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The samples were centrifuged at 400 g for 5 minutes and the digestion buffer was removed. Cells were resuspended in 1 mL wash buffer .1\\% BSA in PBS per tube; filtered through a 40 um cell strainer; centrifuged for 5 minutes at 400 g; and resuspended in 30 50 ul wash buffer. Cell density was estimated by counting on a hemocytometer prior to loading into a 10X Genomics lane. The 10X Genomics Chromium three prime platform and reagents v3.1 kit was used for cell encapsulation reverse transcription and library preparation according to manufacturer instructions manual revision D with 12 cycles of preamplification. For cell encapsulation one lane of the 10X chip was used for each treatment group LPS and control at a target of 16 000 cells/lane.", null, "tissue:Body|genotype:AB|age:6 dpf|treatment:control", "GSM8703960", "GSM8703960: Control 10hr; Danio rerio; RNA Seq", "GSM8703960 r1", "GSM8703960", "1", "Collected tissue was transferred to 300 uL of digestion buffer Final concentration .12 mg/mL Liberase TL Millipore Sigma 5401020001 and 22.5 U/mL DNAse I Worthington LS006331 in .25\\% Trypsin/EDTA Gibco 25200 056 in an eppendorf tube. The tube was placed on a heat block at 30 C for 6 minutes and a P1000 pipette was used to triturate. The samples were centrifuged at 400 g for 5 minutes and the digestion buffer was removed. Cells were resuspended in 1 mL wash buffer .1\\% BSA in PBS per tube; filtered through a 40 um cell strainer; centrifuged for 5 minutes at 400 g; and resuspended in 30 50 ul wash buffer. 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For cell encapsulation one lane of the 10X chip was used for each treatment group LPS and control at a target of 16 000 cells/lane.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP554457", null, "loader:fastq load.py", "Control_S12_L004_I1_001.fastq.gz Control_S12_L004_R1_001.fastq.gz Control_S12_L004_R2_001.fastq.gz", "fastq fastq fastq", 55438180589.0, 436521107.0, "GSM8703960 r4", "0:8 1:28 2:91", "A:11203472019;C:8826429348;G:9895249162;T:9793520783;N:4749425", 8, 28, 91, null, 11203472019, 8826429348, 9895249162, 9793520783, 4749425, "SRX27213775", "SRS23662882", "SRA2042619", "Jerison, Physics, University of Chicago", "Jerison, Physics, University of Chicago", null, null, null, null, null, null, null, null, null, null, null, "B", null, "usable mapping rate", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-12-30", "Larval", "Larval", "Trunk", "Surface Structure"], [34504, "SRR31853999", "SRX27213774", "SRS23662881", "SRP554457", "PRJNA1204318", "Spatially structured inflammatory response in the presence of a uniform stimulus: RNAseq screen", "GSE285534", "Transcriptome Analysis", "Inflammatory responses occur within the complex spatial context of tissues and organs and many questions remain about how tissue structure and cellular communication shape their spatiotemporal dynamics. Here we used single cell RNA sequencing to screen for genes differentially expressed under LPS lipopolysaccharide and vehicle control conditions in epithelial cells in zebrafish larvae. We used this data to choose candidate genes for spatial gene expression analysis. Overall design: 6 dpf AB zebrafish larvae were immersed in either E3 with 37.5 LPS P. Aeuruginosa Sigma or E3 alone vehicle control for 9.5 hours at room temperature. Tail regions from12 larvae per treatment group were pooled and dissociated. The 10X Genomics Chromium three prime platform and reagents v3.1 kit was used for cell encapsulation reverse transcription and library preparation according to manufacturer instructions manual revision D with 12 cycles of preamplification.", null, null, null, "LPS 10hr", "GSM8703959", null, "source name:Body|tissue:Body|genotype:AB|age:6 dpf|treatment:LPS|geo loc name:missing|collection date:missing", "LPS 10hr", "Sequencing data was aligned to the zebrafish reference genome GRCz11 using 10X Genomics Cellranger software 6.1.2. Assembly: GRCz11 Supplementary files format and content: Tab separated values files and matrix files", "Body", null, "Collected tissue was transferred to 300 uL of digestion buffer Final concentration .12 mg/mL Liberase TL Millipore Sigma 5401020001 and 22.5 U/mL DNAse I Worthington LS006331 in .25\\% Trypsin/EDTA Gibco 25200 056 in an eppendorf tube. The tube was placed on a heat block at 30 C for 6 minutes and a P1000 pipette was used to triturate. The samples were centrifuged at 400 g for 5 minutes and the digestion buffer was removed. Cells were resuspended in 1 mL wash buffer .1\\% BSA in PBS per tube; filtered through a 40 um cell strainer; centrifuged for 5 minutes at 400 g; and resuspended in 30 50 ul wash buffer. Cell density was estimated by counting on a hemocytometer prior to loading into a 10X Genomics lane. The 10X Genomics Chromium three prime platform and reagents v3.1 kit was used for cell encapsulation reverse transcription and library preparation according to manufacturer instructions manual revision D with 12 cycles of preamplification. For cell encapsulation one lane of the 10X chip was used for each treatment group LPS and control at a target of 16 000 cells/lane.", null, "tissue:Body|genotype:AB|age:6 dpf|treatment:LPS", "GSM8703959", "GSM8703959: LPS 10hr; Danio rerio; RNA Seq", "GSM8703959 r1", "GSM8703959", "1", "Collected tissue was transferred to 300 uL of digestion buffer Final concentration .12 mg/mL Liberase TL Millipore Sigma 5401020001 and 22.5 U/mL DNAse I Worthington LS006331 in .25\\% Trypsin/EDTA Gibco 25200 056 in an eppendorf tube. The tube was placed on a heat block at 30 C for 6 minutes and a P1000 pipette was used to triturate. The samples were centrifuged at 400 g for 5 minutes and the digestion buffer was removed. Cells were resuspended in 1 mL wash buffer .1\\% BSA in PBS per tube; filtered through a 40 um cell strainer; centrifuged for 5 minutes at 400 g; and resuspended in 30 50 ul wash buffer. Cell density was estimated by counting on a hemocytometer prior to loading into a 10X Genomics lane. The 10X Genomics Chromium three prime platform and reagents v3.1 kit was used for cell encapsulation reverse transcription and library preparation according to manufacturer instructions manual revision D with 12 cycles of preamplification. For cell encapsulation one lane of the 10X chip was used for each treatment group LPS and control at a target of 16 000 cells/lane.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP554457", null, "loader:fastq load.py", "LPS_S11_L001_I1_001.fastq.gz LPS_S11_L001_R1_001.fastq.gz LPS_S11_L001_R2_001.fastq.gz", "fastq fastq fastq", 27204594943.0, 214209409.0, "GSM8703959 r1", "0:8 1:28 2:91", "A:5353386805;C:4418850048;G:5242873068;T:4476300884;N:1645414", 8, 28, 91, null, 5353386805, 4418850048, 5242873068, 4476300884, 1645414, "SRX27213774", "SRS23662881", "SRA2042619", "Jerison, Physics, University of Chicago", "Jerison, Physics, University of Chicago", null, null, null, null, null, null, null, null, null, null, null, "B", null, "usable mapping rate", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-12-30", "Larval", "Larval", "Trunk", "Surface Structure"], [34505, "SRR31854000", "SRX27213774", "SRS23662881", "SRP554457", "PRJNA1204318", "Spatially structured inflammatory response in the presence of a uniform stimulus: RNAseq screen", "GSE285534", "Transcriptome Analysis", "Inflammatory responses occur within the complex spatial context of tissues and organs and many questions remain about how tissue structure and cellular communication shape their spatiotemporal dynamics. Here we used single cell RNA sequencing to screen for genes differentially expressed under LPS lipopolysaccharide and vehicle control conditions in epithelial cells in zebrafish larvae. We used this data to choose candidate genes for spatial gene expression analysis. Overall design: 6 dpf AB zebrafish larvae were immersed in either E3 with 37.5 LPS P. Aeuruginosa Sigma or E3 alone vehicle control for 9.5 hours at room temperature. Tail regions from12 larvae per treatment group were pooled and dissociated. The 10X Genomics Chromium three prime platform and reagents v3.1 kit was used for cell encapsulation reverse transcription and library preparation according to manufacturer instructions manual revision D with 12 cycles of preamplification.", null, null, null, "LPS 10hr", "GSM8703959", null, "source name:Body|tissue:Body|genotype:AB|age:6 dpf|treatment:LPS|geo loc name:missing|collection date:missing", "LPS 10hr", "Sequencing data was aligned to the zebrafish reference genome GRCz11 using 10X Genomics Cellranger software 6.1.2. Assembly: GRCz11 Supplementary files format and content: Tab separated values files and matrix files", "Body", null, "Collected tissue was transferred to 300 uL of digestion buffer Final concentration .12 mg/mL Liberase TL Millipore Sigma 5401020001 and 22.5 U/mL DNAse I Worthington LS006331 in .25\\% Trypsin/EDTA Gibco 25200 056 in an eppendorf tube. The tube was placed on a heat block at 30 C for 6 minutes and a P1000 pipette was used to triturate. The samples were centrifuged at 400 g for 5 minutes and the digestion buffer was removed. Cells were resuspended in 1 mL wash buffer .1\\% BSA in PBS per tube; filtered through a 40 um cell strainer; centrifuged for 5 minutes at 400 g; and resuspended in 30 50 ul wash buffer. Cell density was estimated by counting on a hemocytometer prior to loading into a 10X Genomics lane. The 10X Genomics Chromium three prime platform and reagents v3.1 kit was used for cell encapsulation reverse transcription and library preparation according to manufacturer instructions manual revision D with 12 cycles of preamplification. For cell encapsulation one lane of the 10X chip was used for each treatment group LPS and control at a target of 16 000 cells/lane.", null, "tissue:Body|genotype:AB|age:6 dpf|treatment:LPS", "GSM8703959", "GSM8703959: LPS 10hr; Danio rerio; RNA Seq", "GSM8703959 r1", "GSM8703959", "1", "Collected tissue was transferred to 300 uL of digestion buffer Final concentration .12 mg/mL Liberase TL Millipore Sigma 5401020001 and 22.5 U/mL DNAse I Worthington LS006331 in .25\\% Trypsin/EDTA Gibco 25200 056 in an eppendorf tube. The tube was placed on a heat block at 30 C for 6 minutes and a P1000 pipette was used to triturate. The samples were centrifuged at 400 g for 5 minutes and the digestion buffer was removed. Cells were resuspended in 1 mL wash buffer .1\\% BSA in PBS per tube; filtered through a 40 um cell strainer; centrifuged for 5 minutes at 400 g; and resuspended in 30 50 ul wash buffer. Cell density was estimated by counting on a hemocytometer prior to loading into a 10X Genomics lane. The 10X Genomics Chromium three prime platform and reagents v3.1 kit was used for cell encapsulation reverse transcription and library preparation according to manufacturer instructions manual revision D with 12 cycles of preamplification. For cell encapsulation one lane of the 10X chip was used for each treatment group LPS and control at a target of 16 000 cells/lane.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP554457", null, "loader:fastq load.py", "LPS_S11_L002_I1_001.fastq.gz LPS_S11_L002_R1_001.fastq.gz LPS_S11_L002_R2_001.fastq.gz", "fastq fastq fastq", 27514945859.0, 216653117.0, "GSM8703959 r2", "0:8 1:28 2:91", "A:5407507765;C:4472892263;G:5312032344;T:4520956753;N:2044522", 8, 28, 91, null, 5407507765, 4472892263, 5312032344, 4520956753, 2044522, "SRX27213774", "SRS23662881", "SRA2042619", "Jerison, Physics, University of Chicago", "Jerison, Physics, University of Chicago", null, null, null, null, null, null, null, null, null, null, null, "B", null, "usable mapping rate", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-12-30", "Larval", "Larval", "Trunk", "Surface Structure"], [34506, "SRR31854001", "SRX27213774", "SRS23662881", "SRP554457", "PRJNA1204318", "Spatially structured inflammatory response in the presence of a uniform stimulus: RNAseq screen", "GSE285534", "Transcriptome Analysis", "Inflammatory responses occur within the complex spatial context of tissues and organs and many questions remain about how tissue structure and cellular communication shape their spatiotemporal dynamics. Here we used single cell RNA sequencing to screen for genes differentially expressed under LPS lipopolysaccharide and vehicle control conditions in epithelial cells in zebrafish larvae. We used this data to choose candidate genes for spatial gene expression analysis. Overall design: 6 dpf AB zebrafish larvae were immersed in either E3 with 37.5 LPS P. Aeuruginosa Sigma or E3 alone vehicle control for 9.5 hours at room temperature. Tail regions from12 larvae per treatment group were pooled and dissociated. The 10X Genomics Chromium three prime platform and reagents v3.1 kit was used for cell encapsulation reverse transcription and library preparation according to manufacturer instructions manual revision D with 12 cycles of preamplification.", null, null, null, "LPS 10hr", "GSM8703959", null, "source name:Body|tissue:Body|genotype:AB|age:6 dpf|treatment:LPS|geo loc name:missing|collection date:missing", "LPS 10hr", "Sequencing data was aligned to the zebrafish reference genome GRCz11 using 10X Genomics Cellranger software 6.1.2. Assembly: GRCz11 Supplementary files format and content: Tab separated values files and matrix files", "Body", null, "Collected tissue was transferred to 300 uL of digestion buffer Final concentration .12 mg/mL Liberase TL Millipore Sigma 5401020001 and 22.5 U/mL DNAse I Worthington LS006331 in .25\\% Trypsin/EDTA Gibco 25200 056 in an eppendorf tube. The tube was placed on a heat block at 30 C for 6 minutes and a P1000 pipette was used to triturate. The samples were centrifuged at 400 g for 5 minutes and the digestion buffer was removed. Cells were resuspended in 1 mL wash buffer .1\\% BSA in PBS per tube; filtered through a 40 um cell strainer; centrifuged for 5 minutes at 400 g; and resuspended in 30 50 ul wash buffer. Cell density was estimated by counting on a hemocytometer prior to loading into a 10X Genomics lane. The 10X Genomics Chromium three prime platform and reagents v3.1 kit was used for cell encapsulation reverse transcription and library preparation according to manufacturer instructions manual revision D with 12 cycles of preamplification. For cell encapsulation one lane of the 10X chip was used for each treatment group LPS and control at a target of 16 000 cells/lane.", null, "tissue:Body|genotype:AB|age:6 dpf|treatment:LPS", "GSM8703959", "GSM8703959: LPS 10hr; Danio rerio; RNA Seq", "GSM8703959 r1", "GSM8703959", "1", "Collected tissue was transferred to 300 uL of digestion buffer Final concentration .12 mg/mL Liberase TL Millipore Sigma 5401020001 and 22.5 U/mL DNAse I Worthington LS006331 in .25\\% Trypsin/EDTA Gibco 25200 056 in an eppendorf tube. The tube was placed on a heat block at 30 C for 6 minutes and a P1000 pipette was used to triturate. The samples were centrifuged at 400 g for 5 minutes and the digestion buffer was removed. Cells were resuspended in 1 mL wash buffer .1\\% BSA in PBS per tube; filtered through a 40 um cell strainer; centrifuged for 5 minutes at 400 g; and resuspended in 30 50 ul wash buffer. Cell density was estimated by counting on a hemocytometer prior to loading into a 10X Genomics lane. The 10X Genomics Chromium three prime platform and reagents v3.1 kit was used for cell encapsulation reverse transcription and library preparation according to manufacturer instructions manual revision D with 12 cycles of preamplification. For cell encapsulation one lane of the 10X chip was used for each treatment group LPS and control at a target of 16 000 cells/lane.