of 2 or less to another scar sequence in the same cell that occurred in at least eight times as many reads. Scar sequences in the same cell that were one Hamming distance apart but had a read ratio less than eight were tested on three criteria if both of them occurred at least twice in the scar library: Do both scars have more than one transcript?  Do both scars occur in cells independently from each other?  Do the UMIs of both scars have Hamming distance of two or more? If two of these criteria were true  the scars were kept and the sequences were placed on a list of validated scars that  if they occurred in the same cell in another library  did not have to be tested anymore. If one or zero criteria were true  the scar that had only one transcript  or the scar that did not occur independently  were filtered out. In the fourth filtering step  we determined the distribution of reads for the scars we had kept so far. Based on this distribution  we set a cut off and filtered out the scars that did not have at least this number of reads. Finally  for each cell type  we determined the distribution of different scars seen per cell and set a maximum number of scars a cell of that type can have. We filtered out cells in which we observed more than this maximum number as possible doublets. Genome build: N/A Supplementary files format and content: List of scar transcripts with cell barcode  scar name  cell type  scar probability and number of organisms that have this cell.", "Heart and blood", null, "Single cell dissociation. 10X Genomics Chromium", null, "strain/background:Zebrabow M|tissue:Heart and blood|developmental stage:Adult", "GSM2830053", "GSM2830053: Heart 1 scar; Danio rerio; OTHER", "GSM2830053", null, "1", "Single cell dissociation. 10X Genomics Chromium", "GEO Accession:GSM2830053", "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP121343", null, null, "H5_scar_R1.fastq.gz H5_scar_R2.fastq.gz", "fastq fastq", 1287546624.0, 10218624.0, "GSM2830053 r1", "0:26 1:100", "A:365272675;C:413037677;G:296495693;T:212570153;N:170426", 26, 100, null, null, 365272675, 413037677, 296495693, 212570153, 170426, "SRX3320757", "SRS2626331", "SRA623333", "GEO", "Max Delbr\u00fcck Center", 2, 0.00023, 0.00044, 0.00022, 3e-05, 1.0, 0.99955, null, 0.32653, 26, 100, "T", "T", "mates < 9% mapping rate", "illumina", "nextseq", "unknown", "other", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2017-10-24", "Adult", "Adult", "Multi-tissue", "Multi-system"], [44011, "SRR6211481", "SRX3320756", "SRS2626330", "SRP121343", "PRJNA415636", "Simultaneous lineage tracing and cell type identification using CRISPR/Cas9 induced genetic scars", "GSE106121", "Other", "A key goal of developmental biology is to understand how a single cell transforms into a full grown organism consisting of many different cell types. Single cell RNA sequencing scRNA seq has become a widely used method due to its ability to identify all cell types in a tissue or organ in a systematic manner. However  a major challenge is to organize the resulting taxonomy of cell types into lineage trees revealing the developmental origin of cells. Here  we present a strategy for simultaneous lineage tracing and transcriptome profiling in thousands of single cells. By combining scRNA seq with computational analysis of lineage barcodes generated by genome editing of transgenic reporter genes  we reconstruct developmental lineage trees in zebrafish larvae and adult fish. In future analyses  LINNAEUS LINeage tracing by Nuclease Activated Editing of Ubiquitous Sequences can be used as a systematic approach for identifying the lineage origin of novel cell types  or of known cell types under different conditions. Overall design: Combining scRNA seq with computational analysis of lineage barcodes generated by genome editing of transgenic reporter genes.", null, "pubmed:29644996", null, "Brain 1 scar", "GSM2830052", null, "source name:Brain|strain/background:Zebrabow M|tissue:Brain|developmental stage:Adult", "Brain 1 scar", "Library strategy: Targeted amplification Scar reads have the same structure as transcript reads: they consist of a barcode  a UMI and a scar. The scar sequences were aligned using bwa mem6 to a reference of RFP. We defined a cell as a barcode with at least 500 reads. We removed reads that were unmapped  had an incorrect barcode  or did not start with the exact PCR primer we used. We truncated all scar sequences to 75 nucleotides and filtered out shorter sequences. To correct for sequencing errors  we implemented several rounds of scar filtering Supplementary Fig. 2 in publication. We started by counting the number of times each molecule was sequenced. Sequencing errors will typically have fewer reads than the actual scars they originate from. As a first filtering step  we therefore removed all molecules only seen once to reduce the complexity in the dataset for consecutive filtering steps. In the second filtering step  we aimed to remove easily recognizable sequencing errors. To this end  we consecutively considered scar sequences that have the same cellular barcode and UMI  UMIs that have the same cellular barcode and scar sequence  and cellular barcodes that have the same UMI and scar sequence. In each step  we kept only the molecule with the highest number of reads. The rationale behind this is that it is very improbable to have two valid scar sequences in the same cell with the same UMI  or to have a scar sequence with the same UMI appear in two different cells. The observation of two different UMIs for the same scar in the same cell is much more likely and corresponds to detection of multiple transcripts from the same locus  but information about scar expression levels was not required in our downstream analysis. In the third filtering step  we specifically targeted sequencing errors within each cell. We compared the scar sequences found within a cell to each other. We filtered out sequences that had a Hamming distance of 2 or less to another scar sequence in the same cell that occurred in at least eight times as many reads. Scar sequences in the same cell that were one Hamming distance apart but had a read ratio less than eight were tested on three criteria if both of them occurred at least twice in the scar library: Do both scars have more than one transcript?  Do both scars occur in cells independently from each other?  Do the UMIs of both scars have Hamming distance of two or more? If two of these criteria were true  the scars were kept and the sequences were placed on a list of validated scars that  if they occurred in the same cell in another library  did not have to be tested anymore. If one or zero criteria were true  the scar that had only one transcript  or the scar that did not occur independently  were filtered out. In the fourth filtering step  we determined the distribution of reads for the scars we had kept so far. Based on this distribution  we set a cut off and filtered out the scars that did not have at least this number of reads. Finally  for each cell type  we determined the distribution of different scars seen per cell and set a maximum number of scars a cell of that type can have. We filtered out cells in which we observed more than this maximum number as possible doublets. Genome build: N/A Supplementary files format and content: List of scar transcripts with cell barcode  scar name  cell type  scar probability and number of organisms that have this cell.", "Brain", null, "Single cell dissociation. 10X Genomics Chromium", null, "strain/background:Zebrabow M|tissue:Brain|developmental stage:Adult", "GSM2830052", "GSM2830052: Brain 1 scar; Danio rerio; OTHER", "GSM2830052", null, "1", "Single cell dissociation. 10X Genomics Chromium", "GEO Accession:GSM2830052", "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP121343", null, null, "B5_scar_R1.fastq.gz B5_scar_R2.fastq.gz", "fastq fastq", 438883452.0, 3483202.0, "GSM2830052 r1", "0:26 1:100", "A:125829044;C:139532010;G:100613706;T:72846911;N:61781", 26, 100, null, null, 125829044, 139532010, 100613706, 72846911, 61781, "SRX3320756", "SRS2626330", "SRA623333", "GEO", "Max Delbr\u00fcck Center", 2, 0.00072, 0.0013, 0.00069, 0.00011, 0.99991, 0.99878, 0.75, 0.36879, 26, 100, "T", "T", "mates < 9% mapping rate", "illumina", "nextseq", "unknown", "other", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2017-10-24", "Adult", "Adult", "Brain", "Nervous System"], [44012, "SRR6211480", "SRX3320755", "SRS2626329", "SRP121343", "PRJNA415636", "Simultaneous lineage tracing and cell type identification using CRISPR/Cas9 induced genetic scars", "GSE106121", "Other", "A key goal of developmental biology is to understand how a single cell transforms into a full grown organism consisting of many different cell types. Single cell RNA sequencing scRNA seq has become a widely used method due to its ability to identify all cell types in a tissue or organ in a systematic manner. However  a major challenge is to organize the resulting taxonomy of cell types into lineage trees revealing the developmental origin of cells. Here  we present a strategy for simultaneous lineage tracing and transcriptome profiling in thousands of single cells. By combining scRNA seq with computational analysis of lineage barcodes generated by genome editing of transgenic reporter genes  we reconstruct developmental lineage trees in zebrafish larvae and adult fish. In future analyses  LINNAEUS LINeage tracing by Nuclease Activated Editing of Ubiquitous Sequences can be used as a systematic approach for identifying the lineage origin of novel cell types  or of known cell types under different conditions. Overall design: Combining scRNA seq with computational analysis of lineage barcodes generated by genome editing of transgenic reporter genes.", null, "pubmed:29644996", null, "Pancreas 1 scar", "GSM2830051", null, "source name:Pancreas and liver|strain/background:Zebrabow M|tissue:Pancreas and liver|developmental stage:Adult", "Pancreas 1 scar", "Library strategy: Targeted amplification Scar reads have the same structure as transcript reads: they consist of a barcode  a UMI and a scar. The scar sequences were aligned using bwa mem6 to a reference of RFP. We defined a cell as a barcode with at least 500 reads. We removed reads that were unmapped  had an incorrect barcode  or did not start with the exact PCR primer we used. We truncated all scar sequences to 75 nucleotides and filtered out shorter sequences. To correct for sequencing errors  we implemented several rounds of scar filtering Supplementary Fig. 2 in publication. We started by counting the number of times each molecule was sequenced. Sequencing errors will typically have fewer reads than the actual scars they originate from. As a first filtering step  we therefore removed all molecules only seen once to reduce the complexity in the dataset for consecutive filtering steps. In the second filtering step  we aimed to remove easily recognizable sequencing errors. To this end  we consecutively considered scar sequences that have the same cellular barcode and UMI  UMIs that have the same cellular barcode and scar sequence  and cellular barcodes that have the same UMI and scar sequence. In each step  we kept only the molecule with the highest number of reads. The rationale behind this is that it is very improbable to have two valid scar sequences in the same cell with the same UMI  or to have a scar sequence with the same UMI appear in two different cells. The observation of two different UMIs for the same scar in the same cell is much more likely and corresponds to detection of multiple transcripts from the same locus  but information about scar expression levels was not required in our downstream analysis. In the third filtering step  we specifically targeted sequencing errors within each cell. We compared the scar sequences found within a cell to each other. We filtered out sequences that had a Hamming distance of 2 or less to another scar sequence in the same cell that occurred in at least eight times as many reads. Scar sequences in the same cell that were one Hamming distance apart but had a read ratio less than eight were tested on three criteria if both of them occurred at least twice in the scar library: Do both scars have more than one transcript?  Do both scars occur in cells independently from each other?  Do the UMIs of both scars have Hamming distance of two or more? If two of these criteria were true  the scars were kept and the sequences were placed on a list of validated scars that  if they occurred in the same cell in another library  did not have to be tested anymore. If one or zero criteria were true  the scar that had only one transcript  or the scar that did not occur independently  were filtered out. In the fourth filtering step  we determined the distribution of reads for the scars we had kept so far. Based on this distribution  we set a cut off and filtered out the scars that did not have at least this number of reads. Finally  for each cell type  we determined the distribution of different scars seen per cell and set a maximum number of scars a cell of that type can have. We filtered out cells in which we observed more than this maximum number as possible doublets. Genome build: N/A Supplementary files format and content: List of scar transcripts with cell barcode  scar name  cell type  scar probability and number of organisms that have this cell.", "Pancreas and liver", null, "Single cell dissociation. 10X Genomics Chromium", null, "strain/background:Zebrabow M|tissue:Pancreas and liver|developmental stage:Adult", "GSM2830051", "GSM2830051: Pancreas 1 scar; Danio rerio; OTHER", "GSM2830051", null, "1", "Single cell dissociation. 10X Genomics Chromium", "GEO Accession:GSM2830051", "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP121343", null, null, "P5_scar_R1.fastq.gz P5_scar_R2.fastq.gz", "fastq fastq", 1192602600.0, 9465100.0, "GSM2830051 r1", "0:26 1:100", "A:346841760;C:383266222;G:268916933;T:193424756;N:152929", 26, 100, null, null, 346841760, 383266222, 268916933, 193424756, 152929, "SRX3320755", "SRS2626329", "SRA623333", "GEO", "Max Delbr\u00fcck Center", 2, 0.00021, 0.00091, 0.00014, 2e-05, 0.99997, 0.99892, 0.0, 0.23931, 26, 100, "T", "T", "mates < 9% mapping rate", "illumina", "nextseq", "unknown", "other", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2017-10-24", "Adult", "Adult", "Multi-tissue", "Multi-system"], [59501, "SRR11924323", "SRX8469995", "SRS6770646", "SRP265951", "PRJNA637293", "The shift from early to late types of ribosomes in zebrafish development involves changes at a subset of rRNA 2' O Me sites", "GSE151797", "Other", "A sequencing based profiling method RiboMeth seq for ribose methylations was used to study methylation patterns during Zebrafish Danio rerio development Overall design: All samples were analyzed in biological triplicates  except for adult tail trunk that was in duplicate.", null, "pubmed:32912962", null, "Adult tail 2", "GSM4591062", null, "source name:adult tail trunk|tissue:adult tail trunk|rna fraction:size fractionated 20 40 nt whole cell RNA", "Adult tail 2", "Library strategy: RiboMeth seq Barcode separation using python script Adaptor trimming using Cutadapt v. 2.0 Mapping to rRNA reference sequence using Bowtie2 v. 2.3.4.1 Counting read ends and calculating RiboMeth seq scores using python scripts The output FASTA files from small RNA seq were merged and used as the basis of the SNORD search and rRNA interaction prediction. Initially  SNORDs were identified by running the merged FASTA file through snoScan Schattner et al. 2005 against zebrafish early  and late rRNA reference sequences Locati et al. 2017. Genome build: early and late zebrafish rRNA locati et al. The reference sequences are available in the FASTA file on the series record. Supplementary files format and content: MS Excel file contains five prime and three prime read count and calculated RiboMeth seq score at all positions in the rRNA sequence.", "adult tail trunk", null, "Tissues were homogenized and whole cell RNA was extracted using Qiazol Qiagen according to the manufacturer. RiboMeth seq: 5 10 ug of RNA was partially degraded by alkaline at denaturing temperatures. The size fraction 20 40 nt was purified on gels and linkers added using a system relying on a modified Arabidopsis tRNA ligase joining 2' three prime cyclic phosphate and five prime phosphate ends. The library fragments were then sequenced on the Ion Proton platform. See Birkedal U  Christensen Dalsgaard M  Krogh N  Sabarinathan R  Gorodkin J  Nielsen H. Profiling of ribose methylations in RNA by high throughput sequencing. Angewandte Chemie. 