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP554457", null, "loader:fastq load.py", "LPS_S11_L003_I1_001.fastq.gz LPS_S11_L003_R1_001.fastq.gz LPS_S11_L003_R2_001.fastq.gz", "fastq fastq fastq", 28512338962.0, 224506606.0, "GSM8703959 r3", "0:8 1:28 2:91", "A:5590192273;C:4644899622;G:5516199030;T:4676442556;N:2367665", 8, 28, 91, null, 5590192273, 4644899622, 5516199030, 4676442556, 2367665, "SRX27213774", "SRS23662881", "SRA2042619", "Jerison, Physics, University of Chicago", "Jerison, Physics, University of Chicago", null, null, null, null, null, null, null, null, null, null, null, "B", null, "usable mapping rate", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-12-30", "Larval", "Larval", "Trunk", "Surface Structure"], [34507, "SRR31854002", "SRX27213774", "SRS23662881", "SRP554457", "PRJNA1204318", "Spatially structured inflammatory response in the presence of a uniform stimulus: RNAseq screen", "GSE285534", "Transcriptome Analysis", "Inflammatory responses occur within the complex spatial context of tissues and organs and many questions remain about how tissue structure and cellular communication shape their spatiotemporal dynamics. Here we used single cell RNA sequencing to screen for genes differentially expressed under LPS lipopolysaccharide and vehicle control conditions in epithelial cells in zebrafish larvae. We used this data to choose candidate genes for spatial gene expression analysis. Overall design: 6 dpf AB zebrafish larvae were immersed in either E3 with 37.5 LPS P. Aeuruginosa Sigma or E3 alone vehicle control for 9.5 hours at room temperature. Tail regions from12 larvae per treatment group were pooled and dissociated. The 10X Genomics Chromium three prime platform and reagents v3.1 kit was used for cell encapsulation reverse transcription and library preparation according to manufacturer instructions manual revision D with 12 cycles of preamplification.", null, null, null, "LPS 10hr", "GSM8703959", null, "source name:Body|tissue:Body|genotype:AB|age:6 dpf|treatment:LPS|geo loc name:missing|collection date:missing", "LPS 10hr", "Sequencing data was aligned to the zebrafish reference genome GRCz11 using 10X Genomics Cellranger software 6.1.2. Assembly: GRCz11 Supplementary files format and content: Tab separated values files and matrix files", "Body", null, "Collected tissue was transferred to 300 uL of digestion buffer Final concentration .12 mg/mL Liberase TL Millipore Sigma 5401020001 and 22.5 U/mL DNAse I Worthington LS006331 in .25\\% Trypsin/EDTA Gibco 25200 056 in an eppendorf tube. The tube was placed on a heat block at 30 C for 6 minutes and a P1000 pipette was used to triturate. The samples were centrifuged at 400 g for 5 minutes and the digestion buffer was removed. Cells were resuspended in 1 mL wash buffer .1\\% BSA in PBS per tube; filtered through a 40 um cell strainer; centrifuged for 5 minutes at 400 g; and resuspended in 30 50 ul wash buffer. Cell density was estimated by counting on a hemocytometer prior to loading into a 10X Genomics lane. The 10X Genomics Chromium three prime platform and reagents v3.1 kit was used for cell encapsulation reverse transcription and library preparation according to manufacturer instructions manual revision D with 12 cycles of preamplification. For cell encapsulation one lane of the 10X chip was used for each treatment group LPS and control at a target of 16 000 cells/lane.", null, "tissue:Body|genotype:AB|age:6 dpf|treatment:LPS", "GSM8703959", "GSM8703959: LPS 10hr; Danio rerio; RNA Seq", "GSM8703959 r1", "GSM8703959", "1", "Collected tissue was transferred to 300 uL of digestion buffer Final concentration .12 mg/mL Liberase TL Millipore Sigma 5401020001 and 22.5 U/mL DNAse I Worthington LS006331 in .25\\% Trypsin/EDTA Gibco 25200 056 in an eppendorf tube. The tube was placed on a heat block at 30 C for 6 minutes and a P1000 pipette was used to triturate. The samples were centrifuged at 400 g for 5 minutes and the digestion buffer was removed. Cells were resuspended in 1 mL wash buffer .1\\% BSA in PBS per tube; filtered through a 40 um cell strainer; centrifuged for 5 minutes at 400 g; and resuspended in 30 50 ul wash buffer. Cell density was estimated by counting on a hemocytometer prior to loading into a 10X Genomics lane. The 10X Genomics Chromium three prime platform and reagents v3.1 kit was used for cell encapsulation reverse transcription and library preparation according to manufacturer instructions manual revision D with 12 cycles of preamplification. For cell encapsulation one lane of the 10X chip was used for each treatment group LPS and control at a target of 16 000 cells/lane.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP554457", null, "loader:fastq load.py", "LPS_S11_L004_I1_001.fastq.gz LPS_S11_L004_R1_001.fastq.gz LPS_S11_L004_R2_001.fastq.gz", "fastq fastq fastq", 27411098848.0, 215835424.0, "GSM8703959 r4", "0:8 1:28 2:91", "A:5383218071;C:4459553243;G:5297438054;T:4498601355;N:2212861", 8, 28, 91, null, 5383218071, 4459553243, 5297438054, 4498601355, 2212861, "SRX27213774", "SRS23662881", "SRA2042619", "Jerison, Physics, University of Chicago", "Jerison, Physics, University of Chicago", null, null, null, null, null, null, null, null, null, null, null, "B", null, "usable mapping rate", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2024-12-30", "Larval", "Larval", "Trunk", "Surface Structure"], [36242, "SRR33873799", "SRX29085358", "SRS25297146", "SRP590547", "PRJNA1272846", "Organism wide contributions to systemic skeletal muscle repair in larval zebrafish.", "GSE299146", "Transcriptome Analysis", "We developed a systemic muscle injury model in zebrafish. Single cell transcriptomic analysis of muscle and non muscle tissues revealed that systemic and local muscle injuries elicit distinct cellular molecular responses both quantitatively and qualitatively. These studies suggest that large and small scale muscle injuries activate different regenerative programs resulting in either systemic or local repair. Overall design: To characterize the regenerative responses and signaling pathways activated post systemic or local muscle injury we generated Tgactc1b:NTR mCherry transgenic zebrafish lines.At 4 dpf transgenic larvae were treated with MTZ overnight to systemically injure all myofibers or were subjected to local mechanical injury needlestick of 2 3 somites.Uninjured and systemically injured larvae were collected at 1 2 and 4 xxx post injury. Mechanically injured larvae were collected at 2 xxx post injury. Sequencing results were compared between uninjured systemically injured and mechanically injured siblings.", null, null, null, "larval trunk 2dpi Needle Stick", "GSM9034433", null, "source name:Trunk|tissue:Trunk|genotype:Tgactc1b:NTR mCherry|treatment:Needle Stick|batch:4/20/2022|geo loc name:missing|collection date:missing", "larval trunk 2dpi Needle Stick", "post sequencing the Illumina output was processed using the CellRanger v8.0.1 pipeline to generate gene barcode count matrices. A custom reference genome was made with the \u201ccellranger mkref\u201d command using the fasta file of zebrafish reference genome GRCz11 constructed from the Ensemble genome build https://useast.ensembl.org/Danio rerio/Info/Index and the sorted Gene Transfer Format file v4.3.2 from the improved zebrafish transcriptome annotation Lawson et al. 2020. Base call files for each sample from Illumina were demultiplexed into FASTQ reads. Then the \u201ccellranger count\u201d pipeline was used to align sequencing reads in FASTQ files to the custom reference genome. Both exon and intron sequences were included during the alignment. The filtered gene barcode count matrices generated by \u201ccellranger count\u201d was used for downstream analysis. Datasets were integrated and analyzed using Seurat v4.4.0 package with R v4.4.2Stuart etal. 2019; Team 2024. Each sample count matrix was filtered for genes that were expressed in at least 3 cells and cells expressing at least 200 genes followed by cell quality assessment usingcommonly used QC matrixes Ilicic et al. 2016. Cells having a unique number of genes between 200 and 6500 mitochondrial gene percentage <5 and total number of reads UMIs between 300and 35000 were used for downstream processing. Each dataset was independently normalizedand scaled using the \u201cSCTransform\u201d function which is an improved method for normalization that performs a variance stabilizing transformation using negative binomial regression Hafemeisterand Satija 2019. Standard integration workflow of Seurat was used to identify shared sources of variation across experiments as well as mutual nearest neighbors Butler et al. 2018; Haghverdiet al. 2018. Integration features were selected based on the top 6000 highly variable features using \u201cSelectIntegrationFeatures\u201d function nfeatures\u2009=\u20096000 which was used as input for the\u201canchor.features\u201d argument of the \u201cFindIntegrationAnchors\u201d function. PCA analysis was performed on the 6000 variable features and the top 50 principal components selected based on the elbow plot heuristic which measures the contribution of variation in each component. These 50 principal components were used in \u201cFindNeighbors\u201d and \u201cFindClusters\u201d functions to perform graph based clustering on a shared nearest neighbor graph Levine et al. 2015; Xu and Su 2015. Louvain algorithm was used for modularity optimization in cell clustering using \u201cFindClusters\u201d function. The resolution parameter res\u2009=\u20090.3 that determines the granularity of clusteringwas selected by visually inspecting clusters with resolutions ranging between 0.1 and 2.0 as well as clustree graph Zappia and Oshlack 2018. Uniform Manifold Approximation and Reduction UMAP was used for non linear dimensional reduction of the first 50 principal components and visualize the data using \u201cRunUMAP\u201d function Becht et al. 2018. Data was graphed using different plot functions such as \u201cDimPlot\u201d \u201cVlnPlot\u201d \u201cFeaturePlot\u201d \u201cDotplot\u201d and \u201cDoHeatmap\u201d to view the cell cluster identity and marker gene expression. Cell proportions were extracted using the \u201ctable\u201d and \u201cprop.table\u201d functions. Differential gene expression for individual clusters was identified using Wilcoxon rank sum test in the \u201cFindAllMarkers\u201d function. Marker genes detected in at least 25% of the clustered cells and had a positive average log2FC were reported. Muscle cells identified from the complete dataset were subclustered using the \u201csubset\u201d function for subcluster analysis. The muscle subset was again normalized and scaled using the \u201cSCTransform\u201d function with glmGamPoi method Ahlmann Eltze and Huber 2021. Fifty principal components were used and the resolution parameter was set to 0.4. Downstream analysis was done as described above for the integrated analysis. We used a zebrafish single atlas Sur et al. 2023 to generate a database of markers for each tissue and cell type Table S1. The differentially expressed markers of each cluster were crossreferenced with our compiled database using our \u201cDE Marker Scoring\u201d algorithm Saraswathy et al. 2024. For every matching marker gene one point was given to the respective cluster under the column name with matching cell identity. Iteration over every marker gene was performed to generate a scoring matrix with varying points for each cluster against the different cell identities compiled in the database Table S2 sheet: scoring. The \u201cphyper\u201d function in R was then used to calculate one tailed binomial probabilities using hypergeometric distribution for the total score obtained from each cluster against each cell identity in the database Table S2 sheet: Binomial probability. \u2212log10 of probability values were obtained for plotting the heatmap Table S2 sheet:\u2212log10P. The resulting values were scaled from 0 to 100 and plotted as a heatmap using GraphPad prism. Each cluster was given an identity based on the maximum \u2212log10 p score obtained in the heatmap. The top DE markers of clusters with ambiguous scores were manually annotated using the \u201cident genes\u201d from the zebrafish single atlas Sur et al. 2023 and literature search McKellar et al. 2021. Top DE markers generated for each cluster is given in Table S3 sheet:topDEmarkers.all.clusters \u201cRenameIdents\u201d function was used to assign identity to each cluster. To confirm the assigned cluster identities enrichment of classical markers of respective cell types were tested using Dot plot. The R package CellChat v2.1.2 was used to evaluate regenerative cell cell interactions post local and systemic muscle injury Jin et al. 2021. CellChat models the probability of cell cell communication by integrating our gene expression data with a database of known interaction between signaling ligands receptors and their cofactors CellChatDB. The RNA data was used to create CellChat object using \u201ccreateCellChat\u201d function followed by the recommended preprocessing functions with default parameters for the analysis of individual datasets. Truncated mean method with 10% trimmed observation was used to compute average gene expression per cell group for the complete dataset. The default trimean method was used to compute average gene expression for the CellChat analysis. CellChatDB.zebrafish was used to infer cell cell communication. All categories of ligand receptor interactions in the database were used in the analysis. Communications involving less than 10 cells were excluded. The \u201cnetAnalysis computeCentrality\u201d function was used to calculate network centrality scores at each time point. Functions such as \u201cnetVisual circle\u201d \u201cnetAnalysis contribution\u201d \u201cnetVisual aggregate\u201d \u201cnetVisual bubble\u201d \u201cnetAnalysis signalingRole heatmap\u201d and \u201cnetAnalysis signalingRole scatter\u201d were used to generate different plots used in this paper. Assembly: zebrafish reference genome GRCz11 and the sorted Gene Transfer Format file v4.3.2 from the improved zebrafish transcriptome annotation Lawson et al. 2020. Supplementary files format and content: Compressed Filtered Feature and Barcode files as .tsv file and count matrices in .mtx file format.", "Trunk", "Fish were treated with 12 hours of metronidazole or were stuck locally with a needle", "15 larvae per cohort were dissected to remove the head caudal fin and internal organs and then processed as described Farnsworth DB 459 2020. For tissue lysis 500\u03bcL of dissociation buffer 2ug/ul Collagenase P 2mM CaCl2 0.2 ul DNaseI 0.25% Trypsin in 1X PBS was added to the samples and incubated at 28 \u00b0C until samples were visually dissociated 15min. Dissociation was stopped with equal volume of stop buffer 10% FBS 0.001mM EDTA in 1X PBS. Samples were centrifuged at 750rcf for 7min at 4\u00b0C the supernatant was discarded and the pellet was resuspended in 100\u03bcL of resuspension buffer 1% FBS 2mM CaCl2 1X Penicillin/Streptomycin in DMEM. The suspension was strained through 20\u03bcm cell strainer Pluriselect USA 43 10020 40 centrifuged once 500rcf 1 min 4\u00b0C to pass cells through the strainer and centrifuged a second time 750rcf 7 min 4\u00b0C to pellet the cells. The cells were resuspended in 100\u03bcL of resuspension buffer centrifugated 750rcf 7min 4\u00b0C and the pellet was resuspended in 50\u03bcL 0.04% BSA in PBS. 5\u03bcl of cells were then combined with 5\u03bcl of Hoechst Invitrogen H3570 incubated for 10min and transferred to a hemocytometer Bulldogbio NC1731934 to determine cell concentration. An additional 5\u03bcl of cells were incubated with Trypan blue Sigma T8154 for 5min transferred to a hemocytometer and counted to assess cell viability. Samples with > 70% viability were then submitted for single cell sequencing. For snRNA seq 30 \u00b5l of isolated nuclei at a concentration of 1000 nuclei/\u00b5l was submitted to Genome Technology Access Center at McDonnel Genome Institute of Washington University. Two biological replicates of each genotype were used. cDNA was prepared post the GEM generation and barcoding followed by the GEM RT reaction and bead cleanup steps. cDNA was amplified for 11 13 cycles then purified using SPRIselect beads. Purified cDNA samples were then run on a Bioanalyzer to determine the cDNA concentration. GEX libraries were prepared as recommended by the 10x Genomics Chromium Single Cell 3\u2019 Reagent Kits User Guide v3.1 Chemistry Dual Index with appropriate modifications to the PCR cycles based on the calculated cDNA concentration. For sample preparation on the 10x Genomics platform the Chromium Next GEM Single Cell 3\u2019 Kit v3.1 16 rxns PN 1000268 Chromium Next GEM Chip G Single Cell Kit 48 rxns PN 1000120 and Dual Index Kit TT Set A 96 rxns PN 1000215 were used. The concentration of each library was accurately determined through qPCR utilizing the KAPA library Quantification Kit according to the manufacturer\u2019s protocol KAPA Biosystems/Roche to produce cluster counts appropriate for the Illumina NovaSeq6000 instrument. Normalized libraries were sequenced on a NovaSeq6000 S4 Flow Cell using the XP workflow and a 50x10x16x150 sequencing recipe according to manufacturer protocol. A median sequencing depth of 50 000 reads/cell was targeted for each Gene Expression Library.", "Larval zebrafish of 4 dpf underwent drug treatments or needle stick injuries for muscle ablation", "tissue:Trunk|genotype:Tgactc1b:NTR mCherry|treatment:Needle Stick|batch:4/20/2022", "GSM9034433", "GSM9034433: larval trunk 2dpi Needle Stick; Danio rerio; RNA Seq", "GSM9034433 r1", "GSM9034433", "1", "15 larvae per cohort were dissected to remove the head caudal fin and internal organs and then processed as described Farnsworth DB 459 2020. For tissue lysis 500\u03bcL of dissociation buffer 2ug/ul Collagenase P 2mM CaCl2 0.2 ul DNaseI 0.25% Trypsin in 1X PBS was added to the samples and incubated at 28 \u00b0C until samples were visually dissociated 15min. Dissociation was stopped with equal volume of stop buffer 10% FBS 0.001mM EDTA in 1X PBS. Samples were centrifuged at 750rcf for 7min at 4\u00b0C the supernatant was discarded and the pellet was resuspended in 100\u03bcL of resuspension buffer 1% FBS 2mM CaCl2 1X Penicillin/Streptomycin in DMEM. The suspension was strained through 20\u03bcm cell strainer Pluriselect USA 43 10020 40 centrifuged once 500rcf 1 min 4\u00b0C to pass cells through the strainer and centrifuged a second time 750rcf 7 min 4\u00b0C to pellet the cells. The cells were resuspended in 100\u03bcL of resuspension buffer centrifugated 750rcf 7min 4\u00b0C and the pellet was resuspended in 50\u03bcL 0.04% BSA in PBS. 5\u03bcl of cells were then combined with 5\u03bcl of Hoechst Invitrogen H3570 incubated for 10min and transferred to a hemocytometer Bulldogbio NC1731934 to determine cell concentration. An additional 5\u03bcl of cells were incubated with Trypan blue Sigma T8154 for 5min transferred to a hemocytometer and counted to assess cell viability. Samples with > 70% viability were then submitted for single cell sequencing. For snRNA seq 30 \u00b5l of isolated nuclei at a concentration of 1000 nuclei/\u00b5l was submitted to Genome Technology Access Center at McDonnel Genome Institute of Washington University. Two biological replicates of each genotype were used. cDNA was prepared post the GEM generation and barcoding followed by the GEM RT reaction and bead cleanup steps. cDNA was amplified for 11 13 cycles then purified using SPRIselect beads. Purified cDNA samples were then run on a Bioanalyzer to determine the cDNA concentration. GEX libraries were prepared as recommended by the 10x Genomics Chromium Single Cell three prime Reagent Kits User Guide v3.1 Chemistry Dual Index with appropriate modifications to the PCR cycles based on the calculated cDNA concentration. For sample preparation on the 10x Genomics platform the Chromium Next GEM Single Cell three prime Kit v3.1 16 rxns PN 1000268 Chromium Next GEM Chip G Single Cell Kit 48 rxns PN 1000120 and Dual Index Kit TT Set A 96 rxns PN 1000215 were used. The concentration of each library was accurately determined through qPCR utilizing the KAPA library Quantification Kit according to the manufacturer's protocol KAPA Biosystems/Roche to produce cluster counts appropriate for the Illumina NovaSeq6000 instrument. Normalized libraries were sequenced on a NovaSeq6000 S4 Flow Cell using the XP workflow and a 50x10x16x150 sequencing recipe according to manufacturer protocol. A median sequencing depth of 50 000 reads/cell was targeted for each Gene Expression Library.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP590547", null, null, "AJAH-ACTC_NTR_Mcherry-Needlestick-2dpi-NS-2dpi-lib1_S1_L003_R1_001.fastq.gz AJAH-ACTC_NTR_Mcherry-Needlestick-2dpi-NS-2dpi-lib1_S1_L003_R2_001.fastq.gz", "fastq fastq", 73442728978.0, 412599601.0, "GSM9034433 r1", "0:28 1:150", "A:21212027449;C:16424751525;G:17879456991;T:17925559458;N:933555", 28, 150, null, null, 21212027449, 16424751525, 17879456991, 17925559458, 933555, "SRX29085358", "SRS25297146", "SRA2144659", "Johnson Lab, Developmental Biology, Washington University in St.Louis", "Johnson Lab, Developmental Biology, Washington University in St.Louis", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2025-06-06", "Larval", "Larval", "Trunk", "Surface Structure"], [36243, "SRR33873800", "SRX29085357", "SRS25297145", "SRP590547", "PRJNA1272846", "Organism wide contributions to systemic skeletal muscle repair in larval zebrafish.", "GSE299146", "Transcriptome Analysis", "We developed a systemic muscle injury model in zebrafish. Single cell transcriptomic analysis of muscle and non muscle tissues revealed that systemic and local muscle injuries elicit distinct cellular molecular responses both quantitatively and qualitatively. These studies suggest that large and small scale muscle injuries activate different regenerative programs resulting in either systemic or local repair. Overall design: To characterize the regenerative responses and signaling pathways activated post systemic or local muscle injury we generated Tgactc1b:NTR mCherry transgenic zebrafish lines.At 4 dpf transgenic larvae were treated with MTZ overnight to systemically injure all myofibers or were subjected to local mechanical injury needlestick of 2 3 somites.Uninjured and systemically injured larvae were collected at 1 2 and 4 xxx post injury. Mechanically injured larvae were collected at 2 xxx post injury. Sequencing results were compared between uninjured systemically injured and mechanically injured siblings.", null, null, null, "larval trunk 4dpi mcherry MTZ", "GSM9034432", null, "source name:Trunk|tissue:Trunk|genotype:Tgactc1b:NTR mCherry|treatment:Fish Water + MTZ|batch:10/28/2022|geo loc name:missing|collection date:missing", "larval trunk 4dpi mcherry MTZ", "post sequencing the Illumina output was processed using the CellRanger v8.0.1 pipeline to generate gene barcode count matrices. A custom reference genome was made with the \u201ccellranger mkref\u201d command using the fasta file of zebrafish reference genome GRCz11 constructed from the Ensemble genome build https://useast.ensembl.org/Danio rerio/Info/Index and the sorted Gene Transfer Format file v4.3.2 from the improved zebrafish transcriptome annotation Lawson et al. 2020. Base call files for each sample from Illumina were demultiplexed into FASTQ reads. Then the \u201ccellranger count\u201d pipeline was used to align sequencing reads in FASTQ files to the custom reference genome. Both exon and intron sequences were included during the alignment. The filtered gene barcode count matrices generated by \u201ccellranger count\u201d was used for downstream analysis. Datasets were integrated and analyzed using Seurat v4.4.0 package with R v4.4.2Stuart etal. 2019; Team 2024. Each sample count matrix was filtered for genes that were expressed in at least 3 cells and cells expressing at least 200 genes followed by cell quality assessment usingcommonly used QC matrixes Ilicic et al. 2016. Cells having a unique number of genes between 200 and 6500 mitochondrial gene percentage <5 and total number of reads UMIs between 300and 35000 were used for downstream processing. Each dataset was independently normalizedand scaled using the \u201cSCTransform\u201d function which is an improved method for normalization that performs a variance stabilizing transformation using negative binomial regression Hafemeisterand Satija 2019. Standard integration workflow of Seurat was used to identify shared sources of variation across experiments as well as mutual nearest neighbors Butler et al. 2018; Haghverdiet al. 2018. Integration features were selected based on the top 6000 highly variable features using \u201cSelectIntegrationFeatures\u201d function nfeatures\u2009=\u20096000 which was used as input for the\u201canchor.features\u201d argument of the \u201cFindIntegrationAnchors\u201d function. PCA analysis was performed on the 6000 variable features and the top 50 principal components selected based on the elbow plot heuristic which measures the contribution of variation in each component. These 50 principal components were used in \u201cFindNeighbors\u201d and \u201cFindClusters\u201d functions to perform graph based clustering on a shared nearest neighbor graph Levine et al. 2015; Xu and Su 2015. Louvain algorithm was used for modularity optimization in cell clustering using \u201cFindClusters\u201d function. The resolution parameter res\u2009=\u20090.3 that determines the granularity of clusteringwas selected by visually inspecting clusters with resolutions ranging between 0.1 and 2.0 as well as clustree graph Zappia and Oshlack 2018. Uniform Manifold Approximation and Reduction UMAP was used for non linear dimensional reduction of the first 50 principal components and visualize the data using \u201cRunUMAP\u201d function Becht et al. 2018. Data was graphed using different plot functions such as \u201cDimPlot\u201d \u201cVlnPlot\u201d \u201cFeaturePlot\u201d \u201cDotplot\u201d and \u201cDoHeatmap\u201d to view the cell cluster identity and marker gene expression. Cell proportions were extracted using the \u201ctable\u201d and \u201cprop.table\u201d functions. Differential gene expression for individual clusters was identified using Wilcoxon rank sum test in the \u201cFindAllMarkers\u201d function. Marker genes detected in at least 25% of the clustered cells and had a positive average log2FC were reported. Muscle cells identified from the complete dataset were subclustered using the \u201csubset\u201d function for subcluster analysis. The muscle subset was again normalized and scaled using the \u201cSCTransform\u201d function with glmGamPoi method Ahlmann Eltze and Huber 2021. Fifty principal components were used and the resolution parameter was set to 0.4. Downstream analysis was done as described above for the integrated analysis. We used a zebrafish single atlas Sur et al. 2023 to generate a database of markers for each tissue and cell type Table S1. The differentially expressed markers of each cluster were crossreferenced with our compiled database using our \u201cDE Marker Scoring\u201d algorithm Saraswathy et al. 2024. For every matching marker gene one point was given to the respective cluster under the column name with matching cell identity. Iteration over every marker gene was performed to generate a scoring matrix with varying points for each cluster against the different cell identities compiled in the database Table S2 sheet: scoring. The \u201cphyper\u201d function in R was then used to calculate one tailed binomial probabilities using hypergeometric distribution for the total score obtained from each cluster against each cell identity in the database Table S2 sheet: Binomial probability. \u2212log10 of probability values were obtained for plotting the heatmap Table S2 sheet:\u2212log10P. The resulting values were scaled from 0 to 100 and plotted as a heatmap using GraphPad prism. Each cluster was given an identity based on the maximum \u2212log10 p score obtained in the heatmap. The top DE markers of clusters with ambiguous scores were manually annotated using the \u201cident genes\u201d from the zebrafish single atlas Sur et al. 2023 and literature search McKellar et al. 2021. Top DE markers generated for each cluster is given in Table S3 sheet:topDEmarkers.all.clusters \u201cRenameIdents\u201d function was used to assign identity to each cluster. To confirm the assigned cluster identities enrichment of classical markers of respective cell types were tested using Dot plot. The R package CellChat v2.1.2 was used to evaluate regenerative cell cell interactions post local and systemic muscle injury Jin et al. 2021. CellChat models the probability of cell cell communication by integrating our gene expression data with a database of known interaction between signaling ligands receptors and their cofactors CellChatDB. The RNA data was used to create CellChat object using \u201ccreateCellChat\u201d function followed by the recommended preprocessing functions with default parameters for the analysis of individual datasets. Truncated mean method with 10% trimmed observation was used to compute average gene expression per cell group for the complete dataset. The default trimean method was used to compute average gene expression for the CellChat analysis. CellChatDB.zebrafish was used to infer cell cell communication. All categories of ligand receptor interactions in the database were used in the analysis. Communications involving less than 10 cells were excluded. The \u201cnetAnalysis computeCentrality\u201d function was used to calculate network centrality scores at each time point. Functions such as \u201cnetVisual circle\u201d \u201cnetAnalysis contribution\u201d \u201cnetVisual aggregate\u201d \u201cnetVisual bubble\u201d \u201cnetAnalysis signalingRole heatmap\u201d and \u201cnetAnalysis signalingRole scatter\u201d were used to generate different plots used in this paper. Assembly: zebrafish reference genome GRCz11 and the sorted Gene Transfer Format file v4.3.2 from the improved zebrafish transcriptome annotation Lawson et al. 2020. Supplementary files format and content: Compressed Filtered Feature and Barcode files