2015;542:451 5 for detailed description", null, "tissue:adult tail trunk|rna fraction:size fractionated 20 40 nt whole cell RNA", "GSM4591062", "GSM4591062: Adult tail 2; Danio rerio; OTHER", "GSM4591062", null, "1", "Tissues were homogenized and whole cell RNA was extracted using Qiazol Qiagen according to the manufacturer. RiboMeth seq: 5 10 ug of RNA was partially degraded by alkaline at denaturing temperatures. The size fraction 20 40 nt was purified on gels and linkers added using a system relying on a modified Arabidopsis tRNA ligase joining 2' three prime cyclic phosphate and five prime phosphate ends. The library fragments were then sequenced on the Ion Proton platform. See Birkedal U  Christensen Dalsgaard M  Krogh N  Sabarinathan R  Gorodkin J  Nielsen H. Profiling of ribose methylations in RNA by high throughput sequencing. Angewandte Chemie. 2015;542:451 5 for detailed description", "GEO Accession:GSM4591062", "OTHER", "TRANSCRIPTOMIC", "other", "SINGLE", "ION_TORRENT", "Ion Torrent Proton", null, "SRP265951", null, "intentional duplicate", "Adult_tail_2.bam GSE151797_Reference_sequence.fa", "bam bam", 156647953.0, 5517527.0, "GSM4591062 r1", "0:28.39", "A:32903673;C:49609293;G:39096775;T:35038212;N:0", 28, null, null, null, 32903673, 49609293, 39096775, 35038212, 0, "SRX8469995", "SRS6770646", "SRA1083099", "GEO", "RNA Group - Prof. Henrik Nielsen, Department of Cellular and Molecular Medicine, University of Copenhagen", 1, 0.80662, null, 0.20653, null, 0.88722, null, 0.58074, null, 37, null, "B", null, "usable mapping rate", "ion_torrent", "ion_torrent", "5prime", "small_rna", "unknown", "bulk", "unknown", "unknown", null, "Denmark", "2020-06-04", "Adult", "Adult", "Multi-tissue", "Multi-system"], [59502, "SRR11924321", "SRX8469994", "SRS6770645", "SRP265951", "PRJNA637293", "The shift from early to late types of ribosomes in zebrafish development involves changes at a subset of rRNA 2' O Me sites", "GSE151797", "Other", "A sequencing based profiling method RiboMeth seq for ribose methylations was used to study methylation patterns during Zebrafish Danio rerio development Overall design: All samples were analyzed in biological triplicates  except for adult tail trunk that was in duplicate.", null, "pubmed:32912962", null, "Adult tail 1", "GSM4591061", null, "source name:adult tail trunk|tissue:adult tail trunk|rna fraction:size fractionated 20 40 nt whole cell RNA", "Adult tail 1", "Library strategy: RiboMeth seq Barcode separation using python script Adaptor trimming using Cutadapt v. 2.0 Mapping to rRNA reference sequence using Bowtie2 v. 2.3.4.1 Counting read ends and calculating RiboMeth seq scores using python scripts The output FASTA files from small RNA seq were merged and used as the basis of the SNORD search and rRNA interaction prediction. Initially  SNORDs were identified by running the merged FASTA file through snoScan Schattner et al. 2005 against zebrafish early  and late rRNA reference sequences Locati et al. 2017. Genome build: early and late zebrafish rRNA locati et al. The reference sequences are available in the FASTA file on the series record. Supplementary files format and content: MS Excel file contains five prime and three prime read count and calculated RiboMeth seq score at all positions in the rRNA sequence.", "adult tail trunk", null, "Tissues were homogenized and whole cell RNA was extracted using Qiazol Qiagen according to the manufacturer. RiboMeth seq: 5 10 ug of RNA was partially degraded by alkaline at denaturing temperatures. The size fraction 20 40 nt was purified on gels and linkers added using a system relying on a modified Arabidopsis tRNA ligase joining 2' three prime cyclic phosphate and five prime phosphate ends. The library fragments were then sequenced on the Ion Proton platform. See Birkedal U  Christensen Dalsgaard M  Krogh N  Sabarinathan R  Gorodkin J  Nielsen H. Profiling of ribose methylations in RNA by high throughput sequencing. Angewandte Chemie. 2015;542:451 5 for detailed description", null, "tissue:adult tail trunk|rna fraction:size fractionated 20 40 nt whole cell RNA", "GSM4591061", "GSM4591061: Adult tail 1; Danio rerio; OTHER", "GSM4591061", null, "1", "Tissues were homogenized and whole cell RNA was extracted using Qiazol Qiagen according to the manufacturer. RiboMeth seq: 5 10 ug of RNA was partially degraded by alkaline at denaturing temperatures. The size fraction 20 40 nt was purified on gels and linkers added using a system relying on a modified Arabidopsis tRNA ligase joining 2' three prime cyclic phosphate and five prime phosphate ends. The library fragments were then sequenced on the Ion Proton platform. See Birkedal U  Christensen Dalsgaard M  Krogh N  Sabarinathan R  Gorodkin J  Nielsen H. Profiling of ribose methylations in RNA by high throughput sequencing. Angewandte Chemie. 2015;542:451 5 for detailed description", "GEO Accession:GSM4591061", "OTHER", "TRANSCRIPTOMIC", "other", "SINGLE", "ION_TORRENT", "Ion Torrent Proton", null, "SRP265951", null, "intentional duplicate", "Adult_tail_1.bam GSE151797_Reference_sequence.fa", "bam bam", 50029636.0, 1968329.0, "GSM4591061 r1", "0:25.42", "A:9571393;C:14825016;G:13276309;T:12356918;N:0", 25, null, null, null, 9571393, 14825016, 13276309, 12356918, 0, "SRX8469994", "SRS6770645", "SRA1083099", "GEO", "RNA Group - Prof. Henrik Nielsen, Department of Cellular and Molecular Medicine, University of Copenhagen", 1, 0.46312, null, 0.12127, null, 0.91806, null, 0.67424, null, 44, null, "B", null, "usable mapping rate", "ion_torrent", "ion_torrent", "5prime", "small_rna", "unknown", "bulk", "unknown", "unknown", null, "Denmark", "2020-06-04", "Adult", "Adult", "Multi-tissue", "Multi-system"], [68382, "SRR17720609", "SRX13883476", "SRS11752245", "SRP356476", "PRJNA800053", "Mapping the m1A  m5C  m6A and m7G Methylation Atlas in Zebrafish Brains under Hypoxic Conditions by MeRIP seq", "GSE194284", "Other", "The epigenetic modifications play important regulatory roles in tissue development  maintenance of physiological functions and pathological process. RNA methylations  including newly identified m1A  m5C  m6A and m7G  are important epigenetic modifications. However  how these modifications are distributed in the transcriptome of vertebrate brains and whether their abundance is altered under pathological conditions are still poorly understood. In this study  we chose the model animal of zebrafish to conduct a systematic study to investigate the mRNA methylation atlas in the brain. By performing unbiased analyses of the m1A  m5C  m6A and m7G methylation of mRNA  we found that within the whole brain transcriptome  with the increase of the gene expression levels  the overall level of each of these four modifications on the related genes was also progressively increased. Further bioinformatics analysis indicated that the zebrafish brain has an abundance of m1A modifications. In the hypoxia treated zebrafish brains  the proportion of m1A is decreased  affecting the RNA splicing and zebrafish endogenous retroviruses. Our study presents the first comprehensive atlas of m1A  m5C  m6A and m7G in the epitranscriptome of the zebrafish brain and reveals the distribution of these modifications in mRNA under hypoxic conditions. These data provide an invaluable resource for further research on the involvement of m1A  m5C  m6A and m7G in the regulation of miRNA and repeat elements in vertebrates  and provide new thoughts to study the brain hypoxic injury on the aspect of epitranscriptome. Overall design: For each normoxia control and hypoxia experimental group  10 adult male zebrafish 3 mpf 4 mpf were chosen for the analyses. Three repeats of each experiment were performed and totally 30 fishes per group were collected. The brain tissues around 0.02 g per brain were then stored for further analysis in liquid nitrogen. For each analysis m1A  m5C  m6A  m7G and RNA Seq  the normoxia group and hypoxic group each consisted of 30 mixed brain tissues were analyzed parallelly by RNA seq and MeRIP Seq.", null, "pubmed:35135476", null, "m7G Normoxia IP", "GSM5832287", null, "source name:zebrafish brain tissue|tissue:brain", "m7G Normoxia IP", "Paired end reads were harvested from an Illumina NovaSeq 6000 sequencer Cutadapt v1.9.3  command line software  was used to identify and trim 3\u2019 adapter and low quality bases for rawdata. The clean data were mapped to the reference genome GRCz11 using Hisat2 software v2.0.4. For RNA seq: Guiding by the Ensembl GTF gene annotation file  Cuffdiff software part of cufflinks was used to obtain the gene level FPKM as the expression profiles of mRNA  fold change and p value were calculated based on FPKM For MeRIP seq: To identify the methylated sites on RNAs peaks  MACS software was utilized. Differentially methylated sites were identified by diffReps. The motif predictions of MeRIP Seq data were performed by utilizing a Perl script  findMotifGenome.pl  from HOMER software. Genome build: GRCz11 Supplementary files format and content: Gene expression valuesFPKM and Counts and methylated sites", "zebrafish brain tissue", "Adult wild type zebrafish Danio rerio were bred according to standard methods. For hypoxia treatment  we followed settings established in a previously published protocolYu et al 2011 with modified conditions. Briefly  zebrafish were transferred into a 1 L chamber containing 800 mL predeoxidated water O2: 0.3 0.4 mg/L. Oxygen in the water was then exhausted through the application of 8 L/min nitrogen until the dissolved oxygen value in the water was approximately 0.4 0.6 mg/L. Nitrogen 1 L/min was used to maintain the dissolved oxygen level in the water. post approximately 5 minutes  when the fish became motionless  the zebrafish brain were dissected on ice post anesthetizing to obtain brain tissues. The brain tissues were stored for further analysis in liquid nitrogen.", "Ribo Zero rRNA Removal Kits Illumina  San Diego  CA  USA For RNA seq : TruSeq Stranded Total RNA Library Prep Kit Illumina  San Diego  CA  USA For MeRIP seq: GenSeqTM RNA IP Kit GenSeq Inc.  China and NEBNext\u00ae Ultra II Directional RNA Library Prep Kit New England Biolabs  Inc.  USA RNA seq and MeRIP seq", null, "tissue:brain", "GSM5832287", "GSM5832287: m7G Normoxia IP; Danio rerio; OTHER", "GSM5832287 r1", "GSM5832287", "1", "Ribo Zero rRNA Removal Kits Illumina  San Diego  CA  USA For RNA seq : TruSeq Stranded Total RNA Library Prep Kit Illumina  San Diego  CA  USA For MeRIP seq: GenSeqTM RNA IP Kit GenSeq Inc.  China and NEBNext\u00ae Ultra II Directional RNA Library Prep Kit New England Biolabs  Inc.  USA RNA seq and MeRIP seq", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP356476", null, "loader:fastq load.py", "m7G_Normoxia_IP_R1.fastq.gz m7G_Normoxia_IP_R2.fastq.gz", "fastq fastq", 6634104000.0, 22113680.0, "GSM5832287 r1", "0:150 1:150", "A:1396464650;C:1688319426;G:2250091870;T:1299109891;N:118163", 150, 150, null, null, 1396464650, 1688319426, 2250091870, 1299109891, 118163, "SRX13883476", "SRS11752245", "SRA1361294", "Affiliated Hospital of Guangdong Medical University", "Affiliated Hospital of Guangdong Medical University", 2, 0.9266, 0.92801, 0.07275, 0.06866, 0.89964, 0.90601, 0.65995, 0.75535, 150, 150, "B", "B", "biological fallback assumption", "illumina", "novaseq_era", "full_length", "rrna_depletion", "nebnext", "bulk", "bulk", "bulk", null, "China", "2022-01-24", "Adult", "Adult", "Brain", "Nervous System"], [68383, "SRR17720610", "SRX13883475", "SRS11752244", "SRP356476", "PRJNA800053", "Mapping the m1A  m5C  m6A and m7G Methylation Atlas in Zebrafish Brains under Hypoxic Conditions by MeRIP seq", "GSE194284", "Other", "The epigenetic modifications play important regulatory roles in tissue development  maintenance of physiological functions and pathological process. RNA methylations  including newly identified m1A  m5C  m6A and m7G  are important epigenetic modifications. However  how these modifications are distributed in the transcriptome of vertebrate brains and whether their abundance is altered under pathological conditions are still poorly understood. In this study  we chose the model animal of zebrafish to conduct a systematic study to investigate the mRNA methylation atlas in the brain. By performing unbiased analyses of the m1A  m5C  m6A and m7G methylation of mRNA  we found that within the whole brain transcriptome  with the increase of the gene expression levels  the overall level of each of these four modifications on the related genes was also progressively increased. Further bioinformatics analysis indicated that the zebrafish brain has an abundance of m1A modifications. In the hypoxia treated zebrafish brains  the proportion of m1A is decreased  affecting the RNA splicing and zebrafish endogenous retroviruses. Our study presents the first comprehensive atlas of m1A  m5C  m6A and m7G in the epitranscriptome of the zebrafish brain and reveals the distribution of these modifications in mRNA under hypoxic conditions. These data provide an invaluable resource for further research on the involvement of m1A  m5C  m6A and m7G in the regulation of miRNA and repeat elements in vertebrates  and provide new thoughts to study the brain hypoxic injury on the aspect of epitranscriptome. Overall design: For each normoxia control and hypoxia experimental group  10 adult male zebrafish 3 mpf 4 mpf were chosen for the analyses. Three repeats of each experiment were performed and totally 30 fishes per group were collected. The brain tissues around 0.02 g per brain were then stored for further analysis in liquid nitrogen. For each analysis m1A  m5C  m6A  m7G and RNA Seq  the normoxia group and hypoxic group each consisted of 30 mixed brain tissues were analyzed parallelly by RNA seq and MeRIP Seq.", null, "pubmed:35135476", null, "m7G Normoxia Input", "GSM5832286", null, "source name:zebrafish brain tissue|tissue:brain", "m7G Normoxia Input", "Paired end reads were harvested from an Illumina NovaSeq 6000 sequencer Cutadapt v1.9.3  command line software  was used to identify and trim 3\u2019 adapter and low quality bases for rawdata. The clean data were mapped to the reference genome GRCz11 using Hisat2 software v2.0.4. For RNA seq: Guiding by the Ensembl GTF gene annotation file  Cuffdiff software part of cufflinks was used to obtain the gene level FPKM as the expression profiles of mRNA  fold change and p value were calculated based on FPKM For MeRIP seq: To identify the methylated sites on RNAs peaks  MACS software was utilized. Differentially methylated sites were identified by diffReps. The motif predictions of MeRIP Seq data were performed by utilizing a Perl script  findMotifGenome.pl  from HOMER software. Genome build: GRCz11 Supplementary files format and content: Gene expression valuesFPKM and Counts and methylated sites", "zebrafish brain tissue", "Adult wild type zebrafish Danio rerio were bred according to standard methods. For hypoxia treatment  we followed settings established in a previously published protocolYu et al 2011 with modified conditions. Briefly  zebrafish were transferred into a 1 L chamber containing 800 mL predeoxidated water O2: 0.3 0.4 mg/L. Oxygen in the water was then exhausted through the application of 8 L/min nitrogen until the dissolved oxygen value in the water was approximately 0.4 0.6 mg/L. Nitrogen 1 L/min was used to maintain the dissolved oxygen level in the water. post approximately 5 minutes  when the fish became motionless  the zebrafish brain were dissected on ice post anesthetizing to obtain brain tissues. The brain tissues were stored for further analysis in liquid nitrogen.", "Ribo Zero rRNA Removal Kits Illumina  San Diego  CA  USA For RNA seq : TruSeq Stranded Total RNA Library Prep Kit Illumina  San Diego  CA  USA For MeRIP seq: GenSeqTM RNA IP Kit GenSeq Inc.  