as .tsv file and count matrices in .mtx file format.", "Trunk", "Fish were treated with 12 hours of metronidazole or were stuck locally with a needle", "15 larvae per cohort were dissected to remove the head caudal fin and internal organs and then processed as described Farnsworth DB 459 2020. For tissue lysis 500\u03bcL of dissociation buffer 2ug/ul Collagenase P 2mM CaCl2 0.2 ul DNaseI 0.25% Trypsin in 1X PBS was added to the samples and incubated at 28 \u00b0C until samples were visually dissociated 15min. Dissociation was stopped with equal volume of stop buffer 10% FBS 0.001mM EDTA in 1X PBS. Samples were centrifuged at 750rcf for 7min at 4\u00b0C the supernatant was discarded and the pellet was resuspended in 100\u03bcL of resuspension buffer 1% FBS 2mM CaCl2 1X Penicillin/Streptomycin in DMEM. The suspension was strained through 20\u03bcm cell strainer Pluriselect USA 43 10020 40 centrifuged once 500rcf 1 min 4\u00b0C to pass cells through the strainer and centrifuged a second time 750rcf 7 min 4\u00b0C to pellet the cells. The cells were resuspended in 100\u03bcL of resuspension buffer centrifugated 750rcf 7min 4\u00b0C and the pellet was resuspended in 50\u03bcL 0.04% BSA in PBS. 5\u03bcl of cells were then combined with 5\u03bcl of Hoechst Invitrogen H3570 incubated for 10min and transferred to a hemocytometer Bulldogbio NC1731934 to determine cell concentration. An additional 5\u03bcl of cells were incubated with Trypan blue Sigma T8154 for 5min transferred to a hemocytometer and counted to assess cell viability. Samples with > 70% viability were then submitted for single cell sequencing. For snRNA seq 30 \u00b5l of isolated nuclei at a concentration of 1000 nuclei/\u00b5l was submitted to Genome Technology Access Center at McDonnel Genome Institute of Washington University. Two biological replicates of each genotype were used. cDNA was prepared post the GEM generation and barcoding followed by the GEM RT reaction and bead cleanup steps. cDNA was amplified for 11 13 cycles then purified using SPRIselect beads. Purified cDNA samples were then run on a Bioanalyzer to determine the cDNA concentration. GEX libraries were prepared as recommended by the 10x Genomics Chromium Single Cell 3\u2019 Reagent Kits User Guide v3.1 Chemistry Dual Index with appropriate modifications to the PCR cycles based on the calculated cDNA concentration. For sample preparation on the 10x Genomics platform the Chromium Next GEM Single Cell 3\u2019 Kit v3.1 16 rxns PN 1000268 Chromium Next GEM Chip G Single Cell Kit 48 rxns PN 1000120 and Dual Index Kit TT Set A 96 rxns PN 1000215 were used. The concentration of each library was accurately determined through qPCR utilizing the KAPA library Quantification Kit according to the manufacturer\u2019s protocol KAPA Biosystems/Roche to produce cluster counts appropriate for the Illumina NovaSeq6000 instrument. Normalized libraries were sequenced on a NovaSeq6000 S4 Flow Cell using the XP workflow and a 50x10x16x150 sequencing recipe according to manufacturer protocol. A median sequencing depth of 50 000 reads/cell was targeted for each Gene Expression Library.", "Larval zebrafish of 4 dpf underwent drug treatments or needle stick injuries for muscle ablation", "tissue:Trunk|genotype:Tgactc1b:NTR mCherry|treatment:Fish Water + MTZ|batch:10/28/2022", "GSM9034432", "GSM9034432: larval trunk 4dpi mcherry MTZ; Danio rerio; RNA Seq", "GSM9034432 r1", "GSM9034432", "1", "15 larvae per cohort were dissected to remove the head caudal fin and internal organs and then processed as described Farnsworth DB 459 2020. For tissue lysis 500\u03bcL of dissociation buffer 2ug/ul Collagenase P 2mM CaCl2 0.2 ul DNaseI 0.25% Trypsin in 1X PBS was added to the samples and incubated at 28 \u00b0C until samples were visually dissociated 15min. Dissociation was stopped with equal volume of stop buffer 10% FBS 0.001mM EDTA in 1X PBS. Samples were centrifuged at 750rcf for 7min at 4\u00b0C the supernatant was discarded and the pellet was resuspended in 100\u03bcL of resuspension buffer 1% FBS 2mM CaCl2 1X Penicillin/Streptomycin in DMEM. The suspension was strained through 20\u03bcm cell strainer Pluriselect USA 43 10020 40 centrifuged once 500rcf 1 min 4\u00b0C to pass cells through the strainer and centrifuged a second time 750rcf 7 min 4\u00b0C to pellet the cells. The cells were resuspended in 100\u03bcL of resuspension buffer centrifugated 750rcf 7min 4\u00b0C and the pellet was resuspended in 50\u03bcL 0.04% BSA in PBS. 5\u03bcl of cells were then combined with 5\u03bcl of Hoechst Invitrogen H3570 incubated for 10min and transferred to a hemocytometer Bulldogbio NC1731934 to determine cell concentration. An additional 5\u03bcl of cells were incubated with Trypan blue Sigma T8154 for 5min transferred to a hemocytometer and counted to assess cell viability. Samples with > 70% viability were then submitted for single cell sequencing. For snRNA seq 30 \u00b5l of isolated nuclei at a concentration of 1000 nuclei/\u00b5l was submitted to Genome Technology Access Center at McDonnel Genome Institute of Washington University. Two biological replicates of each genotype were used. cDNA was prepared post the GEM generation and barcoding followed by the GEM RT reaction and bead cleanup steps. cDNA was amplified for 11 13 cycles then purified using SPRIselect beads. Purified cDNA samples were then run on a Bioanalyzer to determine the cDNA concentration. GEX libraries were prepared as recommended by the 10x Genomics Chromium Single Cell three prime Reagent Kits User Guide v3.1 Chemistry Dual Index with appropriate modifications to the PCR cycles based on the calculated cDNA concentration. For sample preparation on the 10x Genomics platform the Chromium Next GEM Single Cell three prime Kit v3.1 16 rxns PN 1000268 Chromium Next GEM Chip G Single Cell Kit 48 rxns PN 1000120 and Dual Index Kit TT Set A 96 rxns PN 1000215 were used. The concentration of each library was accurately determined through qPCR utilizing the KAPA library Quantification Kit according to the manufacturer's protocol KAPA Biosystems/Roche to produce cluster counts appropriate for the Illumina NovaSeq6000 instrument. Normalized libraries were sequenced on a NovaSeq6000 S4 Flow Cell using the XP workflow and a 50x10x16x150 sequencing recipe according to manufacturer protocol. A median sequencing depth of 50 000 reads/cell was targeted for each Gene Expression Library.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP590547", null, null, "AJAH-18300_Red-18300_mCherry_Positive_4dpi-lib1_S2_L004_R1_001.fastq.gz AJAH-18300_Red-18300_mCherry_Positive_4dpi-lib1_S2_L004_R2_001.fastq.gz", "fastq fastq", 109491443482.0, 615120469.0, "GSM9034432 r1", "0:28 1:150", "A:31642210635;C:24956118743;G:26943821428;T:25945839682;N:3452994", 28, 150, null, null, 31642210635, 24956118743, 26943821428, 25945839682, 3452994, "SRX29085357", "SRS25297145", "SRA2144659", "Johnson Lab, Developmental Biology, Washington University in St.Louis", "Johnson Lab, Developmental Biology, Washington University in St.Louis", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2025-06-06", "Larval", "Larval", "Trunk", "Surface Structure"], [36244, "SRR33873801", "SRX29085356", "SRS25297144", "SRP590547", "PRJNA1272846", "Organism wide contributions to systemic skeletal muscle repair in larval zebrafish.", "GSE299146", "Transcriptome Analysis", "We developed a systemic muscle injury model in zebrafish. Single cell transcriptomic analysis of muscle and non muscle tissues revealed that systemic and local muscle injuries elicit distinct cellular molecular responses both quantitatively and qualitatively. These studies suggest that large and small scale muscle injuries activate different regenerative programs resulting in either systemic or local repair. Overall design: To characterize the regenerative responses and signaling pathways activated post systemic or local muscle injury we generated Tgactc1b:NTR mCherry transgenic zebrafish lines.At 4 dpf transgenic larvae were treated with MTZ overnight to systemically injure all myofibers or were subjected to local mechanical injury needlestick of 2 3 somites.Uninjured and systemically injured larvae were collected at 1 2 and 4 xxx post injury. Mechanically injured larvae were collected at 2 xxx post injury. Sequencing results were compared between uninjured systemically injured and mechanically injured siblings.", null, null, null, "larval trunk 4dpi Negative Control", "GSM9034431", null, "source name:Trunk|tissue:Trunk|genotype:Tgactc1b:NTR mCherry|treatment:Fish Water|batch:10/28/2022|geo loc name:missing|collection date:missing", "larval trunk 4dpi Negative Control", "post sequencing the Illumina output was processed using the CellRanger v8.0.1 pipeline to generate gene barcode count matrices. A custom reference genome was made with the \u201ccellranger mkref\u201d command using the fasta file of zebrafish reference genome GRCz11 constructed from the Ensemble genome build https://useast.ensembl.org/Danio rerio/Info/Index and the sorted Gene Transfer Format file v4.3.2 from the improved zebrafish transcriptome annotation Lawson et al. 2020. Base call files for each sample from Illumina were demultiplexed into FASTQ reads. Then the \u201ccellranger count\u201d pipeline was used to align sequencing reads in FASTQ files to the custom reference genome. Both exon and intron sequences were included during the alignment. The filtered gene barcode count matrices generated by \u201ccellranger count\u201d was used for downstream analysis. Datasets were integrated and analyzed using Seurat v4.4.0 package with R v4.4.2Stuart etal. 2019; Team 2024. Each sample count matrix was filtered for genes that were expressed in at least 3 cells and cells expressing at least 200 genes followed by cell quality assessment usingcommonly used QC matrixes Ilicic et al. 2016. Cells having a unique number of genes between 200 and 6500 mitochondrial gene percentage <5 and total number of reads UMIs between 300and 35000 were used for downstream processing. Each dataset was independently normalizedand scaled using the \u201cSCTransform\u201d function which is an improved method for normalization that performs a variance stabilizing transformation using negative binomial regression Hafemeisterand Satija 2019. Standard integration workflow of Seurat was used to identify shared sources of variation across experiments as well as mutual nearest neighbors Butler et al. 2018; Haghverdiet al. 2018. Integration features were selected based on the top 6000 highly variable features using \u201cSelectIntegrationFeatures\u201d function nfeatures\u2009=\u20096000 which was used as input for the\u201canchor.features\u201d argument of the \u201cFindIntegrationAnchors\u201d function. PCA analysis was performed on the 6000 variable features and the top 50 principal components selected based on the elbow plot heuristic which measures the contribution of variation in each component. These 50 principal components were used in \u201cFindNeighbors\u201d and \u201cFindClusters\u201d functions to perform graph based clustering on a shared nearest neighbor graph Levine et al. 2015; Xu and Su 2015. Louvain algorithm was used for modularity optimization in cell clustering using \u201cFindClusters\u201d function. The resolution parameter res\u2009=\u20090.3 that determines the granularity of clusteringwas selected by visually inspecting clusters with resolutions ranging between 0.1 and 2.0 as well as clustree graph Zappia and Oshlack 2018. Uniform Manifold Approximation and Reduction UMAP was used for non linear dimensional reduction of the first 50 principal components and visualize the data using \u201cRunUMAP\u201d function Becht et al. 2018. Data was graphed using different plot functions such as \u201cDimPlot\u201d \u201cVlnPlot\u201d \u201cFeaturePlot\u201d \u201cDotplot\u201d and \u201cDoHeatmap\u201d to view the cell cluster identity and marker gene expression. Cell proportions were extracted using the \u201ctable\u201d and \u201cprop.table\u201d functions. Differential gene expression for individual clusters was identified using Wilcoxon rank sum test in the \u201cFindAllMarkers\u201d function. Marker genes detected in at least 25% of the clustered cells and had a positive average log2FC were reported. Muscle cells identified from the complete dataset were subclustered using the \u201csubset\u201d function for subcluster analysis. The muscle subset was again normalized and scaled using the \u201cSCTransform\u201d function with glmGamPoi method Ahlmann Eltze and Huber 2021. Fifty principal components were used and the resolution parameter was set to 0.4. Downstream analysis was done as described above for the integrated analysis. We used a zebrafish single atlas Sur et al. 2023 to generate a database of markers for each tissue and cell type Table S1. The differentially expressed markers of each cluster were crossreferenced with our compiled database using our \u201cDE Marker Scoring\u201d algorithm Saraswathy et al. 2024. For every matching marker gene one point was given to the respective cluster under the column name with matching cell identity. Iteration over every marker gene was performed to generate a scoring matrix with varying points for each cluster against the different cell identities compiled in the database Table S2 sheet: scoring. The \u201cphyper\u201d function in R was then used to calculate one tailed binomial probabilities using hypergeometric distribution for the total score obtained from each cluster against each cell identity in the database Table S2 sheet: Binomial probability. \u2212log10 of probability values were obtained for plotting the heatmap Table S2 sheet:\u2212log10P. The resulting values were scaled from 0 to 100 and plotted as a heatmap using GraphPad prism. Each cluster was given an identity based on the maximum \u2212log10 p score obtained in the heatmap. The top DE markers of clusters with ambiguous scores were manually annotated using the \u201cident genes\u201d from the zebrafish single atlas Sur et al. 2023 and literature search McKellar et al. 2021. Top DE markers generated for each cluster is given in Table S3 sheet:topDEmarkers.all.clusters \u201cRenameIdents\u201d function was used to assign identity to each cluster. To confirm the assigned cluster identities enrichment of classical markers of respective cell types were tested using Dot plot. The R package CellChat v2.1.2 was used to evaluate regenerative cell cell interactions post local and systemic muscle injury Jin et al. 2021. CellChat models the probability of cell cell communication by integrating our gene expression data with a database of known interaction between signaling ligands receptors and their cofactors CellChatDB. The RNA data was used to create CellChat object using \u201ccreateCellChat\u201d function followed by the recommended preprocessing functions with default parameters for the analysis of individual datasets. Truncated mean method with 10% trimmed observation was used to compute average gene expression per cell group for the complete dataset. The default trimean method was used to compute average gene expression for the CellChat analysis. CellChatDB.zebrafish was used to infer cell cell communication. All categories of ligand receptor interactions in the database were used in the analysis. Communications