China and NEBNext\u00ae Ultra II Directional RNA Library Prep Kit New England Biolabs  Inc.  USA RNA seq and MeRIP seq", null, "tissue:brain", "GSM5832286", "GSM5832286: m7G Normoxia Input; Danio rerio; OTHER", "GSM5832286 r1", "GSM5832286", "1", "Ribo Zero rRNA Removal Kits Illumina  San Diego  CA  USA For RNA seq : TruSeq Stranded Total RNA Library Prep Kit Illumina  San Diego  CA  USA For MeRIP seq: GenSeqTM RNA IP Kit GenSeq Inc.  China and NEBNext\u00ae Ultra II Directional RNA Library Prep Kit New England Biolabs  Inc.  USA RNA seq and MeRIP seq", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP356476", null, "loader:fastq load.py", "m7G_Normoxia_Input_R1.fastq.gz m7G_Normoxia_Input_R2.fastq.gz", "fastq fastq", 6839977800.0, 22799926.0, "GSM5832286 r1", "0:150 1:150", "A:1986780958;C:1411210049;G:1509902094;T:1932043482;N:41217", 150, 150, null, null, 1986780958, 1411210049, 1509902094, 1932043482, 41217, "SRX13883475", "SRS11752244", "SRA1361294", "Affiliated Hospital of Guangdong Medical University", "Affiliated Hospital of Guangdong Medical University", 2, 0.89709, 0.89888, 0.21747, 0.21725, 0.70021, 0.69936, 0.50469, 0.51865, 150, 150, "B", "B", "biological fallback assumption", "illumina", "novaseq_era", "full_length", "rrna_depletion", "nebnext", "bulk", "bulk", "bulk", null, "China", "2022-01-24", "Adult", "Adult", "Brain", "Nervous System"], [68384, "SRR17720611", "SRX13883474", "SRS11752243", "SRP356476", "PRJNA800053", "Mapping the m1A  m5C  m6A and m7G Methylation Atlas in Zebrafish Brains under Hypoxic Conditions by MeRIP seq", "GSE194284", "Other", "The epigenetic modifications play important regulatory roles in tissue development  maintenance of physiological functions and pathological process. RNA methylations  including newly identified m1A  m5C  m6A and m7G  are important epigenetic modifications. However  how these modifications are distributed in the transcriptome of vertebrate brains and whether their abundance is altered under pathological conditions are still poorly understood. In this study  we chose the model animal of zebrafish to conduct a systematic study to investigate the mRNA methylation atlas in the brain. By performing unbiased analyses of the m1A  m5C  m6A and m7G methylation of mRNA  we found that within the whole brain transcriptome  with the increase of the gene expression levels  the overall level of each of these four modifications on the related genes was also progressively increased. Further bioinformatics analysis indicated that the zebrafish brain has an abundance of m1A modifications. In the hypoxia treated zebrafish brains  the proportion of m1A is decreased  affecting the RNA splicing and zebrafish endogenous retroviruses. Our study presents the first comprehensive atlas of m1A  m5C  m6A and m7G in the epitranscriptome of the zebrafish brain and reveals the distribution of these modifications in mRNA under hypoxic conditions. These data provide an invaluable resource for further research on the involvement of m1A  m5C  m6A and m7G in the regulation of miRNA and repeat elements in vertebrates  and provide new thoughts to study the brain hypoxic injury on the aspect of epitranscriptome. Overall design: For each normoxia control and hypoxia experimental group  10 adult male zebrafish 3 mpf 4 mpf were chosen for the analyses. Three repeats of each experiment were performed and totally 30 fishes per group were collected. The brain tissues around 0.02 g per brain were then stored for further analysis in liquid nitrogen. For each analysis m1A  m5C  m6A  m7G and RNA Seq  the normoxia group and hypoxic group each consisted of 30 mixed brain tissues were analyzed parallelly by RNA seq and MeRIP Seq.", null, "pubmed:35135476", null, "m7G Hypoxia IP", "GSM5832285", null, "source name:zebrafish brain tissue|tissue:brain", "m7G Hypoxia IP", "Paired end reads were harvested from an Illumina NovaSeq 6000 sequencer Cutadapt v1.9.3  command line software  was used to identify and trim 3\u2019 adapter and low quality bases for rawdata. The clean data were mapped to the reference genome GRCz11 using Hisat2 software v2.0.4. For RNA seq: Guiding by the Ensembl GTF gene annotation file  Cuffdiff software part of cufflinks was used to obtain the gene level FPKM as the expression profiles of mRNA  fold change and p value were calculated based on FPKM For MeRIP seq: To identify the methylated sites on RNAs peaks  MACS software was utilized. Differentially methylated sites were identified by diffReps. The motif predictions of MeRIP Seq data were performed by utilizing a Perl script  findMotifGenome.pl  from HOMER software. Genome build: GRCz11 Supplementary files format and content: Gene expression valuesFPKM and Counts and methylated sites", "zebrafish brain tissue", "Adult wild type zebrafish Danio rerio were bred according to standard methods. For hypoxia treatment  we followed settings established in a previously published protocolYu et al 2011 with modified conditions. Briefly  zebrafish were transferred into a 1 L chamber containing 800 mL predeoxidated water O2: 0.3 0.4 mg/L. Oxygen in the water was then exhausted through the application of 8 L/min nitrogen until the dissolved oxygen value in the water was approximately 0.4 0.6 mg/L. Nitrogen 1 L/min was used to maintain the dissolved oxygen level in the water. post approximately 5 minutes  when the fish became motionless  the zebrafish brain were dissected on ice post anesthetizing to obtain brain tissues. The brain tissues were stored for further analysis in liquid nitrogen.", "Ribo Zero rRNA Removal Kits Illumina  San Diego  CA  USA For RNA seq : TruSeq Stranded Total RNA Library Prep Kit Illumina  San Diego  CA  USA For MeRIP seq: GenSeqTM RNA IP Kit GenSeq Inc.  China and NEBNext\u00ae Ultra II Directional RNA Library Prep Kit New England Biolabs  Inc.  USA RNA seq and MeRIP seq", null, "tissue:brain", "GSM5832285", "GSM5832285: m7G Hypoxia IP; Danio rerio; OTHER", "GSM5832285 r1", "GSM5832285", "1", "Ribo Zero rRNA Removal Kits Illumina  San Diego  CA  USA For RNA seq : TruSeq Stranded Total RNA Library Prep Kit Illumina  San Diego  CA  USA For MeRIP seq: GenSeqTM RNA IP Kit GenSeq Inc.  China and NEBNext\u00ae Ultra II Directional RNA Library Prep Kit New England Biolabs  Inc.  USA RNA seq and MeRIP seq", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP356476", null, "loader:fastq load.py", "m7G_Hypoxia_IP_R1.fastq.gz m7G_Hypoxia_IP_R2.fastq.gz", "fastq fastq", 7282575000.0, 24275250.0, "GSM5832285 r1", "0:150 1:150", "A:1512757767;C:1913587260;G:2472336371;T:1383764924;N:128678", 150, 150, null, null, 1512757767, 1913587260, 2472336371, 1383764924, 128678, "SRX13883474", "SRS11752243", "SRA1361294", "Affiliated Hospital of Guangdong Medical University", "Affiliated Hospital of Guangdong Medical University", 2, 0.94526, 0.9467, 0.05248, 0.05071, 0.91946, 0.91981, 0.69303, 0.78448, 150, 150, "B", "B", "biological fallback assumption", "illumina", "novaseq_era", "full_length", "rrna_depletion", "nebnext", "bulk", "bulk", "bulk", null, "China", "2022-01-24", "Adult", "Adult", "Brain", "Nervous System"], [68385, "SRR17720612", "SRX13883473", "SRS11752241", "SRP356476", "PRJNA800053", "Mapping the m1A  m5C  m6A and m7G Methylation Atlas in Zebrafish Brains under Hypoxic Conditions by MeRIP seq", "GSE194284", "Other", "The epigenetic modifications play important regulatory roles in tissue development  maintenance of physiological functions and pathological process. RNA methylations  including newly identified m1A  m5C  m6A and m7G  are important epigenetic modifications. However  how these modifications are distributed in the transcriptome of vertebrate brains and whether their abundance is altered under pathological conditions are still poorly understood. In this study  we chose the model animal of zebrafish to conduct a systematic study to investigate the mRNA methylation atlas in the brain. By performing unbiased analyses of the m1A  m5C  m6A and m7G methylation of mRNA  we found that within the whole brain transcriptome  with the increase of the gene expression levels  the overall level of each of these four modifications on the related genes was also progressively increased. Further bioinformatics analysis indicated that the zebrafish brain has an abundance of m1A modifications. In the hypoxia treated zebrafish brains  the proportion of m1A is decreased  affecting the RNA splicing and zebrafish endogenous retroviruses. Our study presents the first comprehensive atlas of m1A  m5C  m6A and m7G in the epitranscriptome of the zebrafish brain and reveals the distribution of these modifications in mRNA under hypoxic conditions. These data provide an invaluable resource for further research on the involvement of m1A  m5C  m6A and m7G in the regulation of miRNA and repeat elements in vertebrates  and provide new thoughts to study the brain hypoxic injury on the aspect of epitranscriptome. Overall design: For each normoxia control and hypoxia experimental group  10 adult male zebrafish 3 mpf 4 mpf were chosen for the analyses. Three repeats of each experiment were performed and totally 30 fishes per group were collected. The brain tissues around 0.02 g per brain were then stored for further analysis in liquid nitrogen. For each analysis m1A  m5C  m6A  m7G and RNA Seq  the normoxia group and hypoxic group each consisted of 30 mixed brain tissues were analyzed parallelly by RNA seq and MeRIP Seq.", null, "pubmed:35135476", null, "m7G Hypoxia Input", "GSM5832284", null, "source name:zebrafish brain tissue|tissue:brain", "m7G Hypoxia Input", "Paired end reads were harvested from an Illumina NovaSeq 6000 sequencer Cutadapt v1.9.3  command line software  was used to identify and trim 3\u2019 adapter and low quality bases for rawdata. The clean data were mapped to the reference genome GRCz11 using Hisat2 software v2.0.4. For RNA seq: Guiding by the Ensembl GTF gene annotation file  Cuffdiff software part of cufflinks was used to obtain the gene level FPKM as the expression profiles of mRNA  fold change and p value were calculated based on FPKM For MeRIP seq: To identify the methylated sites on RNAs peaks  MACS software was utilized. Differentially methylated sites were identified by diffReps. The motif predictions of MeRIP Seq data were performed by utilizing a Perl script  findMotifGenome.pl  from HOMER software. Genome build: GRCz11 Supplementary files format and content: Gene expression valuesFPKM and Counts and methylated sites", "zebrafish brain tissue", "Adult wild type zebrafish Danio rerio were bred according to standard methods. For hypoxia treatment  we followed settings established in a previously published protocolYu et al 2011 with modified conditions. Briefly  zebrafish were transferred into a 1 L chamber containing 800 mL predeoxidated water O2: 0.3 0.4 mg/L. Oxygen in the water was then exhausted through the application of 8 L/min nitrogen until the dissolved oxygen value in the water was approximately 0.4 0.6 mg/L. Nitrogen 1 L/min was used to maintain the dissolved oxygen level in the water. post approximately 5 minutes  when the fish became motionless  the zebrafish brain were dissected on ice post anesthetizing to obtain brain tissues. The brain tissues were stored for further analysis in liquid nitrogen.", "Ribo Zero rRNA Removal Kits Illumina  San Diego  CA  USA For RNA seq : TruSeq Stranded Total RNA Library Prep Kit Illumina  San Diego  CA  USA For MeRIP seq: GenSeqTM RNA IP Kit GenSeq Inc.  China and NEBNext\u00ae Ultra II Directional RNA Library Prep Kit New England Biolabs  Inc.  USA RNA seq and MeRIP seq", null, "tissue:brain", "GSM5832284", "GSM5832284: m7G Hypoxia Input; Danio rerio; OTHER", "GSM5832284 r1", "GSM5832284", "1", "Ribo Zero rRNA Removal Kits Illumina  San Diego  CA  USA For RNA seq : TruSeq Stranded Total RNA Library Prep Kit Illumina  San Diego  CA  USA For MeRIP seq: GenSeqTM RNA IP Kit GenSeq Inc.  China and NEBNext\u00ae Ultra II Directional RNA Library Prep Kit New England Biolabs  Inc.  USA RNA seq and MeRIP seq", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP356476", null, "loader:fastq load.py", "m7G_Hypoxia_Input_R1.fastq.gz m7G_Hypoxia_Input_R2.fastq.gz", "fastq fastq", 7492311600.0, 24974372.0, "GSM5832284 r1", "0:150 1:150", "A:2208863421;C:1521950436;G:1608371217;T:2153082842;N:43684", 150, 150, null, null, 2208863421, 1521950436, 1608371217, 2153082842, 43684, "SRX13883473", "SRS11752241", "SRA1361294", "Affiliated Hospital of Guangdong Medical University", "Affiliated Hospital of Guangdong Medical University", 2, 0.89264, 0.89479, 0.23239, 0.23163, 0.70496, 0.70311, 0.51741, 0.52135, 150, 150, "B", "B", "biological fallback assumption", "illumina", "novaseq_era", "full_length", "rrna_depletion", "nebnext", "bulk", "bulk", "bulk", null, "China", "2022-01-24", "Adult", "Adult", "Brain", "Nervous System"], [68386, "SRR17720613", "SRX13883472", "SRS11752242", "SRP356476", "PRJNA800053", "Mapping the m1A  m5C  m6A and m7G Methylation Atlas in Zebrafish Brains under Hypoxic Conditions by MeRIP seq", "GSE194284", "Other", "The epigenetic modifications play important regulatory roles in tissue development  maintenance of physiological functions and pathological process. RNA methylations  including newly identified m1A  m5C  m6A and m7G  are important epigenetic modifications. However  how these modifications are distributed in the transcriptome of vertebrate brains and whether their abundance is altered under pathological conditions are still poorly understood. In this study  we chose the model animal of zebrafish to conduct a systematic study to investigate the mRNA methylation atlas in the brain. By performing unbiased analyses of the m1A  m5C  m6A and m7G methylation of mRNA  we found that within the whole brain transcriptome  with the increase of the gene expression levels  the overall level of each of these four modifications on the related genes was also progressively increased. Further bioinformatics analysis indicated that the zebrafish brain has an abundance of m1A modifications. In the hypoxia treated zebrafish brains  the proportion of m1A is decreased  affecting the RNA splicing and zebrafish endogenous retroviruses. Our study presents the first comprehensive atlas of m1A  m5C  m6A and m7G in the epitranscriptome of the zebrafish brain and reveals the distribution of these modifications in mRNA under hypoxic conditions. These data provide an invaluable resource for further research on the involvement of m1A  m5C  m6A and m7G in the regulation of miRNA and repeat elements in vertebrates  and provide new thoughts to study the brain hypoxic injury on the aspect of epitranscriptome. Overall design: For each normoxia control and hypoxia experimental group  10 adult male zebrafish 3 mpf 4 mpf were chosen for the analyses. Three repeats of each experiment were performed