involving less than 10 cells were excluded. The \u201cnetAnalysis computeCentrality\u201d function was used to calculate network centrality scores at each time point. Functions such as \u201cnetVisual circle\u201d \u201cnetAnalysis contribution\u201d \u201cnetVisual aggregate\u201d \u201cnetVisual bubble\u201d \u201cnetAnalysis signalingRole heatmap\u201d and \u201cnetAnalysis signalingRole scatter\u201d were used to generate different plots used in this paper. Assembly: zebrafish reference genome GRCz11 and the sorted Gene Transfer Format file v4.3.2 from the improved zebrafish transcriptome annotation Lawson et al. 2020. Supplementary files format and content: Compressed Filtered Feature and Barcode files as .tsv file and count matrices in .mtx file format.", "Trunk", "Fish were treated with 12 hours of metronidazole or were stuck locally with a needle", "15 larvae per cohort were dissected to remove the head caudal fin and internal organs and then processed as described Farnsworth DB 459 2020. For tissue lysis 500\u03bcL of dissociation buffer 2ug/ul Collagenase P 2mM CaCl2 0.2 ul DNaseI 0.25% Trypsin in 1X PBS was added to the samples and incubated at 28 \u00b0C until samples were visually dissociated 15min. Dissociation was stopped with equal volume of stop buffer 10% FBS 0.001mM EDTA in 1X PBS. Samples were centrifuged at 750rcf for 7min at 4\u00b0C the supernatant was discarded and the pellet was resuspended in 100\u03bcL of resuspension buffer 1% FBS 2mM CaCl2 1X Penicillin/Streptomycin in DMEM. The suspension was strained through 20\u03bcm cell strainer Pluriselect USA 43 10020 40 centrifuged once 500rcf 1 min 4\u00b0C to pass cells through the strainer and centrifuged a second time 750rcf 7 min 4\u00b0C to pellet the cells. The cells were resuspended in 100\u03bcL of resuspension buffer centrifugated 750rcf 7min 4\u00b0C and the pellet was resuspended in 50\u03bcL 0.04% BSA in PBS. 5\u03bcl of cells were then combined with 5\u03bcl of Hoechst Invitrogen H3570 incubated for 10min and transferred to a hemocytometer Bulldogbio NC1731934 to determine cell concentration. An additional 5\u03bcl of cells were incubated with Trypan blue Sigma T8154 for 5min transferred to a hemocytometer and counted to assess cell viability. Samples with > 70% viability were then submitted for single cell sequencing. For snRNA seq 30 \u00b5l of isolated nuclei at a concentration of 1000 nuclei/\u00b5l was submitted to Genome Technology Access Center at McDonnel Genome Institute of Washington University. Two biological replicates of each genotype were used. cDNA was prepared post the GEM generation and barcoding followed by the GEM RT reaction and bead cleanup steps. cDNA was amplified for 11 13 cycles then purified using SPRIselect beads. Purified cDNA samples were then run on a Bioanalyzer to determine the cDNA concentration. GEX libraries were prepared as recommended by the 10x Genomics Chromium Single Cell 3\u2019 Reagent Kits User Guide v3.1 Chemistry Dual Index with appropriate modifications to the PCR cycles based on the calculated cDNA concentration. For sample preparation on the 10x Genomics platform the Chromium Next GEM Single Cell 3\u2019 Kit v3.1 16 rxns PN 1000268 Chromium Next GEM Chip G Single Cell Kit 48 rxns PN 1000120 and Dual Index Kit TT Set A 96 rxns PN 1000215 were used. The concentration of each library was accurately determined through qPCR utilizing the KAPA library Quantification Kit according to the manufacturer\u2019s protocol KAPA Biosystems/Roche to produce cluster counts appropriate for the Illumina NovaSeq6000 instrument. Normalized libraries were sequenced on a NovaSeq6000 S4 Flow Cell using the XP workflow and a 50x10x16x150 sequencing recipe according to manufacturer protocol. A median sequencing depth of 50 000 reads/cell was targeted for each Gene Expression Library.", "Larval zebrafish of 4 dpf underwent drug treatments or needle stick injuries for muscle ablation", "tissue:Trunk|genotype:Tgactc1b:NTR mCherry|treatment:Fish Water|batch:10/28/2022", "GSM9034431", "GSM9034431: larval trunk 4dpi Negative Control; Danio rerio; RNA Seq", "GSM9034431 r1", "GSM9034431", "1", "15 larvae per cohort were dissected to remove the head caudal fin and internal organs and then processed as described Farnsworth DB 459 2020. For tissue lysis 500\u03bcL of dissociation buffer 2ug/ul Collagenase P 2mM CaCl2 0.2 ul DNaseI 0.25% Trypsin in 1X PBS was added to the samples and incubated at 28 \u00b0C until samples were visually dissociated 15min. Dissociation was stopped with equal volume of stop buffer 10% FBS 0.001mM EDTA in 1X PBS. Samples were centrifuged at 750rcf for 7min at 4\u00b0C the supernatant was discarded and the pellet was resuspended in 100\u03bcL of resuspension buffer 1% FBS 2mM CaCl2 1X Penicillin/Streptomycin in DMEM. The suspension was strained through 20\u03bcm cell strainer Pluriselect USA 43 10020 40 centrifuged once 500rcf 1 min 4\u00b0C to pass cells through the strainer and centrifuged a second time 750rcf 7 min 4\u00b0C to pellet the cells. The cells were resuspended in 100\u03bcL of resuspension buffer centrifugated 750rcf 7min 4\u00b0C and the pellet was resuspended in 50\u03bcL 0.04% BSA in PBS. 5\u03bcl of cells were then combined with 5\u03bcl of Hoechst Invitrogen H3570 incubated for 10min and transferred to a hemocytometer Bulldogbio NC1731934 to determine cell concentration. An additional 5\u03bcl of cells were incubated with Trypan blue Sigma T8154 for 5min transferred to a hemocytometer and counted to assess cell viability. Samples with > 70% viability were then submitted for single cell sequencing. For snRNA seq 30 \u00b5l of isolated nuclei at a concentration of 1000 nuclei/\u00b5l was submitted to Genome Technology Access Center at McDonnel Genome Institute of Washington University. Two biological replicates of each genotype were used. cDNA was prepared post the GEM generation and barcoding followed by the GEM RT reaction and bead cleanup steps. cDNA was amplified for 11 13 cycles then purified using SPRIselect beads. Purified cDNA samples were then run on a Bioanalyzer to determine the cDNA concentration. GEX libraries were prepared as recommended by the 10x Genomics Chromium Single Cell three prime Reagent Kits User Guide v3.1 Chemistry Dual Index with appropriate modifications to the PCR cycles based on the calculated cDNA concentration. For sample preparation on the 10x Genomics platform the Chromium Next GEM Single Cell three prime Kit v3.1 16 rxns PN 1000268 Chromium Next GEM Chip G Single Cell Kit 48 rxns PN 1000120 and Dual Index Kit TT Set A 96 rxns PN 1000215 were used. The concentration of each library was accurately determined through qPCR utilizing the KAPA library Quantification Kit according to the manufacturer's protocol KAPA Biosystems/Roche to produce cluster counts appropriate for the Illumina NovaSeq6000 instrument. Normalized libraries were sequenced on a NovaSeq6000 S4 Flow Cell using the XP workflow and a 50x10x16x150 sequencing recipe according to manufacturer protocol. A median sequencing depth of 50 000 reads/cell was targeted for each Gene Expression Library.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP590547", null, null, "AJAH-18300_Green-18300_Negative_Control_4dpi-lib1_S1_L004_R1_001.fastq.gz AJAH-18300_Green-18300_Negative_Control_4dpi-lib1_S1_L004_R2_001.fastq.gz", "fastq fastq", 120050343140.0, 674440130.0, "GSM9034431 r1", "0:28 1:150", "A:34219257803;C:27603489363;G:29252474045;T:28971358956;N:3762973", 28, 150, null, null, 34219257803, 27603489363, 29252474045, 28971358956, 3762973, "SRX29085356", "SRS25297144", "SRA2144659", "Johnson Lab, Developmental Biology, Washington University in St.Louis", "Johnson Lab, Developmental Biology, Washington University in St.Louis", null, null, null, null, null, null, null, null, null, null, null, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2025-06-06", "Larval", "Larval", "Trunk", "Surface Structure"], [36245, "SRR33873802", "SRX29085355", "SRS25297143", "SRP590547", "PRJNA1272846", "Organism wide contributions to systemic skeletal muscle repair in larval zebrafish.", "GSE299146", "Transcriptome Analysis", "We developed a systemic muscle injury model in zebrafish. Single cell transcriptomic analysis of muscle and non muscle tissues revealed that systemic and local muscle injuries elicit distinct cellular molecular responses both quantitatively and qualitatively. These studies suggest that large and small scale muscle injuries activate different regenerative programs resulting in either systemic or local repair. Overall design: To characterize the regenerative responses and signaling pathways activated post systemic or local muscle injury we generated Tgactc1b:NTR mCherry transgenic zebrafish lines.At 4 dpf transgenic larvae were treated with MTZ overnight to systemically injure all myofibers or were subjected to local mechanical injury needlestick of 2 3 somites.Uninjured and systemically injured larvae were collected at 1 2 and 4 xxx post injury. Mechanically injured larvae were collected at 2 xxx post injury. Sequencing results were compared between uninjured systemically injured and mechanically injured siblings.", null, null, null, "larval trunk 2dpi mcherry MTZ", "GSM9034430", null, "source name:Trunk|tissue:Trunk|genotype:Tgactc1b:NTR mCherry|treatment:Fish Water + MTZ|batch:10/26/2022|geo loc name:missing|collection date:missing", "larval trunk 2dpi mcherry MTZ", "post sequencing the Illumina output was processed using the CellRanger v8.0.1 pipeline to generate gene barcode count matrices. A custom reference genome was made with the \u201ccellranger mkref\u201d command using the fasta file of zebrafish reference genome GRCz11 constructed from the Ensemble genome build https://useast.ensembl.org/Danio rerio/Info/Index and the sorted Gene Transfer Format file v4.3.2 from the improved zebrafish transcriptome annotation Lawson et al. 2020. Base call files for each sample from Illumina were demultiplexed into FASTQ reads. Then the \u201ccellranger count\u201d pipeline was used to align sequencing reads in FASTQ files to the custom reference genome. Both exon and intron sequences were included during the alignment. The filtered gene barcode count matrices generated by \u201ccellranger count\u201d was used for downstream analysis. Datasets were integrated and analyzed using Seurat v4.4.0 package with R v4.4.2Stuart etal. 2019; Team 2024. Each sample count matrix was filtered for genes that were expressed in at least 3 cells and cells expressing at least 200 genes followed by cell quality assessment usingcommonly used QC matrixes Ilicic et al. 2016. Cells having a unique number of genes between 200 and 6500 mitochondrial gene percentage <5 and total number of reads UMIs between 300and 35000 were used for downstream processing. Each dataset was independently normalizedand scaled using the \u201cSCTransform\u201d function which is an improved method for normalization that performs a variance stabilizing transformation using negative binomial regression Hafemeisterand Satija 2019. Standard integration workflow of Seurat was used to identify shared sources of variation across experiments as well as mutual nearest neighbors Butler et al. 2018; Haghverdiet al. 2018. Integration features were selected based on the top 6000 highly variable features using \u201cSelectIntegrationFeatures\u201d function nfeatures\u2009=\u20096000 which was used as input for the\u201canchor.features\u201d argument of the \u201cFindIntegrationAnchors\u201d function. PCA analysis was performed on the 6000 variable features and the top 50 principal components selected based on the elbow plot heuristic which measures the contribution of variation in each component. These 50 principal components were used in \u201cFindNeighbors\u201d and \u201cFindClusters\u201d functions to perform graph based clustering on a shared nearest neighbor graph Levine et al. 2015; Xu and Su 2015. Louvain algorithm was used for modularity optimization in cell clustering using \u201cFindClusters\u201d function. The resolution parameter res\u2009=\u20090.3 that determines the granularity of clusteringwas selected by visually inspecting clusters with resolutions ranging between 0.1 and 2.0 as well as clustree graph Zappia and Oshlack 2018. Uniform Manifold Approximation and Reduction UMAP was used for non linear dimensional reduction of the first 50 principal components and visualize the data using \u201cRunUMAP\u201d function Becht et al. 2018. Data was graphed using different plot functions such as \u201cDimPlot\u201d \u201cVlnPlot\u201d \u201cFeaturePlot\u201d \u201cDotplot\u201d and \u201cDoHeatmap\u201d to view the cell cluster identity and marker gene expression. Cell proportions were extracted using the \u201ctable\u201d and \u201cprop.table\u201d functions. Differential gene expression for individual clusters was identified using Wilcoxon rank sum test in the \u201cFindAllMarkers\u201d function. Marker genes detected in at least 25% of the clustered cells and had a positive average log2FC were reported. Muscle cells identified from the complete dataset were subclustered using the \u201csubset\u201d function for subcluster analysis. The muscle subset was again normalized and scaled using the \u201cSCTransform\u201d function with glmGamPoi method Ahlmann Eltze and Huber 2021. Fifty principal components were used and the resolution parameter was set to 0.4. Downstream analysis was done as described above for the integrated analysis. We used a zebrafish single atlas Sur et al. 2023 to generate a database of markers for each tissue and cell type Table S1. The differentially expressed markers of each cluster were crossreferenced with our compiled database using our \u201cDE Marker Scoring\u201d algorithm Saraswathy et al. 2024. For every matching marker gene one point was given to the respective cluster under the column name with matching cell identity. Iteration over every marker gene was performed to generate a scoring matrix with varying points for each cluster against the different cell identities compiled in the database Table S2 sheet: scoring. The \u201cphyper\u201d function in R was then used to calculate one tailed binomial probabilities using hypergeometric distribution for the total score obtained from each cluster against each cell identity in the database Table S2 sheet: Binomial probability. \u2212log10 of probability values were obtained for plotting the heatmap Table S2 sheet:\u2212log10P. The resulting values were scaled from 0 to 100 and plotted as a heatmap using GraphPad prism. Each cluster was given an identity based on the maximum \u2212log10 p score obtained in the heatmap. The top DE markers of clusters with ambiguous scores were manually annotated using the \u201cident genes\u201d from the zebrafish single atlas Sur et al. 2023 and literature search McKellar et al. 2021. Top DE markers generated for each cluster is given in Table S3 sheet:topDEmarkers.all.clusters \u201cRenameIdents\u201d function was used to assign identity to each cluster. To confirm the assigned cluster identities enrichment of classical markers of respective cell types were tested using Dot plot. The R package CellChat v2.1.2 was used to evaluate regenerative cell cell interactions post local and systemic muscle injury Jin et al. 2021. CellChat models the probability of cell cell communication by integrating our gene expression data with a database of known interaction between signaling ligands receptors and their cofactors CellChatDB. The RNA data was used to create CellChat object using \u201ccreateCellChat\u201d function followed by the recommended preprocessing functions with default parameters for the analysis of individual datasets. Truncated mean method with 10% trimmed observation was used to compute average gene expression per cell group for the complete dataset. The default trimean method was used to compute average gene expression for the CellChat analysis. CellChatDB.zebrafish was used to infer cell cell communication. All categories of ligand receptor interactions in the database were used in the analysis. Communications involving less than 10 cells were excluded. The \u201cnetAnalysis computeCentrality\u201d function was used to calculate network centrality scores at each time point. Functions such as \u201cnetVisual circle\u201d \u201cnetAnalysis contribution\u201d \u201cnetVisual aggregate\u201d \u201cnetVisual bubble\u201d \u201cnetAnalysis signalingRole heatmap\u201d and \u201cnetAnalysis signalingRole scatter\u201d were used to generate different plots used in this paper. Assembly: zebrafish reference genome GRCz11 and the sorted Gene Transfer Format file v4.3.2 from the improved zebrafish transcriptome annotation Lawson et al. 2020. Supplementary files format and content: Compressed Filtered Feature and Barcode files as .tsv file and count matrices in .mtx file format.", "Trunk", "Fish were treated with 12 hours of metronidazole or were stuck locally with a needle", "15 larvae per cohort were dissected to remove the head caudal fin and internal organs and then processed as described Farnsworth DB 459 2020. For tissue lysis 500\u03bcL of dissociation buffer 2ug/ul Collagenase P 2mM CaCl2 0.2 ul DNaseI 0.25% Trypsin in 1X PBS was added to the samples and incubated at 28 \u00b0C until samples were visually dissociated 15min. Dissociation was stopped with equal volume of stop buffer 10% FBS 0.001mM EDTA in 1X PBS. Samples were centrifuged at 750rcf for 7min at 4\u00b0C the supernatant was discarded and the pellet was resuspended in 100\u03bcL of resuspension buffer 1% FBS 2mM CaCl2 1X Penicillin/Streptomycin in DMEM. The suspension was strained through 20\u03bcm cell strainer Pluriselect USA 43 10020 40 centrifuged once 500rcf 1 min 4\u00b0C to pass cells through the strainer and centrifuged a second time 750rcf 7 min 4\u00b0C to pellet the cells. The cells were resuspended in 100\u03bcL of resuspension buffer centrifugated 750rcf 7min 4\u00b0C and the pellet was resuspended in 50\u03bcL 0.04% BSA in PBS. 5\u03bcl of cells were then combined with 5\u03bcl of Hoechst Invitrogen H3570 incubated for 10min and transferred to a hemocytometer Bulldogbio NC1731934 to determine cell concentration. An additional 5\u03bcl of cells were incubated with Trypan blue Sigma T8154 for 5min transferred to a hemocytometer and counted to assess cell viability. Samples with > 70% viability were then submitted for single cell sequencing. For snRNA seq 30 \u00b5l of isolated nuclei at a concentration of 1000 nuclei/\u00b5l was submitted to Genome Technology Access Center at McDonnel Genome Institute of Washington University. Two biological replicates of each genotype were used. cDNA was prepared post the GEM generation and barcoding followed by the GEM RT reaction and bead cleanup steps. cDNA was amplified for 11 13 cycles then purified using SPRIselect beads. Purified cDNA samples were then run on a Bioanalyzer to determine the cDNA concentration. GEX libraries were prepared as recommended by the 10x Genomics Chromium Single Cell 3\u2019 Reagent Kits User Guide v3.1 Chemistry Dual Index with appropriate modifications to the PCR cycles based on the calculated cDNA concentration. For sample preparation on the 10x Genomics platform the Chromium Next GEM Single Cell 3\u2019 Kit v3.1 16 rxns PN 1000268 Chromium Next GEM Chip G Single Cell Kit 48 rxns PN 1000120 and Dual Index Kit TT Set A 96 rxns PN 1000215 were used. The concentration of each library was accurately determined through qPCR utilizing the KAPA library Quantification Kit according to the manufacturer\u2019s protocol KAPA Biosystems/Roche to produce cluster counts appropriate for the Illumina NovaSeq6000 instrument. Normalized libraries were sequenced on a NovaSeq6000 S4 Flow Cell using the XP workflow and a 50x10x16x150 sequencing recipe according to manufacturer protocol. A median sequencing depth of 50 000 reads/cell was targeted for each Gene Expression Library.", "Larval zebrafish of 4 dpf underwent drug treatments or needle stick injuries for muscle ablation", "tissue:Trunk|genotype:Tgactc1b:NTR mCherry|treatment:Fish Water + MTZ|batch:10/26/2022", "GSM9034430", "GSM9034430: larval trunk 2dpi mcherry MTZ; Danio rerio; RNA Seq", "GSM9034430 r1", "GSM9034430", "1", "15 larvae per cohort were dissected to remove the head caudal fin and internal organs and then processed as described Farnsworth DB 459 2020. For tissue lysis 500\u03bcL of dissociation buffer 2ug/ul Collagenase P 2mM CaCl2 0.2 ul DNaseI 0.25% Trypsin in 1X PBS was added to the samples and incubated at 28 \u00b0C until samples were visually dissociated 15min. Dissociation was stopped with equal volume of stop buffer 10% FBS 0.001mM EDTA in 1X PBS. Samples were centrifuged at 750rcf for 7min at 4\u00b0C the supernatant was discarded and the pellet was resuspended in 100\u03bcL of resuspension buffer 1% FBS 2mM CaCl2 1X Penicillin/Streptomycin in DMEM. The suspension was strained through 20\u03bcm cell strainer Pluriselect USA 43 10020 40 centrifuged once 500rcf 1 min 4\u00b0C to pass cells through the strainer and centrifuged a second time 750rcf 7 min 4\u00b0C to pellet the cells. The cells were resuspended in 100\u03bcL of resuspension buffer centrifugated 750rcf 7min 4\u00b0C and the pellet was resuspended in 50\u03bcL 0.04% BSA in PBS. 5\u03bcl of cells were then combined with 5\u03bcl of Hoechst Invitrogen H3570 incubated for 10min and transferred to a hemocytometer Bulldogbio NC1731934 to determine cell concentration. An additional 5\u03bcl of cells were incubated with Trypan blue Sigma T8154 for 5min transferred to a hemocytometer and counted to assess cell viability. Samples with > 70% viability were then submitted for single cell sequencing. For snRNA seq 30 \u00b5l of isolated nuclei at a concentration of 1000 nuclei/\u00b5l was submitted to Genome Technology Access Center at McDonnel Genome Institute of Washington University. Two biological replicates of each genotype were used. cDNA was prepared post the GEM generation and barcoding followed by the GEM RT reaction and bead cleanup steps. cDNA was amplified for 11 13 cycles then purified using SPRIselect beads. Purified cDNA samples were then run on a Bioanalyzer to determine the cDNA concentration. GEX libraries were prepared as recommended by the 10x Genomics Chromium Single Cell three prime Reagent Kits User Guide v3.1 Chemistry Dual Index with appropriate modifications to the PCR cycles based on the calculated cDNA concentration. For sample preparation on the 10x Genomics platform the Chromium Next GEM Single Cell three prime Kit v3.1 16 rxns PN 1000268 Chromium Next GEM Chip G Single Cell Kit 48 rxns PN 1000120 and Dual Index Kit TT Set A 96 rxns PN 1000215 were used. The concentration of each library was accurately determined through qPCR utilizing the KAPA library Quantification Kit according to the manufacturer's protocol KAPA Biosystems/Roche to produce cluster counts appropriate for the Illumina NovaSeq6000 instrument. Normalized libraries were sequenced on a NovaSeq6000 S4 Flow Cell using the XP workflow and a 50x10x16x150 sequencing recipe according to manufacturer protocol. A median sequencing depth of 50 000 reads/cell was targeted for each Gene Expression Library.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP590547", null, null, "AJAH-18300_Red-18300_mCherry_Positive_2dpi-lib1_S2_L004_R1_001.fastq.gz AJAH-18300_Red-18300_mCherry_Positive_2dpi-lib1_S2_L004_R2_001.fastq.gz", "fastq fastq", 86534465752.0, 486148684.0, "GSM9034430 r1", "0:28 1:150", "A:23591959992;C:20534495856;G:22206815673;T:20199626171;N:1568060", 28, 150, null, null, 23591959992, 20534495856, 22206815673, 20199626171, 1568060, "SRX29085355", "SRS25297143", "SRA2144659", "Johnson Lab, Developmental Biology, Washington University in St.Louis", "Johnson Lab, Developmental Biology, Washington University in St.Louis", 2, 0.01419, 0.94664, 0.00513, 0.17395, 0.99504, 0.8396, 0.29625, 0.66798, 28, 150, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2025-06-06", "Larval", "Larval", "Trunk", "Surface Structure"], [36246, "SRR33873803", "SRX29085354", "SRS25297142", "SRP590547", "PRJNA1272846", "Organism wide contributions to systemic skeletal muscle repair in larval zebrafish.", "GSE299146", "Transcriptome Analysis", "We developed a systemic muscle injury model in zebrafish. Single cell transcriptomic analysis of muscle and non muscle tissues revealed that systemic and local muscle injuries elicit distinct cellular molecular responses both quantitatively and qualitatively. These studies suggest that large and small scale muscle injuries activate different regenerative programs resulting in either systemic or local repair. Overall design: To characterize the regenerative responses and signaling pathways activated post systemic or local muscle injury we generated Tgactc1b:NTR mCherry transgenic zebrafish lines.At 4 dpf transgenic larvae were treated with MTZ overnight to systemically injure all myofibers or were subjected to local mechanical injury needlestick of 2 3 somites.Uninjured and systemically injured larvae were collected at 1 2 and 4 xxx post injury. Mechanically injured larvae were collected at 2 xxx post injury. Sequencing results were compared between uninjured systemically injured and mechanically injured siblings.", null, null, null, "larval trunk 2dpi Negative Control", "GSM9034429", null, "source name:Trunk|tissue:Trunk|genotype:Tgactc1b:NTR mCherry|treatment:Fish Water|batch:10/26/2022|geo loc name:missing|collection date:missing", "larval trunk 2dpi Negative Control", "post sequencing the Illumina output was processed using the CellRanger v8.0.1 pipeline to generate gene barcode count matrices. A custom reference genome was made with the \u201ccellranger mkref\u201d command using the fasta file of zebrafish reference genome GRCz11 constructed from the Ensemble genome build https://useast.ensembl.org/Danio rerio/Info/Index and the sorted Gene Transfer Format file v4.3.2 from the improved zebrafish transcriptome annotation Lawson et al. 2020. Base call files for each sample from Illumina were demultiplexed into FASTQ reads. Then the \u201ccellranger count\u201d pipeline was used to align sequencing reads in FASTQ files to the custom reference genome. Both exon and intron sequences were included during the alignment. The filtered gene barcode count matrices generated by \u201ccellranger count\u201d was used for downstream analysis. Datasets were integrated and analyzed using Seurat v4.4.0 package with R v4.4.2Stuart etal. 2019; Team 2024. Each sample count matrix was filtered for genes that were expressed in at least 3 cells and cells expressing at least 200 genes followed by cell quality assessment usingcommonly used QC matrixes Ilicic et al. 2016. Cells having a unique number of genes between 200 and 6500 mitochondrial gene percentage <5 and total number of reads UMIs between 300and 35000 were used for downstream processing. Each dataset was independently normalizedand scaled using the \u201cSCTransform\u201d function which is an improved method for normalization that performs a variance stabilizing transformation using negative binomial regression Hafemeisterand Satija 2019. Standard integration workflow of Seurat was used to identify shared sources of variation across experiments as well as mutual nearest neighbors Butler et al. 2018; Haghverdiet al. 2018. Integration features were selected based on the top 6000 highly variable features using \u201cSelectIntegrationFeatures\u201d function nfeatures\u2009=\u20096000 which was used as input for the\u201canchor.features\u201d argument of the \u201cFindIntegrationAnchors\u201d function. PCA analysis was performed on the 6000 variable features and the top 50 principal components selected based on the elbow plot heuristic which measures the contribution of variation in each component. These 50 principal components were used in \u201cFindNeighbors\u201d and \u201cFindClusters\u201d functions to perform graph based clustering on a shared nearest neighbor graph Levine et al. 2015; Xu and Su 2015. Louvain algorithm was used for modularity optimization in cell clustering using \u201cFindClusters\u201d function. The resolution parameter res\u2009=\u20090.3 that determines the granularity of clusteringwas selected by visually inspecting clusters with resolutions ranging between 0.1 and 2.0 as well as clustree graph Zappia and Oshlack 2018. Uniform Manifold Approximation and Reduction UMAP was used for non linear dimensional reduction of the first 50 principal components and visualize the data using \u201cRunUMAP\u201d function Becht et al. 2018. Data was graphed using different plot functions such as \u201cDimPlot\u201d \u201cVlnPlot\u201d \u201cFeaturePlot\u201d \u201cDotplot\u201d and \u201cDoHeatmap\u201d to view the cell cluster identity and marker gene expression. Cell proportions were extracted using the \u201ctable\u201d and \u201cprop.table\u201d functions. Differential gene expression for individual clusters was identified using Wilcoxon rank sum test in the \u201cFindAllMarkers\u201d function. Marker genes detected in at least 25% of the clustered cells and had a positive average log2FC were reported. Muscle cells identified from the complete dataset were subclustered using the \u201csubset\u201d function for subcluster analysis. The muscle subset was again normalized and scaled using the \u201cSCTransform\u201d function with glmGamPoi method Ahlmann Eltze and Huber 2021. Fifty principal components were used and the resolution parameter was set to 0.4. Downstream analysis was done as described above for the integrated analysis. We used a zebrafish single atlas Sur et al. 2023 to generate a database of markers for each tissue and cell type Table S1. The differentially expressed markers of each cluster were crossreferenced with our compiled database using our \u201cDE Marker Scoring\u201d algorithm Saraswathy et al. 2024. For every matching marker gene one point was given to the respective cluster under the column name with matching cell identity. Iteration over every marker gene was performed to generate a scoring matrix with varying points for each cluster against the different cell identities compiled in the database Table S2 sheet: scoring. The \u201cphyper\u201d function in R was then used to calculate one tailed binomial probabilities using hypergeometric distribution for the total score obtained from each cluster against each cell identity in the database Table S2 sheet: Binomial probability. \u2212log10 of probability values were obtained for plotting the heatmap Table S2 sheet:\u2212log10P. The resulting values were scaled from 0 to 100 