and totally 30 fishes per group were collected. The brain tissues around 0.02 g per brain were then stored for further analysis in liquid nitrogen. For each analysis m1A  m5C  m6A  m7G and RNA Seq  the normoxia group and hypoxic group each consisted of 30 mixed brain tissues were analyzed parallelly by RNA seq and MeRIP Seq.", null, "pubmed:35135476", null, "m6A Normoxia IP", "GSM5832283", null, "source name:zebrafish brain tissue|tissue:brain", "m6A Normoxia IP", "Paired end reads were harvested from an Illumina NovaSeq 6000 sequencer Cutadapt v1.9.3  command line software  was used to identify and trim 3\u2019 adapter and low quality bases for rawdata. The clean data were mapped to the reference genome GRCz11 using Hisat2 software v2.0.4. For RNA seq: Guiding by the Ensembl GTF gene annotation file  Cuffdiff software part of cufflinks was used to obtain the gene level FPKM as the expression profiles of mRNA  fold change and p value were calculated based on FPKM For MeRIP seq: To identify the methylated sites on RNAs peaks  MACS software was utilized. Differentially methylated sites were identified by diffReps. The motif predictions of MeRIP Seq data were performed by utilizing a Perl script  findMotifGenome.pl  from HOMER software. Genome build: GRCz11 Supplementary files format and content: Gene expression valuesFPKM and Counts and methylated sites", "zebrafish brain tissue", "Adult wild type zebrafish Danio rerio were bred according to standard methods. For hypoxia treatment  we followed settings established in a previously published protocolYu et al 2011 with modified conditions. Briefly  zebrafish were transferred into a 1 L chamber containing 800 mL predeoxidated water O2: 0.3 0.4 mg/L. Oxygen in the water was then exhausted through the application of 8 L/min nitrogen until the dissolved oxygen value in the water was approximately 0.4 0.6 mg/L. Nitrogen 1 L/min was used to maintain the dissolved oxygen level in the water. post approximately 5 minutes  when the fish became motionless  the zebrafish brain were dissected on ice post anesthetizing to obtain brain tissues. The brain tissues were stored for further analysis in liquid nitrogen.", "Ribo Zero rRNA Removal Kits Illumina  San Diego  CA  USA For RNA seq : TruSeq Stranded Total RNA Library Prep Kit Illumina  San Diego  CA  USA For MeRIP seq: GenSeqTM RNA IP Kit GenSeq Inc.  China and NEBNext\u00ae Ultra II Directional RNA Library Prep Kit New England Biolabs  Inc.  USA RNA seq and MeRIP seq", null, "tissue:brain", "GSM5832283", "GSM5832283: m6A Normoxia IP; Danio rerio; OTHER", "GSM5832283 r1", "GSM5832283", "1", "Ribo Zero rRNA Removal Kits Illumina  San Diego  CA  USA For RNA seq : TruSeq Stranded Total RNA Library Prep Kit Illumina  San Diego  CA  USA For MeRIP seq: GenSeqTM RNA IP Kit GenSeq Inc.  China and NEBNext\u00ae Ultra II Directional RNA Library Prep Kit New England Biolabs  Inc.  USA RNA seq and MeRIP seq", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP356476", null, null, "m6A_Normoxia_IP_R1.fastq.gz m6A_Normoxia_IP_R2.fastq.gz", "fastq fastq", 6583667700.0, 21945559.0, "GSM5832283 r1", "0:150 1:150", "A:1750230540;C:1500991424;G:1592129260;T:1740287575;N:28901", 150, 150, null, null, 1750230540, 1500991424, 1592129260, 1740287575, 28901, "SRX13883472", "SRS11752242", "SRA1361294", "Affiliated Hospital of Guangdong Medical University", "Affiliated Hospital of Guangdong Medical University", 2, 0.87682, 0.87986, 0.18203, 0.17239, 0.74671, 0.7472, 0.55638, 0.55861, 150, 150, "B", "B", "biological fallback assumption", "illumina", "novaseq_era", "full_length", "rrna_depletion", "nebnext", "bulk", "bulk", "bulk", null, "China", "2022-01-24", "Adult", "Adult", "Brain", "Nervous System"], [68387, "SRR17720614", "SRX13883471", "SRS11752240", "SRP356476", "PRJNA800053", "Mapping the m1A  m5C  m6A and m7G Methylation Atlas in Zebrafish Brains under Hypoxic Conditions by MeRIP seq", "GSE194284", "Other", "The epigenetic modifications play important regulatory roles in tissue development  maintenance of physiological functions and pathological process. RNA methylations  including newly identified m1A  m5C  m6A and m7G  are important epigenetic modifications. However  how these modifications are distributed in the transcriptome of vertebrate brains and whether their abundance is altered under pathological conditions are still poorly understood. In this study  we chose the model animal of zebrafish to conduct a systematic study to investigate the mRNA methylation atlas in the brain. By performing unbiased analyses of the m1A  m5C  m6A and m7G methylation of mRNA  we found that within the whole brain transcriptome  with the increase of the gene expression levels  the overall level of each of these four modifications on the related genes was also progressively increased. Further bioinformatics analysis indicated that the zebrafish brain has an abundance of m1A modifications. In the hypoxia treated zebrafish brains  the proportion of m1A is decreased  affecting the RNA splicing and zebrafish endogenous retroviruses. Our study presents the first comprehensive atlas of m1A  m5C  m6A and m7G in the epitranscriptome of the zebrafish brain and reveals the distribution of these modifications in mRNA under hypoxic conditions. These data provide an invaluable resource for further research on the involvement of m1A  m5C  m6A and m7G in the regulation of miRNA and repeat elements in vertebrates  and provide new thoughts to study the brain hypoxic injury on the aspect of epitranscriptome. Overall design: For each normoxia control and hypoxia experimental group  10 adult male zebrafish 3 mpf 4 mpf were chosen for the analyses. Three repeats of each experiment were performed and totally 30 fishes per group were collected. The brain tissues around 0.02 g per brain were then stored for further analysis in liquid nitrogen. For each analysis m1A  m5C  m6A  m7G and RNA Seq  the normoxia group and hypoxic group each consisted of 30 mixed brain tissues were analyzed parallelly by RNA seq and MeRIP Seq.", null, "pubmed:35135476", null, "m6A Normoxia Input", "GSM5832282", null, "source name:zebrafish brain tissue|tissue:brain", "m6A Normoxia Input", "Paired end reads were harvested from an Illumina NovaSeq 6000 sequencer Cutadapt v1.9.3  command line software  was used to identify and trim 3\u2019 adapter and low quality bases for rawdata. The clean data were mapped to the reference genome GRCz11 using Hisat2 software v2.0.4. For RNA seq: Guiding by the Ensembl GTF gene annotation file  Cuffdiff software part of cufflinks was used to obtain the gene level FPKM as the expression profiles of mRNA  fold change and p value were calculated based on FPKM For MeRIP seq: To identify the methylated sites on RNAs peaks  MACS software was utilized. Differentially methylated sites were identified by diffReps. The motif predictions of MeRIP Seq data were performed by utilizing a Perl script  findMotifGenome.pl  from HOMER software. Genome build: GRCz11 Supplementary files format and content: Gene expression valuesFPKM and Counts and methylated sites", "zebrafish brain tissue", "Adult wild type zebrafish Danio rerio were bred according to standard methods. For hypoxia treatment  we followed settings established in a previously published protocolYu et al 2011 with modified conditions. Briefly  zebrafish were transferred into a 1 L chamber containing 800 mL predeoxidated water O2: 0.3 0.4 mg/L. Oxygen in the water was then exhausted through the application of 8 L/min nitrogen until the dissolved oxygen value in the water was approximately 0.4 0.6 mg/L. Nitrogen 1 L/min was used to maintain the dissolved oxygen level in the water. post approximately 5 minutes  when the fish became motionless  the zebrafish brain were dissected on ice post anesthetizing to obtain brain tissues. The brain tissues were stored for further analysis in liquid nitrogen.", "Ribo Zero rRNA Removal Kits Illumina  San Diego  CA  USA For RNA seq : TruSeq Stranded Total RNA Library Prep Kit Illumina  San Diego  CA  USA For MeRIP seq: GenSeqTM RNA IP Kit GenSeq Inc.  China and NEBNext\u00ae Ultra II Directional RNA Library Prep Kit New England Biolabs  Inc.  USA RNA seq and MeRIP seq", null, "tissue:brain", "GSM5832282", "GSM5832282: m6A Normoxia Input; Danio rerio; OTHER", "GSM5832282 r1", "GSM5832282", "1", "Ribo Zero rRNA Removal Kits Illumina  San Diego  CA  USA For RNA seq : TruSeq Stranded Total RNA Library Prep Kit Illumina  San Diego  CA  USA For MeRIP seq: GenSeqTM RNA IP Kit GenSeq Inc.  China and NEBNext\u00ae Ultra II Directional RNA Library Prep Kit New England Biolabs  Inc.  USA RNA seq and MeRIP seq", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP356476", null, "loader:fastq load.py", "m6A_Normoxia_Input_R1.fastq.gz m6A_Normoxia_Input_R2.fastq.gz", "fastq fastq", 6314076000.0, 21046920.0, "GSM5832282 r1", "0:150 1:150", "A:1815907910;C:1329572814;G:1378464668;T:1790102301;N:28307", 150, 150, null, null, 1815907910, 1329572814, 1378464668, 1790102301, 28307, "SRX13883471", "SRS11752240", "SRA1361294", "Affiliated Hospital of Guangdong Medical University", "Affiliated Hospital of Guangdong Medical University", 2, 0.91754, 0.91835, 0.21273, 0.20993, 0.69702, 0.69625, 0.53456, 0.53763, 150, 150, "B", "B", "biological fallback assumption", "illumina", "novaseq_era", "full_length", "rrna_depletion", "nebnext", "bulk", "bulk", "bulk", null, "China", "2022-01-24", "Adult", "Adult", "Brain", "Nervous System"], [68388, "SRR17720615", "SRX13883470", "SRS11752239", "SRP356476", "PRJNA800053", "Mapping the m1A  m5C  m6A and m7G Methylation Atlas in Zebrafish Brains under Hypoxic Conditions by MeRIP seq", "GSE194284", "Other", "The epigenetic modifications play important regulatory roles in tissue development  maintenance of physiological functions and pathological process. RNA methylations  including newly identified m1A  m5C  m6A and m7G  are important epigenetic modifications. However  how these modifications are distributed in the transcriptome of vertebrate brains and whether their abundance is altered under pathological conditions are still poorly understood. In this study  we chose the model animal of zebrafish to conduct a systematic study to investigate the mRNA methylation atlas in the brain. By performing unbiased analyses of the m1A  m5C  m6A and m7G methylation of mRNA  we found that within the whole brain transcriptome  with the increase of the gene expression levels  the overall level of each of these four modifications on the related genes was also progressively increased. Further bioinformatics analysis indicated that the zebrafish brain has an abundance of m1A modifications. In the hypoxia treated zebrafish brains  the proportion of m1A is decreased  affecting the RNA splicing and zebrafish endogenous retroviruses. Our study presents the first comprehensive atlas of m1A  m5C  m6A and m7G in the epitranscriptome of the zebrafish brain and reveals the distribution of these modifications in mRNA under hypoxic conditions. These data provide an invaluable resource for further research on the involvement of m1A  m5C  m6A and m7G in the regulation of miRNA and repeat elements in vertebrates  and provide new thoughts to study the brain hypoxic injury on the aspect of epitranscriptome. Overall design: For each normoxia control and hypoxia experimental group  10 adult male zebrafish 3 mpf 4 mpf were chosen for the analyses. Three repeats of each experiment were performed and totally 30 fishes per group were collected. The brain tissues around 0.02 g per brain were then stored for further analysis in liquid nitrogen. For each analysis m1A  m5C  m6A  m7G and RNA Seq  the normoxia group and hypoxic group each consisted of 30 mixed brain tissues were analyzed parallelly by RNA seq and MeRIP Seq.", null, "pubmed:35135476", null, "m6A Hypoxia IP", "GSM5832281", null, "source name:zebrafish brain tissue|tissue:brain", "m6A Hypoxia IP", "Paired end reads were harvested from an Illumina NovaSeq 6000 sequencer Cutadapt v1.9.3  command line software  was used to identify and trim 3\u2019 adapter and low quality bases for rawdata. The clean data were mapped to the reference genome GRCz11 using Hisat2 software v2.0.4. For RNA seq: Guiding by the Ensembl GTF gene annotation file  Cuffdiff software part of cufflinks was used to obtain the gene level FPKM as the expression profiles of mRNA  fold change and p value were calculated based on FPKM For MeRIP seq: To identify the methylated sites on RNAs peaks  MACS software was utilized. Differentially methylated sites were identified by diffReps. The motif predictions of MeRIP Seq data were performed by utilizing a Perl script  findMotifGenome.pl  from HOMER software. Genome build: GRCz11 Supplementary files format and content: Gene expression valuesFPKM and Counts and methylated sites", "zebrafish brain tissue", "Adult wild type zebrafish Danio rerio were bred according to standard methods. For hypoxia treatment  we followed settings established in a previously published protocolYu et al 2011 with modified conditions. Briefly  zebrafish were transferred into a 1 L chamber containing 800 mL predeoxidated water O2: 0.3 0.4 mg/L. Oxygen in the water was then exhausted through the application of 8 L/min nitrogen until the dissolved oxygen value in the water was approximately 0.4 0.6 mg/L. Nitrogen 1 L/min was used to maintain the dissolved oxygen level in the water. post approximately 5 minutes  when the fish became motionless  the zebrafish brain were dissected on ice post anesthetizing to obtain brain tissues. The brain tissues were stored for further analysis in liquid nitrogen.", "Ribo Zero rRNA Removal Kits Illumina  San Diego  CA  USA For RNA seq : TruSeq Stranded Total RNA Library Prep Kit Illumina  San Diego  CA  USA For MeRIP seq: GenSeqTM RNA IP Kit GenSeq Inc.  China and NEBNext\u00ae Ultra II Directional RNA Library Prep Kit New England Biolabs  Inc.  USA RNA seq and MeRIP seq", null, "tissue:brain", "GSM5832281", "GSM5832281: m6A Hypoxia IP; Danio rerio; OTHER", "GSM5832281 r1", "GSM5832281", "1", "Ribo Zero rRNA Removal Kits Illumina  San Diego  CA  USA For RNA seq : TruSeq Stranded Total RNA Library Prep Kit Illumina  San Diego  CA  USA For MeRIP seq: GenSeqTM RNA IP Kit GenSeq Inc.  China and NEBNext\u00ae Ultra II Directional RNA Library Prep Kit New England Biolabs  Inc.  USA RNA seq and MeRIP seq", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP356476", null, null, "m6A_Hypoxia_IP_R1.fastq.gz m6A_Hypoxia_IP_R2.fastq.gz", "fastq fastq", 6490349100.0, 21634497.0, "GSM5832281 r1", "0:150 1:150", "A:1714144102;C:1483635762;G:1606044832;T:1686496024;N:28380", 150, 150, null, null, 1714144102, 1483635762, 1606044832, 1686496024, 28380, "SRX13883470", "SRS11752239", "SRA1361294", "Affiliated Hospital of Guangdong Medical University", "Affiliated Hospital of Guangdong Medical University", 2, 0.87598, 0.88161, 0.16783, 0.16105, 0.74588, 0.74568, 0.55361, 0.55307, 150, 150, "B", "B", "biological fallback assumption", "illumina", "novaseq_era", "full_length", "rrna_depletion", "nebnext", "bulk", "bulk", "bulk", null, "China", "2022-01-24", "Adult", "Adult", "Brain", "Nervous System"], [68389, "SRR17720616", "SRX13883469", "SRS11752237", "SRP356476", "PRJNA800053", "Mapping the m1A  m5C  m6A and m7G Methylation Atlas in Zebrafish Brains under Hypoxic Conditions by MeRIP seq", "GSE194284", "Other", "The epigenetic modifications play important regulatory roles in tissue development  maintenance of physiological functions and pathological process. RNA methylations  including newly identified m1A  m5C  m6A and m7G  are important epigenetic modifications. However  how these modifications are distributed in the transcriptome of vertebrate brains and whether their abundance is altered under pathological conditions are still poorly understood. In this study  we chose the model animal of zebrafish to conduct a systematic study to investigate the mRNA methylation atlas in the brain. By performing unbiased analyses of the m1A  m5C  m6A and m7G methylation of mRNA  we found that within the whole brain transcriptome  with the increase of the gene expression levels  the overall level of each of these four modifications on the related genes was also progressively increased. Further bioinformatics analysis indicated that the zebrafish brain has an abundance of m1A modifications. In the hypoxia treated zebrafish brains  the proportion of m1A is decreased  affecting the RNA splicing and zebrafish endogenous retroviruses. Our study presents the first comprehensive atlas of m1A  m5C  m6A and m7G in the epitranscriptome of the zebrafish brain and reveals the distribution of these modifications in mRNA under hypoxic conditions. These data provide an invaluable resource for further research on the involvement of m1A  m5C  m6A and m7G in the regulation of miRNA and repeat elements in vertebrates  and provide new thoughts to study the brain hypoxic injury on the aspect of epitranscriptome. Overall design: For each normoxia control and hypoxia experimental group  10 adult male zebrafish 3 mpf 4 mpf were chosen for the analyses. Three repeats of each experiment were performed and totally 30 fishes per group were collected. The brain tissues around 0.02 g per brain were then stored for further analysis in liquid nitrogen. For each analysis m1A  m5C  m6A  m7G and RNA Seq  the normoxia group and hypoxic group each consisted of 30 mixed brain tissues were analyzed parallelly by RNA seq and MeRIP Seq.", null, "pubmed:35135476", null, "m6A Hypoxia Input", "GSM5832280", null, "source name:zebrafish brain tissue|tissue:brain", "m6A Hypoxia Input", "Paired end reads were harvested from an Illumina NovaSeq 6000 sequencer Cutadapt v1.9.3  command line software  was used to identify and trim 3\u2019 adapter and low quality bases for rawdata. The clean data were mapped to the reference genome GRCz11 using Hisat2 software v2.0.4. For RNA seq: Guiding by the Ensembl GTF gene annotation file  Cuffdiff software part of cufflinks was used to obtain the gene level FPKM as the expression profiles of mRNA  fold change and p value were calculated based on FPKM For MeRIP seq: To identify the methylated sites on RNAs peaks  MACS software was utilized. Differentially methylated sites were identified by diffReps. The motif predictions of MeRIP Seq data were performed by utilizing a Perl script  findMotifGenome.pl  from HOMER software. Genome build: GRCz11 Supplementary files format and content: Gene expression valuesFPKM and Counts and methylated sites", "zebrafish brain tissue", "Adult wild type zebrafish Danio rerio were bred according to standard methods. For hypoxia treatment  we followed settings established in a previously published protocolYu et al 2011 with modified conditions. Briefly  zebrafish were transferred into a 1 L chamber containing 800 mL predeoxidated water O2: 0.3 0.4 mg/L. Oxygen in the water was then exhausted through the application of 8 L/min nitrogen until the dissolved oxygen value in the water was approximately 0.4 0.6 mg/L. Nitrogen 1 L/min was used to maintain the dissolved oxygen level in the water. post approximately 5 minutes  when the fish became motionless  the zebrafish brain were dissected on ice post anesthetizing to obtain brain tissues. The brain tissues were stored for further analysis in liquid nitrogen.", "Ribo Zero rRNA Removal Kits Illumina  San Diego  CA  USA For RNA seq : TruSeq Stranded Total RNA Library Prep Kit Illumina  San Diego  CA  USA For MeRIP seq: GenSeqTM RNA IP Kit GenSeq Inc.  China and NEBNext\u00ae Ultra II Directional RNA Library Prep Kit New England Biolabs  Inc.  USA RNA seq and MeRIP seq", null, "tissue:brain", "GSM5832280", "GSM5832280: m6A Hypoxia Input; Danio rerio; OTHER", "GSM5832280 r1", "GSM5832280", "1", "Ribo Zero rRNA Removal Kits Illumina  San Diego  CA  USA For RNA seq : TruSeq Stranded Total RNA Library Prep Kit Illumina  San Diego  CA  USA For MeRIP seq: GenSeqTM RNA IP Kit GenSeq Inc.  China and NEBNext\u00ae Ultra II Directional RNA Library Prep Kit New England Biolabs  Inc.  USA RNA seq and MeRIP seq", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP356476", null, "loader:fastq load.py", "m6A_Hypoxia_Input_R1.fastq.gz m6A_Hypoxia_Input_R2.fastq.gz", "fastq fastq", 7054483800.0, 23514946.0, "GSM5832280 r1", "0:150 1:150", "A:2000164754;C:1513377207;G:1570441784;T:1970468107;N:31948", 150, 150, null, null, 2000164754, 1513377207, 1570441784, 1970468107, 31948, "SRX13883469", "SRS11752237", "SRA1361294", "Affiliated Hospital of Guangdong Medical University", "Affiliated Hospital of Guangdong Medical University", 2, 0.91916, 0.91997, 0.21403, 0.21158, 0.69716, 0.69503, 0.52616, 0.51982, 150, 150, "B", "B", "biological fallback assumption", "illumina", "novaseq_era", "full_length", "rrna_depletion", "nebnext", "bulk", "bulk", "bulk", null, "China", "2022-01-24", "Adult", "Adult", "Brain", "Nervous System"], [68390, "SRR17720617", "SRX13883468", "SRS11752238", "SRP356476", "PRJNA800053", "Mapping the m1A  m5C  m6A and m7G Methylation Atlas in Zebrafish Brains under Hypoxic Conditions by MeRIP seq", "GSE194284", "Other", "The epigenetic modifications play important regulatory roles in tissue development  maintenance of physiological functions and pathological process. RNA methylations  including newly identified m1A  m5C  m6A and m7G  are important epigenetic modifications. However  how these modifications are distributed in the transcriptome of vertebrate brains and whether their abundance is altered under pathological conditions are still poorly understood. In this study  we chose the model animal of zebrafish to conduct a systematic study to investigate the mRNA methylation atlas in the brain. By performing unbiased analyses of the m1A  m5C  m6A and m7G methylation of mRNA  we found that within the whole brain transcriptome  with the increase of the gene expression levels  the overall level of each of these four modifications on the related genes was also progressively increased. Further bioinformatics analysis indicated that the zebrafish brain has an abundance of m1A modifications. In the hypoxia treated zebrafish brains  the proportion of m1A is decreased  affecting the RNA splicing and zebrafish endogenous retroviruses. Our study presents the first comprehensive atlas of m1A  m5C  m6A and m7G in the epitranscriptome of the zebrafish brain and reveals the distribution of these modifications in mRNA under hypoxic conditions. These data provide an invaluable resource for further research on the involvement of m1A  m5C  m6A and m7G in the regulation of miRNA and repeat elements in vertebrates  and provide new thoughts to study the brain hypoxic injury on the aspect of epitranscriptome. Overall design: For each normoxia control and hypoxia experimental group  10 adult male zebrafish 3 mpf 4 mpf were chosen for the analyses. Three repeats of each experiment were performed and totally 30 fishes per group were collected. The brain tissues around 0.02 g per brain were then stored for further analysis in liquid nitrogen. For each analysis m1A  m5C  m6A  m7G and RNA Seq  the normoxia group and hypoxic group each consisted of 30 mixed brain tissues were analyzed parallelly by RNA seq and MeRIP Seq.", null, "pubmed:35135476", null, "m5C Normoxia IP", "GSM5832279", null, "source name:zebrafish brain tissue|tissue:brain", "m5C Normoxia IP", "Paired end reads were harvested from an Illumina NovaSeq 6000 sequencer Cutadapt v1.9.3  command line software  was used to identify and trim 3\u2019 adapter and low quality bases for rawdata. The clean data were mapped to the reference genome GRCz11 using Hisat2 software v2.0.4. For RNA seq: Guiding by the Ensembl GTF gene annotation file  Cuffdiff software part of cufflinks was used to obtain the gene level FPKM as the expression profiles of mRNA  fold change and p value were calculated based on FPKM For MeRIP seq: To identify the methylated sites on RNAs peaks  MACS software was utilized. Differentially methylated sites were identified by diffReps. The motif predictions of MeRIP Seq data were performed by utilizing a Perl script  findMotifGenome.pl  from HOMER software. Genome build: GRCz11 Supplementary files format and content: Gene expression valuesFPKM and Counts and methylated sites", "zebrafish brain tissue", "Adult wild type zebrafish Danio rerio were bred according to standard methods. For hypoxia treatment  we followed settings established in a previously published protocolYu et al 2011 with modified conditions. Briefly  zebrafish were transferred into a 1 L chamber containing 800 mL predeoxidated water O2: 0.3 0.4 mg/L. Oxygen in the water was then exhausted through the application of 8 L/min nitrogen until the dissolved oxygen value in the water was approximately 0.4 0.6 mg/L. Nitrogen 1 L/min was used to maintain the dissolved oxygen level in the water. post approximately 5 minutes  when the fish became motionless  the zebrafish brain were dissected on ice post anesthetizing to obtain brain tissues. The brain tissues were stored for further analysis in liquid nitrogen.", "Ribo Zero rRNA Removal Kits Illumina  San Diego  CA  USA For RNA seq : TruSeq Stranded Total RNA Library Prep Kit Illumina  San Diego  CA  USA For MeRIP seq: GenSeqTM RNA IP Kit GenSeq Inc.  China and NEBNext\u00ae Ultra II Directional RNA Library Prep Kit New England Biolabs  Inc.  USA RNA seq and MeRIP seq", null, "tissue:brain", "GSM5832279", "GSM5832279: m5C Normoxia IP; Danio rerio; OTHER", "GSM5832279 r1", "GSM5832279", "1", "Ribo Zero rRNA Removal Kits Illumina  San Diego  CA  USA For RNA seq : TruSeq Stranded Total RNA Library Prep Kit Illumina  San Diego  CA  USA For MeRIP seq: GenSeqTM RNA IP Kit GenSeq Inc.  China and NEBNext\u00ae Ultra II Directional RNA Library Prep Kit New England Biolabs  Inc.  USA RNA seq and MeRIP seq", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP356476", null, "loader:fastq load.py", "m5C_Normoxia_IP_R1.fastq.gz m5C_Normoxia_IP_R2.fastq.gz", "fastq fastq", 7385723100.0, 24619077.0, "GSM5832279 r1", "0:150 1:150", "A:1779838658;C:1853060139;G:2010257354;T:1742536078;N:30871", 150, 150, null, null, 1779838658, 1853060139, 2010257354, 1742536078, 30871, "SRX13883468", "SRS11752238", "SRA1361294", "Affiliated Hospital of Guangdong Medical University", "Affiliated Hospital of Guangdong Medical University", 2, 0.88617, 0.87633, 0.42619, 0.41974, 0.71792, 0.74016, 0.69827, 0.68649, 150, 150, "B", "B", "biological fallback assumption", "illumina", "novaseq_era", "full_length", "rrna_depletion", "nebnext", "bulk", "bulk", "bulk", null, "China", "2022-01-24", "Adult", "Adult", "Brain", "Nervous System"], [68391, "SRR17720618", "SRX13883467", "SRS11752236", "SRP356476", "PRJNA800053", "Mapping the m1A  m5C  m6A and m7G Methylation Atlas in Zebrafish Brains under Hypoxic Conditions by MeRIP seq", "GSE194284", "Other", "The epigenetic modifications play important regulatory roles in tissue development  maintenance of physiological functions and pathological process. RNA methylations  including newly identified m1A  m5C  m6A and m7G  are important epigenetic modifications. However  how these modifications are distributed in the transcriptome of vertebrate brains and whether their abundance is altered under pathological conditions are still poorly understood. In this study  we chose the model animal of zebrafish to conduct a systematic study to investigate the mRNA methylation atlas in the brain. By performing unbiased analyses of the m1A  m5C  m6A and m7G methylation of mRNA  we found that within the whole brain transcriptome  with the increase of the gene expression levels  the overall level of each of these four modifications on the related genes was also progressively increased. Further bioinformatics analysis indicated that the zebrafish brain has an abundance of m1A modifications. In the hypoxia treated zebrafish brains  the proportion of m1A is decreased  affecting the RNA splicing and zebrafish endogenous retroviruses. Our study presents the first comprehensive atlas of m1A  m5C  m6A and m7G in the epitranscriptome of the zebrafish brain and reveals the distribution of these modifications in mRNA under hypoxic conditions. These data provide an invaluable resource for further research on the involvement of m1A  m5C  m6A and m7G in the regulation of miRNA and repeat elements in vertebrates  and provide new thoughts to study the brain hypoxic injury on the aspect of epitranscriptome. Overall design: For each normoxia control and hypoxia experimental group  10 adult male zebrafish 3 mpf 4 mpf were chosen for the analyses. Three repeats of each experiment were performed and totally 30 fishes per group were collected. The brain tissues around 0.02 g per brain were then stored for further analysis in liquid nitrogen. For each analysis m1A  m5C  m6A  m7G and RNA Seq  the normoxia group and hypoxic group each consisted of 30 mixed brain tissues were analyzed parallelly by RNA seq and MeRIP Seq.", null, "pubmed:35135476", null, "m5C Normoxia Input", "GSM5832278", null, "source name:zebrafish brain tissue|tissue:brain", "m5C Normoxia Input", "Paired end reads were harvested from an Illumina NovaSeq 6000 sequencer Cutadapt v1.9.3  command line software  was used to identify and trim 3\u2019 adapter and low quality bases for rawdata. The clean data were mapped to the reference genome GRCz11 using Hisat2 software v2.0.4. For RNA seq: Guiding by the Ensembl GTF gene annotation file  Cuffdiff software part of cufflinks was used to obtain the gene level FPKM as the expression profiles of mRNA  fold change and p value were calculated based on FPKM For MeRIP seq: To identify the methylated sites on RNAs peaks  MACS software was utilized. Differentially methylated sites were identified by diffReps. The motif predictions of MeRIP Seq data were performed by utilizing a Perl script  findMotifGenome.pl  from HOMER software. Genome build: GRCz11 Supplementary files format and content: Gene expression valuesFPKM and Counts and methylated sites", "zebrafish brain tissue", "Adult wild type zebrafish Danio rerio were bred according to standard methods. For hypoxia treatment  we followed settings established in a previously published protocolYu et al 2011 with modified conditions. Briefly  zebrafish were transferred into a 1 L chamber containing 800 mL predeoxidated water O2: 0.3 0.4 mg/L. Oxygen in the water was then exhausted through the application of 8 L/min nitrogen until the dissolved oxygen value in the water was approximately 0.4 0.6 mg/L. Nitrogen 1 L/min was used to maintain the dissolved oxygen level in the water. post approximately 5 minutes  when the fish became motionless  the zebrafish brain were dissected on ice post anesthetizing to obtain brain tissues. The brain tissues were stored for further analysis in liquid nitrogen.", "Ribo Zero rRNA Removal Kits Illumina  San Diego  CA  USA For RNA seq : TruSeq Stranded Total RNA Library Prep Kit Illumina  San Diego  CA  USA For MeRIP seq: GenSeqTM RNA IP Kit GenSeq Inc.  China and NEBNext\u00ae Ultra II Directional RNA Library Prep Kit New England Biolabs  Inc.  USA RNA seq and MeRIP seq", null, "tissue:brain", "GSM5832278", "GSM5832278: m5C Normoxia Input; Danio rerio; OTHER", "GSM5832278 r1", "GSM5832278", "1", "Ribo Zero rRNA Removal Kits Illumina  San Diego  CA  USA For RNA seq : TruSeq Stranded Total RNA Library Prep Kit Illumina  San Diego  CA  USA For MeRIP seq: GenSeqTM RNA IP Kit GenSeq Inc.  China and NEBNext\u00ae Ultra II Directional RNA Library Prep Kit New England Biolabs  Inc.  