and plotted as a heatmap using GraphPad prism. Each cluster was given an identity based on the maximum \u2212log10 p score obtained in the heatmap. The top DE markers of clusters with ambiguous scores were manually annotated using the \u201cident genes\u201d from the zebrafish single atlas Sur et al. 2023 and literature search McKellar et al. 2021. Top DE markers generated for each cluster is given in Table S3 sheet:topDEmarkers.all.clusters \u201cRenameIdents\u201d function was used to assign identity to each cluster. To confirm the assigned cluster identities enrichment of classical markers of respective cell types were tested using Dot plot. The R package CellChat v2.1.2 was used to evaluate regenerative cell cell interactions post local and systemic muscle injury Jin et al. 2021. CellChat models the probability of cell cell communication by integrating our gene expression data with a database of known interaction between signaling ligands receptors and their cofactors CellChatDB. The RNA data was used to create CellChat object using \u201ccreateCellChat\u201d function followed by the recommended preprocessing functions with default parameters for the analysis of individual datasets. Truncated mean method with 10% trimmed observation was used to compute average gene expression per cell group for the complete dataset. The default trimean method was used to compute average gene expression for the CellChat analysis. CellChatDB.zebrafish was used to infer cell cell communication. All categories of ligand receptor interactions in the database were used in the analysis. Communications involving less than 10 cells were excluded. The \u201cnetAnalysis computeCentrality\u201d function was used to calculate network centrality scores at each time point. Functions such as \u201cnetVisual circle\u201d \u201cnetAnalysis contribution\u201d \u201cnetVisual aggregate\u201d \u201cnetVisual bubble\u201d \u201cnetAnalysis signalingRole heatmap\u201d and \u201cnetAnalysis signalingRole scatter\u201d were used to generate different plots used in this paper. Assembly: zebrafish reference genome GRCz11 and the sorted Gene Transfer Format file v4.3.2 from the improved zebrafish transcriptome annotation Lawson et al. 2020. Supplementary files format and content: Compressed Filtered Feature and Barcode files as .tsv file and count matrices in .mtx file format.", "Trunk", "Fish were treated with 12 hours of metronidazole or were stuck locally with a needle", "15 larvae per cohort were dissected to remove the head caudal fin and internal organs and then processed as described Farnsworth DB 459 2020. For tissue lysis 500\u03bcL of dissociation buffer 2ug/ul Collagenase P 2mM CaCl2 0.2 ul DNaseI 0.25% Trypsin in 1X PBS was added to the samples and incubated at 28 \u00b0C until samples were visually dissociated 15min. Dissociation was stopped with equal volume of stop buffer 10% FBS 0.001mM EDTA in 1X PBS. Samples were centrifuged at 750rcf for 7min at 4\u00b0C the supernatant was discarded and the pellet was resuspended in 100\u03bcL of resuspension buffer 1% FBS 2mM CaCl2 1X Penicillin/Streptomycin in DMEM. The suspension was strained through 20\u03bcm cell strainer Pluriselect USA 43 10020 40 centrifuged once 500rcf 1 min 4\u00b0C to pass cells through the strainer and centrifuged a second time 750rcf 7 min 4\u00b0C to pellet the cells. The cells were resuspended in 100\u03bcL of resuspension buffer centrifugated 750rcf 7min 4\u00b0C and the pellet was resuspended in 50\u03bcL 0.04% BSA in PBS. 5\u03bcl of cells were then combined with 5\u03bcl of Hoechst Invitrogen H3570 incubated for 10min and transferred to a hemocytometer Bulldogbio NC1731934 to determine cell concentration. An additional 5\u03bcl of cells were incubated with Trypan blue Sigma T8154 for 5min transferred to a hemocytometer and counted to assess cell viability. Samples with > 70% viability were then submitted for single cell sequencing. For snRNA seq 30 \u00b5l of isolated nuclei at a concentration of 1000 nuclei/\u00b5l was submitted to Genome Technology Access Center at McDonnel Genome Institute of Washington University. Two biological replicates of each genotype were used. cDNA was prepared post the GEM generation and barcoding followed by the GEM RT reaction and bead cleanup steps. cDNA was amplified for 11 13 cycles then purified using SPRIselect beads. Purified cDNA samples were then run on a Bioanalyzer to determine the cDNA concentration. GEX libraries were prepared as recommended by the 10x Genomics Chromium Single Cell 3\u2019 Reagent Kits User Guide v3.1 Chemistry Dual Index with appropriate modifications to the PCR cycles based on the calculated cDNA concentration. For sample preparation on the 10x Genomics platform the Chromium Next GEM Single Cell 3\u2019 Kit v3.1 16 rxns PN 1000268 Chromium Next GEM Chip G Single Cell Kit 48 rxns PN 1000120 and Dual Index Kit TT Set A 96 rxns PN 1000215 were used. The concentration of each library was accurately determined through qPCR utilizing the KAPA library Quantification Kit according to the manufacturer\u2019s protocol KAPA Biosystems/Roche to produce cluster counts appropriate for the Illumina NovaSeq6000 instrument. Normalized libraries were sequenced on a NovaSeq6000 S4 Flow Cell using the XP workflow and a 50x10x16x150 sequencing recipe according to manufacturer protocol. A median sequencing depth of 50 000 reads/cell was targeted for each Gene Expression Library.", "Larval zebrafish of 4 dpf underwent drug treatments or needle stick injuries for muscle ablation", "tissue:Trunk|genotype:Tgactc1b:NTR mCherry|treatment:Fish Water|batch:10/26/2022", "GSM9034429", "GSM9034429: larval trunk 2dpi Negative Control; Danio rerio; RNA Seq", "GSM9034429 r1", "GSM9034429", "1", "15 larvae per cohort were dissected to remove the head caudal fin and internal organs and then processed as described Farnsworth DB 459 2020. For tissue lysis 500\u03bcL of dissociation buffer 2ug/ul Collagenase P 2mM CaCl2 0.2 ul DNaseI 0.25% Trypsin in 1X PBS was added to the samples and incubated at 28 \u00b0C until samples were visually dissociated 15min. Dissociation was stopped with equal volume of stop buffer 10% FBS 0.001mM EDTA in 1X PBS. Samples were centrifuged at 750rcf for 7min at 4\u00b0C the supernatant was discarded and the pellet was resuspended in 100\u03bcL of resuspension buffer 1% FBS 2mM CaCl2 1X Penicillin/Streptomycin in DMEM. The suspension was strained through 20\u03bcm cell strainer Pluriselect USA 43 10020 40 centrifuged once 500rcf 1 min 4\u00b0C to pass cells through the strainer and centrifuged a second time 750rcf 7 min 4\u00b0C to pellet the cells. The cells were resuspended in 100\u03bcL of resuspension buffer centrifugated 750rcf 7min 4\u00b0C and the pellet was resuspended in 50\u03bcL 0.04% BSA in PBS. 5\u03bcl of cells were then combined with 5\u03bcl of Hoechst Invitrogen H3570 incubated for 10min and transferred to a hemocytometer Bulldogbio NC1731934 to determine cell concentration. An additional 5\u03bcl of cells were incubated with Trypan blue Sigma T8154 for 5min transferred to a hemocytometer and counted to assess cell viability. Samples with > 70% viability were then submitted for single cell sequencing. For snRNA seq 30 \u00b5l of isolated nuclei at a concentration of 1000 nuclei/\u00b5l was submitted to Genome Technology Access Center at McDonnel Genome Institute of Washington University. Two biological replicates of each genotype were used. cDNA was prepared post the GEM generation and barcoding followed by the GEM RT reaction and bead cleanup steps. cDNA was amplified for 11 13 cycles then purified using SPRIselect beads. Purified cDNA samples were then run on a Bioanalyzer to determine the cDNA concentration. GEX libraries were prepared as recommended by the 10x Genomics Chromium Single Cell three prime Reagent Kits User Guide v3.1 Chemistry Dual Index with appropriate modifications to the PCR cycles based on the calculated cDNA concentration. For sample preparation on the 10x Genomics platform the Chromium Next GEM Single Cell three prime Kit v3.1 16 rxns PN 1000268 Chromium Next GEM Chip G Single Cell Kit 48 rxns PN 1000120 and Dual Index Kit TT Set A 96 rxns PN 1000215 were used. The concentration of each library was accurately determined through qPCR utilizing the KAPA library Quantification Kit according to the manufacturer's protocol KAPA Biosystems/Roche to produce cluster counts appropriate for the Illumina NovaSeq6000 instrument. Normalized libraries were sequenced on a NovaSeq6000 S4 Flow Cell using the XP workflow and a 50x10x16x150 sequencing recipe according to manufacturer protocol. A median sequencing depth of 50 000 reads/cell was targeted for each Gene Expression Library.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP590547", null, null, "AJAH-18300_Green-18300_Negative_Control-lib1_S1_L004_R1_001.fastq.gz AJAH-18300_Green-18300_Negative_Control-lib1_S1_L004_R2_001.fastq.gz", "fastq fastq", 81637706044.0, 458638798.0, "GSM9034429 r1", "0:28 1:150", "A:23244690048;C:18579650528;G:19634226269;T:20177635070;N:1504129", 28, 150, null, null, 23244690048, 18579650528, 19634226269, 20177635070, 1504129, "SRX29085354", "SRS25297142", "SRA2144659", "Johnson Lab, Developmental Biology, Washington University in St.Louis", "Johnson Lab, Developmental Biology, Washington University in St.Louis", 2, 0.0091, 0.93772, 0.00313, 0.1383, 0.99446, 0.82698, 0.33858, 0.5389, 28, 150, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2025-06-06", "Larval", "Larval", "Trunk", "Surface Structure"], [36247, "SRR33873804", "SRX29085353", "SRS25297141", "SRP590547", "PRJNA1272846", "Organism wide contributions to systemic skeletal muscle repair in larval zebrafish.", "GSE299146", "Transcriptome Analysis", "We developed a systemic muscle injury model in zebrafish. Single cell transcriptomic analysis of muscle and non muscle tissues revealed that systemic and local muscle injuries elicit distinct cellular molecular responses both quantitatively and qualitatively. These studies suggest that large and small scale muscle injuries activate different regenerative programs resulting in either systemic or local repair. Overall design: To characterize the regenerative responses and signaling pathways activated post systemic or local muscle injury we generated Tgactc1b:NTR mCherry transgenic zebrafish lines.At 4 dpf transgenic larvae were treated with MTZ overnight to systemically injure all myofibers or were subjected to local mechanical injury needlestick of 2 3 somites.Uninjured and systemically injured larvae were collected at 1 2 and 4 xxx post injury. Mechanically injured larvae were collected at 2 xxx post injury. Sequencing results were compared between uninjured systemically injured and mechanically injured siblings.", null, null, null, "larval trunk 1dpi mcherry MTZ", "GSM9034428", null, "source name:Trunk|tissue:Trunk|genotype:Tgactc1b:NTR mCherry|treatment:Fish Water + MTZ|batch:10/25/2022|geo loc name:missing|collection date:missing", "larval trunk 1dpi mcherry MTZ", "post sequencing the Illumina output was processed using the CellRanger v8.0.1 pipeline to generate gene barcode count matrices. A custom reference genome was made with the \u201ccellranger mkref\u201d command using the fasta file of zebrafish reference genome GRCz11 constructed from the Ensemble genome build https://useast.ensembl.org/Danio rerio/Info/Index and the sorted Gene Transfer Format file v4.3.2 from the improved zebrafish transcriptome annotation Lawson et al. 2020. Base call files for each sample from Illumina were demultiplexed into FASTQ reads. Then the \u201ccellranger count\u201d pipeline was used to align sequencing reads in FASTQ files to the custom reference genome. Both exon and intron sequences were included during the alignment. The filtered gene barcode count matrices generated by \u201ccellranger count\u201d was used for downstream analysis. Datasets were integrated and analyzed using Seurat v4.4.0 package with R v4.4.2Stuart etal. 2019; Team 2024. Each sample count matrix was filtered for genes that were expressed in at least 3 cells and cells expressing at least 200 genes followed by cell quality assessment usingcommonly used QC matrixes Ilicic et al. 2016. Cells having a unique number of genes between 200 and 6500 mitochondrial gene percentage <5 and total number of reads UMIs between 300and 35000 were used for downstream processing. Each dataset was independently normalizedand scaled using the \u201cSCTransform\u201d function which is an improved method for normalization that performs a variance stabilizing transformation using negative binomial regression Hafemeisterand Satija 2019. Standard integration workflow of Seurat was used to identify shared sources of variation across experiments as well as mutual nearest neighbors Butler et al. 2018; Haghverdiet al. 2018. Integration features were selected based on the top 6000 highly variable features using \u201cSelectIntegrationFeatures\u201d function nfeatures\u2009=\u20096000 which was used as input for the\u201canchor.features\u201d argument of the \u201cFindIntegrationAnchors\u201d function. PCA analysis was performed on the 6000 variable features and the top 50 principal components selected based on the elbow plot heuristic which measures the contribution of variation in each component. These 50 principal components were used in \u201cFindNeighbors\u201d and \u201cFindClusters\u201d functions to perform graph based clustering on a shared nearest neighbor graph Levine et al. 2015; Xu and Su 2015. Louvain algorithm was used for modularity optimization in cell clustering using \u201cFindClusters\u201d function. The resolution parameter res\u2009=\u20090.3 that determines the granularity of clusteringwas selected by visually inspecting clusters with resolutions ranging between 0.1 and 2.0 as well as clustree graph Zappia and Oshlack 2018. Uniform Manifold Approximation and Reduction UMAP was used for non linear dimensional reduction of the first 50 principal components and visualize the data using \u201cRunUMAP\u201d function Becht et al. 2018. Data was graphed using different plot functions such as \u201cDimPlot\u201d \u201cVlnPlot\u201d \u201cFeaturePlot\u201d \u201cDotplot\u201d and \u201cDoHeatmap\u201d to view the cell cluster identity and marker gene expression. Cell proportions were extracted using the \u201ctable\u201d and \u201cprop.table\u201d functions. Differential gene expression for individual clusters was identified using Wilcoxon rank sum test in the \u201cFindAllMarkers\u201d function. Marker genes detected in at least 25% of the clustered cells and had a positive average log2FC were reported. Muscle cells identified from the complete dataset were subclustered using the \u201csubset\u201d function for subcluster analysis. The muscle subset was again normalized and scaled using the \u201cSCTransform\u201d function with glmGamPoi method Ahlmann Eltze and Huber 2021. Fifty principal components were used and the resolution parameter was set to 0.4. Downstream analysis was done as described above for the integrated analysis. We used a zebrafish single atlas Sur et al. 2023 to generate a database of markers for each tissue and cell type Table S1. The differentially expressed markers of each cluster were crossreferenced with our compiled database using our \u201cDE