USA RNA seq and MeRIP seq", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP356476", null, "loader:fastq load.py", "m5C_Normoxia_Input_R1.fastq.gz m5C_Normoxia_Input_R2.fastq.gz", "fastq fastq", 6594811500.0, 21982705.0, "GSM5832278 r1", "0:150 1:150", "A:1941068575;C:1341378672;G:1414823713;T:1897501503;N:39037", 150, 150, null, null, 1941068575, 1341378672, 1414823713, 1897501503, 39037, "SRX13883467", "SRS11752236", "SRA1361294", "Affiliated Hospital of Guangdong Medical University", "Affiliated Hospital of Guangdong Medical University", 2, 0.89423, 0.89602, 0.22595, 0.2243, 0.70212, 0.70112, 0.52954, 0.52253, 150, 150, "B", "B", "biological fallback assumption", "illumina", "novaseq_era", "full_length", "rrna_depletion", "nebnext", "bulk", "bulk", "bulk", null, "China", "2022-01-24", "Adult", "Adult", "Brain", "Nervous System"], [68392, "SRR17720619", "SRX13883466", "SRS11752235", "SRP356476", "PRJNA800053", "Mapping the m1A  m5C  m6A and m7G Methylation Atlas in Zebrafish Brains under Hypoxic Conditions by MeRIP seq", "GSE194284", "Other", "The epigenetic modifications play important regulatory roles in tissue development  maintenance of physiological functions and pathological process. RNA methylations  including newly identified m1A  m5C  m6A and m7G  are important epigenetic modifications. However  how these modifications are distributed in the transcriptome of vertebrate brains and whether their abundance is altered under pathological conditions are still poorly understood. In this study  we chose the model animal of zebrafish to conduct a systematic study to investigate the mRNA methylation atlas in the brain. By performing unbiased analyses of the m1A  m5C  m6A and m7G methylation of mRNA  we found that within the whole brain transcriptome  with the increase of the gene expression levels  the overall level of each of these four modifications on the related genes was also progressively increased. Further bioinformatics analysis indicated that the zebrafish brain has an abundance of m1A modifications. In the hypoxia treated zebrafish brains  the proportion of m1A is decreased  affecting the RNA splicing and zebrafish endogenous retroviruses. Our study presents the first comprehensive atlas of m1A  m5C  m6A and m7G in the epitranscriptome of the zebrafish brain and reveals the distribution of these modifications in mRNA under hypoxic conditions. These data provide an invaluable resource for further research on the involvement of m1A  m5C  m6A and m7G in the regulation of miRNA and repeat elements in vertebrates  and provide new thoughts to study the brain hypoxic injury on the aspect of epitranscriptome. Overall design: For each normoxia control and hypoxia experimental group  10 adult male zebrafish 3 mpf 4 mpf were chosen for the analyses. Three repeats of each experiment were performed and totally 30 fishes per group were collected. The brain tissues around 0.02 g per brain were then stored for further analysis in liquid nitrogen. For each analysis m1A  m5C  m6A  m7G and RNA Seq  the normoxia group and hypoxic group each consisted of 30 mixed brain tissues were analyzed parallelly by RNA seq and MeRIP Seq.", null, "pubmed:35135476", null, "m5C Hypoxia IP", "GSM5832277", null, "source name:zebrafish brain tissue|tissue:brain", "m5C Hypoxia IP", "Paired end reads were harvested from an Illumina NovaSeq 6000 sequencer Cutadapt v1.9.3  command line software  was used to identify and trim 3\u2019 adapter and low quality bases for rawdata. The clean data were mapped to the reference genome GRCz11 using Hisat2 software v2.0.4. For RNA seq: Guiding by the Ensembl GTF gene annotation file  Cuffdiff software part of cufflinks was used to obtain the gene level FPKM as the expression profiles of mRNA  fold change and p value were calculated based on FPKM For MeRIP seq: To identify the methylated sites on RNAs peaks  MACS software was utilized. Differentially methylated sites were identified by diffReps. The motif predictions of MeRIP Seq data were performed by utilizing a Perl script  findMotifGenome.pl  from HOMER software. Genome build: GRCz11 Supplementary files format and content: Gene expression valuesFPKM and Counts and methylated sites", "zebrafish brain tissue", "Adult wild type zebrafish Danio rerio were bred according to standard methods. For hypoxia treatment  we followed settings established in a previously published protocolYu et al 2011 with modified conditions. Briefly  zebrafish were transferred into a 1 L chamber containing 800 mL predeoxidated water O2: 0.3 0.4 mg/L. Oxygen in the water was then exhausted through the application of 8 L/min nitrogen until the dissolved oxygen value in the water was approximately 0.4 0.6 mg/L. Nitrogen 1 L/min was used to maintain the dissolved oxygen level in the water. post approximately 5 minutes  when the fish became motionless  the zebrafish brain were dissected on ice post anesthetizing to obtain brain tissues. The brain tissues were stored for further analysis in liquid nitrogen.", "Ribo Zero rRNA Removal Kits Illumina  San Diego  CA  USA For RNA seq : TruSeq Stranded Total RNA Library Prep Kit Illumina  San Diego  CA  USA For MeRIP seq: GenSeqTM RNA IP Kit GenSeq Inc.  China and NEBNext\u00ae Ultra II Directional RNA Library Prep Kit New England Biolabs  Inc.  USA RNA seq and MeRIP seq", null, "tissue:brain", "GSM5832277", "GSM5832277: m5C Hypoxia IP; Danio rerio; OTHER", "GSM5832277 r1", "GSM5832277", "1", "Ribo Zero rRNA Removal Kits Illumina  San Diego  CA  USA For RNA seq : TruSeq Stranded Total RNA Library Prep Kit Illumina  San Diego  CA  USA For MeRIP seq: GenSeqTM RNA IP Kit GenSeq Inc.  China and NEBNext\u00ae Ultra II Directional RNA Library Prep Kit New England Biolabs  Inc.  USA RNA seq and MeRIP seq", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP356476", null, "loader:fastq load.py", "m5C_Hypoxia_IP_R1.fastq.gz m5C_Hypoxia_IP_R2.fastq.gz", "fastq fastq", 7837067100.0, 26123557.0, "GSM5832277 r1", "0:150 1:150", "A:1881167242;C:1973697370;G:2143523979;T:1838645554;N:32955", 150, 150, null, null, 1881167242, 1973697370, 2143523979, 1838645554, 32955, "SRX13883466", "SRS11752235", "SRA1361294", "Affiliated Hospital of Guangdong Medical University", "Affiliated Hospital of Guangdong Medical University", 2, 0.87593, 0.87108, 0.45438, 0.45093, 0.71664, 0.7321, 0.67861, 0.69742, 150, 150, "B", "B", "biological fallback assumption", "illumina", "novaseq_era", "full_length", "rrna_depletion", "nebnext", "bulk", "bulk", "bulk", null, "China", "2022-01-24", "Adult", "Adult", "Brain", "Nervous System"], [68393, "SRR17720620", "SRX13883465", "SRS11752233", "SRP356476", "PRJNA800053", "Mapping the m1A  m5C  m6A and m7G Methylation Atlas in Zebrafish Brains under Hypoxic Conditions by MeRIP seq", "GSE194284", "Other", "The epigenetic modifications play important regulatory roles in tissue development  maintenance of physiological functions and pathological process. RNA methylations  including newly identified m1A  m5C  m6A and m7G  are important epigenetic modifications. However  how these modifications are distributed in the transcriptome of vertebrate brains and whether their abundance is altered under pathological conditions are still poorly understood. In this study  we chose the model animal of zebrafish to conduct a systematic study to investigate the mRNA methylation atlas in the brain. By performing unbiased analyses of the m1A  m5C  m6A and m7G methylation of mRNA  we found that within the whole brain transcriptome  with the increase of the gene expression levels  the overall level of each of these four modifications on the related genes was also progressively increased. Further bioinformatics analysis indicated that the zebrafish brain has an abundance of m1A modifications. In the hypoxia treated zebrafish brains  the proportion of m1A is decreased  affecting the RNA splicing and zebrafish endogenous retroviruses. Our study presents the first comprehensive atlas of m1A  m5C  m6A and m7G in the epitranscriptome of the zebrafish brain and reveals the distribution of these modifications in mRNA under hypoxic conditions. These data provide an invaluable resource for further research on the involvement of m1A  m5C  m6A and m7G in the regulation of miRNA and repeat elements in vertebrates  and provide new thoughts to study the brain hypoxic injury on the aspect of epitranscriptome. Overall design: For each normoxia control and hypoxia experimental group  10 adult male zebrafish 3 mpf 4 mpf were chosen for the analyses. Three repeats of each experiment were performed and totally 30 fishes per group were collected. The brain tissues around 0.02 g per brain were then stored for further analysis in liquid nitrogen. For each analysis m1A  m5C  m6A  m7G and RNA Seq  the normoxia group and hypoxic group each consisted of 30 mixed brain tissues were analyzed parallelly by RNA seq and MeRIP Seq.", null, "pubmed:35135476", null, "m5C Hypoxia Input", "GSM5832276", null, "source name:zebrafish brain tissue|tissue:brain", "m5C Hypoxia Input", "Paired end reads were harvested from an Illumina NovaSeq 6000 sequencer Cutadapt v1.9.3  command line software  was used to identify and trim 3\u2019 adapter and low quality bases for rawdata. The clean data were mapped to the reference genome GRCz11 using Hisat2 software v2.0.4. For RNA seq: Guiding by the Ensembl GTF gene annotation file  Cuffdiff software part of cufflinks was used to obtain the gene level FPKM as the expression profiles of mRNA  fold change and p value were calculated based on FPKM For MeRIP seq: To identify the methylated sites on RNAs peaks  MACS software was utilized. Differentially methylated sites were identified by diffReps. The motif predictions of MeRIP Seq data were performed by utilizing a Perl script  findMotifGenome.pl  from HOMER software. Genome build: GRCz11 Supplementary files format and content: Gene expression valuesFPKM and Counts and methylated sites", "zebrafish brain tissue", "Adult wild type zebrafish Danio rerio were bred according to standard methods. For hypoxia treatment  we followed settings established in a previously published protocolYu et al 2011 with modified conditions. Briefly  zebrafish were transferred into a 1 L chamber containing 800 mL predeoxidated water O2: 0.3 0.4 mg/L. Oxygen in the water was then exhausted through the application of 8 L/min nitrogen until the dissolved oxygen value in the water was approximately 0.4 0.6 mg/L. Nitrogen 1 L/min was used to maintain the dissolved oxygen level in the water. post approximately 5 minutes  when the fish became motionless  the zebrafish brain were dissected on ice post anesthetizing to obtain brain tissues. The brain tissues were stored for further analysis in liquid nitrogen.", "Ribo Zero rRNA Removal Kits Illumina  San Diego  CA  USA For RNA seq : TruSeq Stranded Total RNA Library Prep Kit Illumina  San Diego  CA  USA For MeRIP seq: GenSeqTM RNA IP Kit GenSeq Inc.  China and NEBNext\u00ae Ultra II Directional RNA Library Prep Kit New England Biolabs  Inc.  USA RNA seq and MeRIP seq", null, "tissue:brain", "GSM5832276", "GSM5832276: m5C Hypoxia Input; Danio rerio; OTHER", "GSM5832276 r1", "GSM5832276", "1", "Ribo Zero rRNA Removal Kits Illumina  San Diego  CA  USA For RNA seq : TruSeq Stranded Total RNA Library Prep Kit Illumina  San Diego  CA  USA For MeRIP seq: GenSeqTM RNA IP Kit GenSeq Inc.  China and NEBNext\u00ae Ultra II Directional RNA Library Prep Kit New England Biolabs  Inc.  USA RNA seq and MeRIP seq", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP356476", null, "loader:fastq load.py", "m5C_Hypoxia_Input_R1.fastq.gz m5C_Hypoxia_Input_R2.fastq.gz", "fastq fastq", 8696183100.0, 28987277.0, "GSM5832276 r1", "0:150 1:150", "A:2564166903;C:1771446935;G:1858965930;T:2501551942;N:51390", 150, 150, null, null, 2564166903, 1771446935, 1858965930, 2501551942, 51390, "SRX13883465", "SRS11752233", "SRA1361294", "Affiliated Hospital of Guangdong Medical University", "Affiliated Hospital of Guangdong Medical University", 2, 0.89379, 0.89585, 0.23898, 0.23828, 0.70272, 0.70278, 0.52965, 0.50047, 150, 150, "B", "B", "biological fallback assumption", "illumina", "novaseq_era", "full_length", "rrna_depletion", "nebnext", "bulk", "bulk", "bulk", null, "China", "2022-01-24", "Adult", "Adult", "Brain", "Nervous System"], [68394, "SRR17720621", "SRX13883464", "SRS11752234", "SRP356476", "PRJNA800053", "Mapping the m1A  m5C  m6A and m7G Methylation Atlas in Zebrafish Brains under Hypoxic Conditions by MeRIP seq", "GSE194284", "Other", "The epigenetic modifications play important regulatory roles in tissue development  maintenance of physiological functions and pathological process. RNA methylations  including newly identified m1A  m5C  m6A and m7G  are important epigenetic modifications. However  how these modifications are distributed in the transcriptome of vertebrate brains and whether their abundance is altered under pathological conditions are still poorly understood. In this study  we chose the model animal of zebrafish to conduct a systematic study to investigate the mRNA methylation atlas in the brain. By performing unbiased analyses of the m1A  m5C  m6A and m7G methylation of mRNA  we found that within the whole brain transcriptome  with the increase of the gene expression levels  the overall level of each of these four modifications on the related genes was also progressively increased. Further bioinformatics analysis indicated that the zebrafish brain has an abundance of m1A modifications. In the hypoxia treated zebrafish brains  the proportion of m1A is decreased  affecting the RNA splicing and zebrafish endogenous retroviruses. Our study presents the first comprehensive atlas of m1A  m5C  m6A and m7G in the epitranscriptome of the zebrafish brain and reveals the distribution of these modifications in mRNA under hypoxic conditions. These data provide an invaluable resource for further research on the involvement of m1A  m5C  m6A and m7G in the regulation of miRNA and repeat elements in vertebrates  and provide new thoughts to study the brain hypoxic injury on the aspect of epitranscriptome. Overall design: For each normoxia control and hypoxia experimental group  10 adult male zebrafish 3 mpf 4 mpf were chosen for the analyses. Three repeats of each experiment were performed and totally 30 fishes per group were collected. The brain tissues around 0.02 g per brain were then stored for further analysis in liquid nitrogen. For each analysis m1A  m5C  m6A  m7G and RNA Seq  the normoxia group and hypoxic group each consisted of 30 mixed brain tissues were analyzed parallelly by RNA seq and MeRIP Seq.", null, "pubmed:35135476", null, "m1A Normoxia IP", "GSM5832275", null, "source name:zebrafish brain tissue|tissue:brain", "m1A Normoxia IP", "Paired end reads were harvested from an Illumina NovaSeq 6000 sequencer Cutadapt v1.9.3  command line software  was used to identify and trim 3\u2019 adapter and low quality bases for rawdata. The clean data were mapped to the reference genome GRCz11 using Hisat2 software v2.0.4. For RNA seq: Guiding by the Ensembl GTF gene annotation file  Cuffdiff software part of cufflinks was used to obtain the gene level FPKM as the expression profiles of mRNA  fold change and p value were calculated based on FPKM For MeRIP seq: To identify the methylated sites on RNAs peaks  MACS software was utilized. Differentially methylated sites were identified by diffReps. The motif predictions of MeRIP Seq data were performed by utilizing a Perl script  findMotifGenome.pl  from HOMER software. Genome build: GRCz11 Supplementary files format and content: Gene expression valuesFPKM and Counts and methylated sites", "zebrafish brain tissue", "Adult wild type zebrafish Danio rerio were bred according to standard methods. For hypoxia treatment  we followed settings established in a previously published protocolYu et al 2011 with modified conditions. Briefly  zebrafish were transferred into a 1 L chamber containing 800 mL predeoxidated water O2: 0.3 0.4 mg/L. Oxygen in the water was then exhausted through the application of 8 L/min nitrogen until the dissolved oxygen value in the water was approximately 0.4 0.6 mg/L. Nitrogen 1 L/min was used to maintain the dissolved oxygen level in the water. post approximately 5 minutes  when the fish became motionless  the zebrafish brain were dissected on ice post anesthetizing to obtain brain tissues. The brain tissues were stored for further analysis in liquid nitrogen.", "Ribo Zero rRNA Removal Kits Illumina  San Diego  CA  USA For RNA seq : TruSeq Stranded Total RNA Library Prep Kit Illumina  San Diego  CA  USA For MeRIP seq: GenSeqTM RNA IP Kit GenSeq Inc.  China and NEBNext\u00ae Ultra II Directional RNA Library Prep Kit New England Biolabs  Inc.  USA RNA seq and MeRIP seq", null, "tissue:brain", "GSM5832275", "GSM5832275: m1A Normoxia IP; Danio rerio; OTHER", "GSM5832275 r1", "GSM5832275", "1", "Ribo Zero rRNA Removal Kits Illumina  San Diego  CA  USA For RNA seq : TruSeq Stranded Total RNA Library Prep Kit Illumina  San Diego  CA  USA For MeRIP seq: GenSeqTM RNA IP Kit GenSeq Inc.  China and NEBNext\u00ae Ultra II Directional RNA Library Prep Kit New England Biolabs  Inc.  USA RNA seq and MeRIP seq", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP356476", null, "loader:fastq load.py", "m1A_Normoxia_IP_R1.fastq.gz m1A_Normoxia_IP_R2.fastq.gz", "fastq fastq", 6882734400.0, 22942448.0, "GSM5832275 r1", "0:150 1:150", "A:1321946139;C:1977632664;G:2310916241;T:1272200359;N:38997", 150, 150, null, null, 1321946139, 1977632664, 2310916241, 1272200359, 38997, "SRX13883464", "SRS11752234", "SRA1361294", "Affiliated Hospital of Guangdong Medical University", "Affiliated Hospital of Guangdong Medical University", 2, 0.88367, 0.88951, 0.09774, 0.09525, 0.86395, 0.86401, 0.70125, 0.74894, 150, 150, "B", "B", "biological fallback assumption", "illumina", "novaseq_era", "full_length", "rrna_depletion", "nebnext", "bulk", "bulk", "bulk", null, "China", "2022-01-24", "Adult", "Adult", "Brain", "Nervous System"], [68395, "SRR17720622", "SRX13883463", "SRS11752232", "SRP356476", "PRJNA800053", "Mapping the m1A  m5C  m6A and m7G Methylation Atlas in Zebrafish Brains under Hypoxic Conditions by MeRIP seq", "GSE194284", "Other", "The epigenetic modifications play important regulatory roles in tissue development  maintenance of physiological functions and pathological process. RNA methylations  including newly identified m1A  m5C  m6A and m7G  are important epigenetic modifications. However  how these modifications are distributed in the transcriptome of vertebrate brains and whether their abundance is altered under pathological conditions are still poorly understood. In this study  we chose the model animal of zebrafish to conduct a systematic study to investigate the mRNA methylation atlas in the brain. By performing unbiased analyses of the m1A  m5C  m6A and m7G methylation of mRNA  we found that within the whole brain transcriptome  with the increase of the gene expression levels  the overall level of each of these four modifications on the related genes was also progressively increased. Further bioinformatics analysis indicated that the zebrafish brain has an abundance of m1A modifications. In the hypoxia treated zebrafish brains  the proportion of m1A is decreased  affecting the RNA splicing and zebrafish endogenous retroviruses. Our study presents the first comprehensive atlas of m1A  m5C  m6A and m7G in the epitranscriptome of the zebrafish brain and reveals the distribution of these modifications in mRNA under hypoxic conditions. These data provide an invaluable resource for further research on the involvement of m1A  m5C  m6A and m7G in the regulation of miRNA and repeat elements in vertebrates  and provide new thoughts to study the brain hypoxic injury on the aspect of epitranscriptome. Overall design: For each normoxia control and hypoxia experimental group  10 adult male zebrafish 3 mpf 4 mpf were chosen for the analyses. Three repeats of each experiment were performed and totally 30 fishes per group were collected. The brain tissues around 0.02 g per brain were then stored for further analysis in liquid nitrogen. For each analysis m1A  m5C  m6A  m7G and RNA Seq  the normoxia group and hypoxic group each consisted of 30 mixed brain tissues were analyzed parallelly by RNA seq and MeRIP Seq.", null, "pubmed:35135476", null, "m1A Normoxia Input", "GSM5832274", null, "source name:zebrafish brain tissue|tissue:brain", "m1A Normoxia Input", "Paired end reads were harvested from an Illumina NovaSeq 6000 sequencer Cutadapt v1.9.3  command line software  was used to identify and trim 3\u2019 adapter and low quality bases for rawdata. The clean data were mapped to the reference genome GRCz11 using Hisat2 software v2.0.4. For RNA seq: Guiding by the Ensembl GTF gene annotation file  Cuffdiff software part of cufflinks was used to obtain the gene level FPKM as the expression profiles of mRNA  fold change and p value were calculated based on FPKM For MeRIP seq: To identify the methylated sites on RNAs peaks  MACS software was utilized. Differentially methylated sites were identified by diffReps. The motif predictions of MeRIP Seq data were performed by utilizing a Perl script  findMotifGenome.pl  from HOMER software. Genome build: GRCz11 Supplementary files format and content: Gene expression valuesFPKM and Counts and methylated sites", "zebrafish brain tissue", "Adult wild type zebrafish Danio rerio were bred according to standard methods. For hypoxia treatment  we followed settings established in a previously published protocolYu et al 2011 with modified conditions. Briefly  zebrafish were transferred into a 1 L chamber containing 800 mL predeoxidated water O2: 0.3 0.4 mg/L. Oxygen in the water was then exhausted through the application of 8 L/min nitrogen until the dissolved oxygen value in the water was approximately 0.4 0.6 mg/L. Nitrogen 1 L/min was used to maintain the dissolved oxygen level in the water. post approximately 5 minutes  when the fish became motionless  the zebrafish brain were dissected on ice post anesthetizing to obtain brain tissues. The brain tissues were stored for further analysis in liquid nitrogen.", "Ribo Zero rRNA Removal Kits Illumina  San Diego  CA  USA For RNA seq : TruSeq Stranded Total RNA Library Prep Kit Illumina  San Diego  CA  USA For MeRIP seq: GenSeqTM RNA IP Kit GenSeq Inc.  China and NEBNext\u00ae Ultra II Directional RNA Library Prep Kit New England Biolabs  Inc.  USA RNA seq and MeRIP seq", null, "tissue:brain", "GSM5832274", "GSM5832274: m1A Normoxia Input; Danio rerio; OTHER", "GSM5832274 r1", "GSM5832274", "1", "Ribo Zero rRNA Removal Kits Illumina  San Diego  CA  USA For RNA seq : TruSeq Stranded Total RNA Library Prep Kit Illumina  San Diego  CA  USA For MeRIP seq: GenSeqTM RNA IP Kit GenSeq Inc.  China and NEBNext\u00ae Ultra II Directional RNA Library Prep Kit New England Biolabs  Inc.  USA RNA seq and MeRIP seq", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP356476", null, "loader:fastq load.py", "m1A_Normoxia_Input_R1.fastq.gz m1A_Normoxia_Input_R2.fastq.gz", "fastq fastq", 7374452700.0, 24581509.0, "GSM5832274 r1", "0:150 1:150", "A:1511389847;C:2082118937;G:2325922232;T:1454979400;N:42284", 150, 150, null, null, 1511389847, 2082118937, 2325922232, 1454979400, 42284, "SRX13883463", "SRS11752232", "SRA1361294", "Affiliated Hospital of Guangdong Medical University", "Affiliated Hospital of Guangdong Medical University", 2, 0.94589, 0.94385, 0.18226, 0.18222, 0.80878, 0.8102, 0.73686, 0.71921, 150, 150, "B", "B", "biological fallback assumption", "illumina", "novaseq_era", "full_length", "rrna_depletion", "nebnext", "bulk", "bulk", "bulk", null, "China", "2022-01-24", "Adult", "Adult", "Brain", "Nervous System"], [68396, "SRR17720623", "SRX13883462", "SRS11752231", "SRP356476", "PRJNA800053", "Mapping the m1A  m5C  m6A and m7G Methylation Atlas in Zebrafish Brains under Hypoxic Conditions by MeRIP seq", "GSE194284", "Other", "The epigenetic modifications play important regulatory roles in tissue development  maintenance of physiological functions and pathological process. RNA methylations  including newly identified m1A  m5C  m6A and m7G  are important epigenetic modifications. However  how these modifications are distributed in the transcriptome of vertebrate brains and whether their abundance is altered under pathological conditions are still poorly understood. In this study  we chose the model animal of zebrafish to conduct a systematic study to investigate the mRNA methylation atlas in the brain. By performing unbiased analyses of the m1A  m5C  m6A and m7G methylation of mRNA  we found that within the whole brain transcriptome  with the increase of the gene expression levels  the overall level of each of these four modifications on the related genes was also progressively increased. Further bioinformatics analysis indicated that the zebrafish brain has an abundance of m1A modifications. In the hypoxia treated zebrafish brains  the proportion of m1A is decreased  affecting the RNA splicing and zebrafish endogenous retroviruses. Our study presents the first comprehensive atlas of m1A  m5C  m6A and m7G in the epitranscriptome of the zebrafish brain and reveals the distribution of these modifications in mRNA under hypoxic conditions. These data provide an invaluable resource for further research on the involvement of m1A  m5C  m6A and m7G in the regulation of miRNA and repeat elements in vertebrates  and provide new thoughts to study the brain hypoxic injury on the aspect of epitranscriptome. Overall design: For each normoxia control and hypoxia experimental group  10 adult male zebrafish 3 mpf 4 mpf were chosen for the analyses. Three repeats of each experiment were performed and totally 30 fishes per group were collected. The brain tissues around 0.02 g per brain were then stored for further analysis in liquid nitrogen. For each analysis m1A  m5C  m6A  m7G and RNA Seq  the normoxia group and hypoxic group each consisted of 30 mixed brain tissues were analyzed parallelly by RNA seq and MeRIP Seq.", null, "pubmed:35135476", null, "m1A Hypoxia IP", "GSM5832273", null, "source name:zebrafish brain tissue|tissue:brain", "m1A Hypoxia IP", "Paired end reads were harvested from an Illumina NovaSeq 6000 sequencer Cutadapt v1.9.3  command line software  was used to identify and trim 3\u2019 adapter and low quality bases for rawdata. The clean data were mapped to the reference genome GRCz11 using Hisat2 software v2.0.4. For RNA seq: Guiding by the Ensembl GTF gene annotation file  Cuffdiff software part of cufflinks was used to obtain the gene level FPKM as the expression profiles of mRNA  fold change and p value were calculated based on FPKM For MeRIP seq: To identify the methylated sites on RNAs peaks  MACS software was utilized. Differentially methylated sites were identified by diffReps. The motif predictions of MeRIP Seq data were performed by utilizing a Perl script  findMotifGenome.pl  from HOMER software. Genome build: GRCz11 Supplementary files format and content: Gene expression valuesFPKM and Counts and methylated sites", "zebrafish brain tissue", "Adult wild type zebrafish Danio rerio were bred according to standard methods. For hypoxia treatment  we followed settings established in a previously published protocolYu et al 2011 with modified conditions. Briefly  zebrafish were transferred into a 1 L chamber containing 800 mL predeoxidated water O2: 0.3 0.4 mg/L. Oxygen in the water was then exhausted through the application of 8 L/min nitrogen until the dissolved oxygen value in the water was approximately 0.4 0.6 mg/L. Nitrogen 1 L/min was used to maintain the dissolved oxygen level in the water. post approximately 5 minutes  when the fish became motionless  the zebrafish brain were dissected on ice post anesthetizing to obtain brain tissues. The brain tissues were stored for further analysis in liquid nitrogen.", "Ribo Zero rRNA Removal Kits Illumina  San Diego  CA  USA For RNA seq : TruSeq Stranded Total RNA Library Prep Kit Illumina  San Diego  CA  USA For MeRIP seq: GenSeqTM RNA IP Kit GenSeq Inc.  China and NEBNext\u00ae Ultra II Directional RNA Library Prep Kit New England Biolabs  Inc.  USA RNA seq and MeRIP seq", null, "tissue:brain", "GSM5832273", "GSM5832273: m1A Hypoxia IP; Danio rerio; OTHER", "GSM5832273 r1", "GSM5832273", "1", "Ribo Zero rRNA Removal Kits Illumina  San Diego  CA  USA For RNA seq : TruSeq Stranded Total RNA Library Prep Kit Illumina  San Diego  CA  USA For MeRIP seq: GenSeqTM RNA IP Kit GenSeq Inc.  China and NEBNext\u00ae Ultra II Directional RNA Library Prep Kit New England Biolabs  Inc.  USA RNA seq and MeRIP seq", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP356476", null, "loader:fastq load.py", "m1A_Hypoxia_IP_R1.fastq.gz m1A_Hypoxia_IP_R2.fastq.gz", "fastq fastq", 4861573800.0, 16205246.0, "GSM5832273 r1", "0:150 1:150", "A:927063480;C:1355342107;G:1698345464;T:880801957;N:20792", 150, 150, null, null, 927063480, 1355342107, 1698345464, 880801957, 20792, "SRX13883462", "SRS11752231", "SRA1361294", "Affiliated Hospital of Guangdong Medical University", "Affiliated Hospital of Guangdong Medical University", 2, 0.8575, 0.86165, 0.10013, 0.09909, 0.87249, 0.87221, 0.72225, 0.66629, 150, 150, "B", "B", "biological fallback assumption", "illumina", "novaseq_era", "full_length", "rrna_depletion", "nebnext", "bulk", "bulk", "bulk", null, "China", "2022-01-24", "Adult", "Adult", "Brain", "Nervous System"], [68397, "SRR17720624", "SRX13883461", "SRS11752229", "SRP356476", "PRJNA800053", "Mapping the m1A  m5C  m6A and m7G Methylation Atlas in Zebrafish Brains under Hypoxic Conditions by MeRIP seq", "GSE194284", "Other", "The epigenetic modifications play important regulatory roles in tissue development  maintenance of physiological functions and pathological process. RNA methylations  including newly identified m1A  m5C  m6A and m7G  are important epigenetic modifications. However  how these modifications are distributed in the transcriptome of vertebrate brains and whether their abundance is altered under pathological conditions are still poorly understood. In this study  we chose the model animal of zebrafish to conduct a systematic study to investigate the mRNA methylation atlas in the brain. By performing unbiased analyses of the m1A  m5C  m6A and m7G methylation of mRNA  we found that within the whole brain transcriptome  with the increase of the gene expression levels  the overall level of each of these four modifications on the related genes was also progressively increased. Further bioinformatics analysis indicated that the zebrafish brain has an abundance of m1A modifications. In the hypoxia treated zebrafish brains  the proportion of m1A is decreased  affecting the RNA splicing and zebrafish endogenous retroviruses. Our study presents the first comprehensive atlas of m1A  m5C  m6A and m7G in the epitranscriptome of the zebrafish brain and reveals the distribution of these modifications in mRNA under hypoxic conditions. These data provide an invaluable resource for further research on the involvement of m1A  m5C  m6A and m7G in the regulation of miRNA and repeat elements in vertebrates  and provide new thoughts to study the brain hypoxic injury on the aspect of epitranscriptome. Overall design: For each normoxia control and hypoxia experimental group  10 adult male zebrafish 3 mpf 4 mpf were chosen for the analyses. Three repeats of each experiment were performed and totally 30 fishes per group were collected. The brain tissues around 0.02 g per brain were then stored for further analysis in liquid nitrogen. For each analysis m1A  m5C  m6A  m7G and RNA Seq  the normoxia group and hypoxic group each consisted of 30 mixed brain tissues were analyzed parallelly by RNA seq and MeRIP Seq.", null, "pubmed:35135476", null, "m1A Hypoxia Input", "GSM5832272", null, "source name:zebrafish brain tissue|tissue:brain", "m1A Hypoxia Input", "Paired end reads were harvested from an Illumina NovaSeq 6000 sequencer Cutadapt v1.9.3  command line software  was used to identify and trim 3\u2019 adapter and low quality bases for rawdata. The clean data were mapped to the reference genome GRCz11 using Hisat2 software v2.0.4. For RNA seq: Guiding by the Ensembl GTF gene annotation file  Cuffdiff software part of cufflinks was used to obtain the gene level FPKM as the expression profiles of mRNA  fold change and p value were calculated based on FPKM For MeRIP seq: To identify the methylated sites on RNAs peaks  MACS software was utilized. Differentially methylated sites were identified by diffReps. The motif predictions of MeRIP Seq data were performed by utilizing a Perl script  findMotifGenome.pl  from HOMER software. Genome build: GRCz11 Supplementary files format and content: Gene expression valuesFPKM and Counts and methylated sites", "zebrafish brain tissue", "Adult wild type zebrafish Danio rerio were bred according to standard methods. For hypoxia treatment  we followed settings established in a previously published protocolYu et al 2011 with modified conditions. Briefly  zebrafish were transferred into a 1 L chamber containing 800 mL predeoxidated water O2: 0.3 0.4 mg/L. Oxygen in the water was then exhausted through the application of 8 L/min nitrogen until the dissolved oxygen value in the water was approximately 0.4 0.6 mg/L. Nitrogen 1 L/min was used to maintain the dissolved oxygen level in the water. post approximately 5 minutes  when the fish became motionless  the zebrafish brain were dissected on ice post anesthetizing to obtain brain tissues. The brain tissues were stored for further analysis in liquid nitrogen.", "Ribo Zero rRNA Removal Kits Illumina  San Diego  CA  USA For RNA seq : TruSeq Stranded Total RNA Library Prep Kit Illumina  San Diego  CA  USA For MeRIP seq: GenSeqTM RNA IP Kit GenSeq Inc.  China and NEBNext\u00ae Ultra II Directional RNA Library Prep Kit New England Biolabs  Inc.  USA RNA seq and MeRIP seq", null, "tissue:brain", "GSM5832272", "GSM5832272: m1A Hypoxia Input; Danio rerio; OTHER", "GSM5832272 r1", "GSM5832272", "1", "Ribo Zero rRNA Removal Kits Illumina  San Diego  CA  USA For RNA seq : TruSeq Stranded Total RNA Library Prep Kit Illumina  San Diego  CA  USA For MeRIP seq: GenSeqTM RNA IP Kit GenSeq Inc.  China and NEBNext\u00ae Ultra II Directional RNA Library Prep Kit New England Biolabs  Inc.  USA RNA seq and MeRIP seq", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP356476", null, "loader:fastq load.py", "m1A_Hypoxia_Input_R1.fastq.gz m1A_Hypoxia_Input_R2.fastq.gz", "fastq fastq", 7262130600.0, 24207102.0, "GSM5832272 r1", "0:150 1:150", "A:1553326396;C:2003023914;G:2214285414;T:1491453374;N:41502", 150, 150, null, null, 1553326396, 2003023914, 2214285414, 1491453374, 41502, "SRX13883461", "SRS11752229", "SRA1361294", "Affiliated Hospital of Guangdong Medical University", "Affiliated Hospital of Guangdong Medical University", 2, 0.94247, 0.94013, 0.20625, 0.20507, 0.80188, 0.80137, 0.70188, 0.73891, 150, 150, "B", "B", "biological fallback assumption", "illumina", "novaseq_era", "full_length", "rrna_depletion", "nebnext", "bulk", "bulk", "bulk", null, "China", "2022-01-24", "Adult", "Adult", "Brain", "Nervous System"], [72561, "SRR22722190", "SRX18683720", "SRS16126888", "SRP412911", "PRJNA911847", "Transgenic IDH2 R172K and IDH2 R140Q zebrafish models recapitulated features of human acute myeloid leukaemia", "PRJNA911847", "Other", "Isocitrate dehydrogenase 2 IDH2 mutations occur in more than 15% of cytogenetically normal acute myeloid leukemia CN AML but comparative studies of their roles in leukemogenesis have been scarce. We generated zebrafish models of IDH2R172K and IDH2R140Q AML and reported their pathologic  functional and transcriptomic features and therapeutic responses to target therapies. Transgenic embryos co expressing FLT3ITD and IDH2 mutations showed accentuation of myelopoiesis. As these embryos were raised to maturity  full blown leukemia ensued with multi lineage dysplasia  increase in myeloblasts and marrow cellularity and splenomegaly. The leukemia cells were transplantable into primary and secondary recipients and resulted in more aggressive disease. TgRunx1:FLT3ITDIDH2R172K but not TgRunx1:FLT3ITDIDH2R140Q zebrafish showed increase in T cell development at embryonic and adult stage. Single cell transcriptomic analysis revealed increased myeloid skewing  differentiation blockade and enrichment of leukemia associated gene signatures in both zebrafish models. TgRunx1:FLT3ITDIDH2R172K but not TgRunx1:FLT3ITDIDH2R140Q zebrafish showed increase in interferon signals at adult stage. Leukemic phenotypes in both zebrafish could be ameliorated by quizartinib and enasidenib. In conclusion  the zebrafish models of IDH2 mutated AML recapitulated the morphologic  clinical  functional and transcriptomic characteristics of human diseases  and provided the prototype for developing zebrafish leukemia models of other genotypes that would become a platform for high throughput drug screening", null, null, null, null, "Transgenic FLT3 ITD IDH2 R140Q", null, "strain:TU|isolate:not applicable|breed:not applicable|cultivar:not applicable|ecotype:not applicable|age:8 month|dev stage:8 month|sex:pooled male and female|tissue:kidney marrow|genotype:Transgenic Runx1:FLT3ITDIDH2R140Q|BioSampleModel:Model organism or animal", null, null, null, null, null, null, null, null, "Single cell RNA seq of Danio rerio: Transgenic FLT3 ITD IDH2 R140Q", "ITD140Q", "ITD140Q", "Single cell RNA seq library.Single viable KM cells were collected from the transgenic double mutant n=3; pooled and WT n=3; pooled fish at 7 mpf into 0.9X PBS with 5% FBS. Their viability was examined by 0.4% Trypan blue staining under microscopy. The single cell library was constructed using the ChromiumTM Controller and ChromiumTM Next GEM Single Cell 3 Kit v3.1 10x Genomics  Pleasanton  CA. Complementary DNA cDNA was synthesized from the fragmentated RNAs using N6 random primers  followed by end repair and ligation to BGISEQ sequencer compatible adapters. Quality control of the final library was performed by checking the distribution of the fragments size using the Agilent 2100 bioanalyzer and quantification was performed by real time quantitative PCR using TaqMan probes. The final products were sequenced using the DNBSEQTM platform BGI  HK  China.", null, null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "DNBSEQ", "DNBSEQ-G400", null, "SRP412911", null, "loader:fastq load.py", "ITD172KA_S1_L001_I1_001.fastq.gz ITD172KA_S1_L001_R1_001.fastq.gz ITD172KA_S1_L001_R2_001.fastq.gz", "fastq fastq fastq", 52149830422.0, 410628586.0, "ITD172KA S1 L001 I1 001.fastq.gz", "0:8 1:28 2:91", "A:10282953217;C:8459559201;G:8851285287;T:9772343870;N:1059751", 8, 28, 91, null, 10282953217, 8459559201, 8851285287, 9772343870, 1059751, "SRX18683720", "SRS16126888", "SRA1558824", "The University of Hong Kong|Department of Medicine", "The University of Hong Kong", 1, 0.88465, null, 0.13112, null, 0.81789, null, 0.55842, null, 91, null, "B", null, "usable mapping rate", "bgi", "bgi", "unknown", "random_priming", "unknown", "sc", "single_cell_droplet", "10x", null, "China", "2022-12-14", "Adult", "Adult", "Kidney", "Renal System"], [72562, "SRR22722191", "SRX18683719", "SRS16126887", "SRP412911", "PRJNA911847", "Transgenic IDH2 R172K and IDH2 R140Q zebrafish models recapitulated features of human acute myeloid leukaemia", "PRJNA911847", "Other", "Isocitrate dehydrogenase 2 IDH2 mutations occur in more than 15% of cytogenetically normal acute myeloid leukemia CN AML but comparative studies of their roles in leukemogenesis have been scarce. We generated zebrafish models of IDH2R172K and IDH2R140Q AML and reported their pathologic  functional and transcriptomic features and therapeutic responses to target therapies. Transgenic embryos co expressing FLT3ITD and IDH2 mutations showed accentuation of myelopoiesis. As these embryos were raised to maturity  full blown leukemia ensued with multi lineage dysplasia  increase in myeloblasts and marrow cellularity and splenomegaly. The leukemia cells were transplantable into primary and secondary recipients and resulted in more aggressive disease. TgRunx1:FLT3ITDIDH2R172K but not TgRunx1:FLT3ITDIDH2R140Q zebrafish showed increase in T cell development at embryonic and adult stage. Single cell transcriptomic analysis revealed increased myeloid skewing  differentiation blockade and enrichment of leukemia associated gene signatures in both zebrafish models. TgRunx1:FLT3ITDIDH2R172K but not TgRunx1:FLT3ITDIDH2R140Q zebrafish showed increase in interferon signals at adult stage. Leukemic phenotypes in both zebrafish could be ameliorated by quizartinib and enasidenib. In conclusion  the zebrafish models of IDH2 mutated AML recapitulated the morphologic  clinical  functional and transcriptomic characteristics of human diseases  and provided the prototype for developing zebrafish leukemia models of other genotypes that would become a platform for high throughput drug screening", null, null, null, null, "Transgenic FLT3 ITD IDH2 R172K", null, "strain:TU|isolate:not applicable|breed:not applicable|cultivar:not applicable|ecotype:not applicable|age:8 month|dev stage:8 month|sex:pooled male and female|tissue:kidney marrow|genotype:Transgenic Runx1:FLT3ITDIDH2R172K|BioSampleModel:Model organism or animal", null, null, null, null, null, null, null, null, "Single cell RNA seq of Danio rerio: Transgenic FLT3 ITD IDH2 R172K", "ITD172K", "ITD172K", "Single cell RNA seq library.Single viable KM cells were collected from the transgenic double mutant n=3; pooled and WT n=3; pooled fish at 7 mpf into 0.9X PBS with 5% FBS. Their viability was examined by 0.4% Trypan blue staining under microscopy. The single cell library was constructed using the ChromiumTM Controller and ChromiumTM Next GEM Single Cell 3 Kit v3.1 10x Genomics  Pleasanton  CA. Complementary DNA cDNA was synthesized from the fragmentated RNAs using N6 random primers  followed by end repair and ligation to BGISEQ sequencer compatible adapters. Quality control of the final library was performed by checking the distribution of the fragments size using the Agilent 2100 bioanalyzer and quantification was performed by real time quantitative PCR using TaqMan probes. The final products were sequenced using the DNBSEQTM platform BGI  HK  China.", null, null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "DNBSEQ", "DNBSEQ-G400", null, "SRP412911", null, "loader:fastq load.py", "ITD140QA_S1_L004_I1_001.fastq.gz ITD140QA_S1_L004_R1_001.fastq.gz ITD140QA_S1_L004_R2_001.fastq.gz", "fastq fastq fastq", 28595025233.0, 225157679.0, "ITD140QA S1 L004 I1 001.fastq.gz", "0:8 1:28 2:91", "A:5628987577;C:4565848641;G:4959209904;T:5302394659;N:32908008", 8, 28, 91, null, 5628987577, 4565848641, 4959209904, 5302394659, 32908008, "SRX18683719", "SRS16126887", "SRA1558824", "The University of Hong Kong|Department of Medicine", "The University of Hong Kong", 1, 0.81404, null, 0.11315, null, 0.83327, null, 0.56222, null, 91, null, "B", null, "usable mapping rate", "bgi", "bgi", "unknown", "random_priming", "unknown", "sc", "single_cell_droplet", "10x", null, "China", "2022-12-13", "Adult", "Adult", "Kidney", "Renal System"], [72563, "SRR22722192", "SRX18683718", "SRS16126886", "SRP412911", "PRJNA911847", "Transgenic IDH2 R172K and IDH2 R140Q zebrafish models recapitulated features of human acute myeloid leukaemia", "PRJNA911847", "Other", "Isocitrate dehydrogenase 2 IDH2 mutations occur in more than 15% of cytogenetically normal acute myeloid leukemia CN AML but comparative studies of their roles in leukemogenesis have been scarce. We generated zebrafish models of IDH2R172K and IDH2R140Q AML and reported their pathologic  functional and transcriptomic features and therapeutic responses to target therapies. Transgenic embryos co expressing FLT3ITD and IDH2 mutations showed accentuation of myelopoiesis. As these embryos were raised to maturity  full blown leukemia ensued with multi lineage dysplasia  increase in myeloblasts and marrow cellularity and splenomegaly. The leukemia cells were transplantable into primary and secondary recipients and resulted in more aggressive disease. TgRunx1:FLT3ITDIDH2R172K but not TgRunx1:FLT3ITDIDH2R140Q zebrafish showed increase in T cell development at embryonic and adult stage. Single cell transcriptomic analysis revealed increased myeloid skewing  differentiation blockade and enrichment of leukemia associated gene signatures in both zebrafish models. TgRunx1:FLT3ITDIDH2R172K but not TgRunx1:FLT3ITDIDH2R140Q zebrafish showed increase in interferon signals at adult stage. Leukemic phenotypes in both zebrafish could be ameliorated by quizartinib and enasidenib. In conclusion  the zebrafish models of IDH2 mutated AML recapitulated the morphologic  clinical  functional and transcriptomic characteristics of human diseases  and provided the prototype for developing zebrafish leukemia models of other genotypes that would become a platform for high throughput drug screening", null, null, null, null, "Wild type", null, "strain:TU|isolate:not applicable|breed:not applicable|cultivar:not applicable|ecotype:not applicable|age:8 month|dev stage:8 month|sex:pooled male and female|tissue:kidney marrow|genotype:Wild type|BioSampleModel:Model organism or animal", null, null, null, null, null, null, null, null, "Single cell RNA seq of Danio rerio: Wild type", "Control", "Control", "Single cell RNA seq library.Single viable KM cells were collected from the transgenic double mutant n=3; pooled and WT n=3; pooled fish at 7 mpf into 0.9X PBS with 5% FBS. Their viability was examined by 0.4% Trypan blue staining under microscopy. The single cell library was constructed using the ChromiumTM Controller and ChromiumTM Next GEM Single Cell 3 Kit v3.1 10x Genomics  Pleasanton  CA. Complementary DNA cDNA was synthesized from the fragmentated RNAs using N6 random primers  followed by end repair and ligation to BGISEQ sequencer compatible adapters. Quality control of the final library was performed by checking the distribution of the fragments size using the Agilent 2100 bioanalyzer and quantification was performed by real time quantitative PCR using TaqMan probes. The final products were sequenced using the DNBSEQTM platform BGI  HK  China.", null, null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "DNBSEQ", "DNBSEQ-G400", null, "SRP412911", null, "loader:fastq load.py", "ControlA_S1_L003_R2_001.fastq.gz ControlA_S1_L003_R1_001.fastq.gz ControlA_S1_L003_I1_001.fastq.gz", "fastq fastq fastq", 37892727491.0, 298367933.0, "ControlA S1 L003 I1 001.fastq.gz", "0:8 1:28 2:91", "A:7386602298;C:6174680460;G:6579652828;T:6955791213;N:54755104", 8, 28, 91, null, 7386602298, 6174680460, 6579652828, 6955791213, 54755104, "SRX18683718", "SRS16126886", "SRA1558824", "The University of Hong Kong|Department of Medicine", "The University of Hong Kong", 1, 0.81686, null, 0.11049, null, 0.84139, null, 0.46084, null, 91, null, "B", null, "usable mapping rate", "bgi", "bgi", "unknown", "random_priming", "unknown", "sc", "single_cell_droplet", "10x", null, "China", "2022-12-14", "Adult", "Adult", "Kidney", "Renal System"]], "truncated": false, 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