Marker Scoring\u201d algorithm Saraswathy et al. 2024. For every matching marker gene one point was given to the respective cluster under the column name with matching cell identity. Iteration over every marker gene was performed to generate a scoring matrix with varying points for each cluster against the different cell identities compiled in the database Table S2 sheet: scoring. The \u201cphyper\u201d function in R was then used to calculate one tailed binomial probabilities using hypergeometric distribution for the total score obtained from each cluster against each cell identity in the database Table S2 sheet: Binomial probability. \u2212log10 of probability values were obtained for plotting the heatmap Table S2 sheet:\u2212log10P. The resulting values were scaled from 0 to 100 and plotted as a heatmap using GraphPad prism. Each cluster was given an identity based on the maximum \u2212log10 p score obtained in the heatmap. The top DE markers of clusters with ambiguous scores were manually annotated using the \u201cident genes\u201d from the zebrafish single atlas Sur et al. 2023 and literature search McKellar et al. 2021. Top DE markers generated for each cluster is given in Table S3 sheet:topDEmarkers.all.clusters \u201cRenameIdents\u201d function was used to assign identity to each cluster. To confirm the assigned cluster identities enrichment of classical markers of respective cell types were tested using Dot plot. The R package CellChat v2.1.2 was used to evaluate regenerative cell cell interactions post local and systemic muscle injury Jin et al. 2021. CellChat models the probability of cell cell communication by integrating our gene expression data with a database of known interaction between signaling ligands receptors and their cofactors CellChatDB. The RNA data was used to create CellChat object using \u201ccreateCellChat\u201d function followed by the recommended preprocessing functions with default parameters for the analysis of individual datasets. Truncated mean method with 10% trimmed observation was used to compute average gene expression per cell group for the complete dataset. The default trimean method was used to compute average gene expression for the CellChat analysis. CellChatDB.zebrafish was used to infer cell cell communication. All categories of ligand receptor interactions in the database were used in the analysis. Communications involving less than 10 cells were excluded. The \u201cnetAnalysis computeCentrality\u201d function was used to calculate network centrality scores at each time point. Functions such as \u201cnetVisual circle\u201d \u201cnetAnalysis contribution\u201d \u201cnetVisual aggregate\u201d \u201cnetVisual bubble\u201d \u201cnetAnalysis signalingRole heatmap\u201d and \u201cnetAnalysis signalingRole scatter\u201d were used to generate different plots used in this paper. Assembly: zebrafish reference genome GRCz11 and the sorted Gene Transfer Format file v4.3.2 from the improved zebrafish transcriptome annotation Lawson et al. 2020. Supplementary files format and content: Compressed Filtered Feature and Barcode files as .tsv file and count matrices in .mtx file format.", "Trunk", "Fish were treated with 12 hours of metronidazole or were stuck locally with a needle", "15 larvae per cohort were dissected to remove the head caudal fin and internal organs and then processed as described Farnsworth DB 459 2020. For tissue lysis 500\u03bcL of dissociation buffer 2ug/ul Collagenase P 2mM CaCl2 0.2 ul DNaseI 0.25% Trypsin in 1X PBS was added to the samples and incubated at 28 \u00b0C until samples were visually dissociated 15min. Dissociation was stopped with equal volume of stop buffer 10% FBS 0.001mM EDTA in 1X PBS. Samples were centrifuged at 750rcf for 7min at 4\u00b0C the supernatant was discarded and the pellet was resuspended in 100\u03bcL of resuspension buffer 1% FBS 2mM CaCl2 1X Penicillin/Streptomycin in DMEM. The suspension was strained through 20\u03bcm cell strainer Pluriselect USA 43 10020 40 centrifuged once 500rcf 1 min 4\u00b0C to pass cells through the strainer and centrifuged a second time 750rcf 7 min 4\u00b0C to pellet the cells. The cells were resuspended in 100\u03bcL of resuspension buffer centrifugated 750rcf 7min 4\u00b0C and the pellet was resuspended in 50\u03bcL 0.04% BSA in PBS. 5\u03bcl of cells were then combined with 5\u03bcl of Hoechst Invitrogen H3570 incubated for 10min and transferred to a hemocytometer Bulldogbio NC1731934 to determine cell concentration. An additional 5\u03bcl of cells were incubated with Trypan blue Sigma T8154 for 5min transferred to a hemocytometer and counted to assess cell viability. Samples with > 70% viability were then submitted for single cell sequencing. For snRNA seq 30 \u00b5l of isolated nuclei at a concentration of 1000 nuclei/\u00b5l was submitted to Genome Technology Access Center at McDonnel Genome Institute of Washington University. Two biological replicates of each genotype were used. cDNA was prepared post the GEM generation and barcoding followed by the GEM RT reaction and bead cleanup steps. cDNA was amplified for 11 13 cycles then purified using SPRIselect beads. Purified cDNA samples were then run on a Bioanalyzer to determine the cDNA concentration. GEX libraries were prepared as recommended by the 10x Genomics Chromium Single Cell 3\u2019 Reagent Kits User Guide v3.1 Chemistry Dual Index with appropriate modifications to the PCR cycles based on the calculated cDNA concentration. For sample preparation on the 10x Genomics platform the Chromium Next GEM Single Cell 3\u2019 Kit v3.1 16 rxns PN 1000268 Chromium Next GEM Chip G Single Cell Kit 48 rxns PN 1000120 and Dual Index Kit TT Set A 96 rxns PN 1000215 were used. The concentration of each library was accurately determined through qPCR utilizing the KAPA library Quantification Kit according to the manufacturer\u2019s protocol KAPA Biosystems/Roche to produce cluster counts appropriate for the Illumina NovaSeq6000 instrument. Normalized libraries were sequenced on a NovaSeq6000 S4 Flow Cell using the XP workflow and a 50x10x16x150 sequencing recipe according to manufacturer protocol. A median sequencing depth of 50 000 reads/cell was targeted for each Gene Expression Library.", "Larval zebrafish of 4 dpf underwent drug treatments or needle stick injuries for muscle ablation", "tissue:Trunk|genotype:Tgactc1b:NTR mCherry|treatment:Fish Water + MTZ|batch:10/25/2022", "GSM9034428", "GSM9034428: larval trunk 1dpi mcherry MTZ; Danio rerio; RNA Seq", "GSM9034428 r1", "GSM9034428", "1", "15 larvae per cohort were dissected to remove the head caudal fin and internal organs and then processed as described Farnsworth DB 459 2020. For tissue lysis 500\u03bcL of dissociation buffer 2ug/ul Collagenase P 2mM CaCl2 0.2 ul DNaseI 0.25% Trypsin in 1X PBS was added to the samples and incubated at 28 \u00b0C until samples were visually dissociated 15min. Dissociation was stopped with equal volume of stop buffer 10% FBS 0.001mM EDTA in 1X PBS. Samples were centrifuged at 750rcf for 7min at 4\u00b0C the supernatant was discarded and the pellet was resuspended in 100\u03bcL of resuspension buffer 1% FBS 2mM CaCl2 1X Penicillin/Streptomycin in DMEM. The suspension was strained through 20\u03bcm cell strainer Pluriselect USA 43 10020 40 centrifuged once 500rcf 1 min 4\u00b0C to pass cells through the strainer and centrifuged a second time 750rcf 7 min 4\u00b0C to pellet the cells. The cells were resuspended in 100\u03bcL of resuspension buffer centrifugated 750rcf 7min 4\u00b0C and the pellet was resuspended in 50\u03bcL 0.04% BSA in PBS. 5\u03bcl of cells were then combined with 5\u03bcl of Hoechst Invitrogen H3570 incubated for 10min and transferred to a hemocytometer Bulldogbio NC1731934 to determine cell concentration. An additional 5\u03bcl of cells were incubated with Trypan blue Sigma T8154 for 5min transferred to a hemocytometer and counted to assess cell viability. Samples with > 70% viability were then submitted for single cell sequencing. For snRNA seq 30 \u00b5l of isolated nuclei at a concentration of 1000 nuclei/\u00b5l was submitted to Genome Technology Access Center at McDonnel Genome Institute of Washington University. Two biological replicates of each genotype were used. cDNA was prepared post the GEM generation and barcoding followed by the GEM RT reaction and bead cleanup steps. cDNA was amplified for 11 13 cycles then purified using SPRIselect beads. Purified cDNA samples were then run on a Bioanalyzer to determine the cDNA concentration. GEX libraries were prepared as recommended by the 10x Genomics Chromium Single Cell three prime Reagent Kits User Guide v3.1 Chemistry Dual Index with appropriate modifications to the PCR cycles based on the calculated cDNA concentration. For sample preparation on the 10x Genomics platform the Chromium Next GEM Single Cell three prime Kit v3.1 16 rxns PN 1000268 Chromium Next GEM Chip G Single Cell Kit 48 rxns PN 1000120 and Dual Index Kit TT Set A 96 rxns PN 1000215 were used. The concentration of each library was accurately determined through qPCR utilizing the KAPA library Quantification Kit according to the manufacturer's protocol KAPA Biosystems/Roche to produce cluster counts appropriate for the Illumina NovaSeq6000 instrument. Normalized libraries were sequenced on a NovaSeq6000 S4 Flow Cell using the XP workflow and a 50x10x16x150 sequencing recipe according to manufacturer protocol. A median sequencing depth of 50 000 reads/cell was targeted for each Gene Expression Library.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP590547", null, null, "AJAH-18300_Red-18300_mCherry_Positive-lib1_S2_L004_R1_001.fastq.gz AJAH-18300_Red-18300_mCherry_Positive-lib1_S2_L004_R2_001.fastq.gz", "fastq fastq", 84014647022.0, 471992399.0, "GSM9034428 r1", "0:28 1:150", "A:24181834463;C:18988262388;G:20195117959;T:20647899177;N:1533035", 28, 150, null, null, 24181834463, 18988262388, 20195117959, 20647899177, 1533035, "SRX29085353", "SRS25297141", "SRA2144659", "Johnson Lab, Developmental Biology, Washington University in St.Louis", "Johnson Lab, Developmental Biology, Washington University in St.Louis", 2, 0.00859, 0.93077, 0.00306, 0.13947, 0.99393, 0.81807, 0.39035, 0.66419, 28, 150, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2025-06-06", "Larval", "Larval", "Trunk", "Surface Structure"], [36248, "SRR33873805", "SRX29085352", "SRS25297140", "SRP590547", "PRJNA1272846", "Organism wide contributions to systemic skeletal muscle repair in larval zebrafish.", "GSE299146", "Transcriptome Analysis", "We developed a systemic muscle injury model in zebrafish. Single cell transcriptomic analysis of muscle and non muscle tissues revealed that systemic and local muscle injuries elicit distinct cellular molecular responses both quantitatively and qualitatively. These studies suggest that large and small scale muscle injuries activate different regenerative programs resulting in either systemic or local repair. Overall design: To characterize the regenerative responses and signaling pathways activated post systemic or local muscle injury we generated Tgactc1b:NTR mCherry transgenic zebrafish lines.At 4 dpf transgenic larvae were treated with MTZ overnight to systemically injure all myofibers or were subjected to local mechanical injury needlestick of 2 3 somites.Uninjured and systemically injured larvae were collected at 1 2 and 4 xxx post injury. Mechanically injured larvae were collected at 2 xxx post injury. Sequencing results were compared between uninjured systemically injured and mechanically injured siblings.", null, null, null, "larval trunk 1dpi Negative Control", "GSM9034427", null, "source name:Trunk|tissue:Trunk|genotype:Tgactc1b:NTR mCherry|treatment:Fish Water|batch:11/4/2024|geo loc name:missing|collection date:missing", "larval trunk 1dpi Negative Control", "post sequencing the Illumina output was processed using the CellRanger v8.0.1 pipeline to generate gene barcode count matrices. A custom reference genome was made with the \u201ccellranger mkref\u201d command using the fasta file of zebrafish reference genome GRCz11 constructed from the Ensemble genome build https://useast.ensembl.org/Danio rerio/Info/Index and the sorted Gene Transfer Format file v4.3.2 from the improved zebrafish transcriptome annotation Lawson et al. 2020. Base call files for each sample from Illumina were demultiplexed into FASTQ reads. Then the \u201ccellranger count\u201d pipeline was used to align sequencing reads in FASTQ files to the custom reference genome. Both exon and intron sequences were included during the alignment. The filtered gene barcode count matrices generated by \u201ccellranger count\u201d was used for downstream analysis. Datasets were integrated and analyzed using Seurat v4.4.0 package with R v4.4.2Stuart etal. 2019; Team 2024. Each sample count matrix was filtered for genes that were expressed in at least 3 cells and cells expressing at least 200 genes followed by cell quality assessment usingcommonly used QC matrixes Ilicic et al. 2016. Cells having a unique number of genes between 200 and 6500 mitochondrial gene percentage <5 and total number of reads UMIs between 300and 35000 were used for downstream processing. Each dataset was independently normalizedand scaled using the \u201cSCTransform\u201d function which is an improved method for normalization that performs a variance stabilizing transformation using negative binomial regression Hafemeisterand Satija 2019. Standard integration workflow of Seurat was used to identify shared sources of variation across experiments as well as mutual nearest neighbors Butler et al. 2018; Haghverdiet al. 2018. Integration features were selected based on the top 6000 highly variable features using \u201cSelectIntegrationFeatures\u201d function nfeatures\u2009=\u20096000 which was used as input for the\u201canchor.features\u201d argument of the \u201cFindIntegrationAnchors\u201d function. PCA analysis was performed on the 6000 variable features and the top 50 principal components selected based on the elbow plot heuristic which measures the contribution of variation in each component. These 50 principal components were used in \u201cFindNeighbors\u201d and \u201cFindClusters\u201d functions to perform graph based clustering on a shared nearest neighbor graph Levine et al. 2015; Xu and Su 2015. Louvain algorithm was used for modularity optimization in cell clustering using \u201cFindClusters\u201d function. The resolution parameter res\u2009=\u20090.3 that determines the granularity of clusteringwas selected by visually inspecting clusters with resolutions ranging between 0.1 and 2.0 as well as clustree graph Zappia and Oshlack 2018. Uniform Manifold Approximation and Reduction UMAP was used for non linear dimensional reduction of the first 50 principal components and visualize the data using \u201cRunUMAP\u201d function Becht et al. 2018. Data was graphed using different plot functions such as \u201cDimPlot\u201d \u201cVlnPlot\u201d \u201cFeaturePlot\u201d \u201cDotplot\u201d and \u201cDoHeatmap\u201d to view the cell cluster identity and marker gene expression. Cell proportions were extracted using the \u201ctable\u201d and \u201cprop.table\u201d functions. Differential gene expression for individual clusters was identified using Wilcoxon rank sum test in the \u201cFindAllMarkers\u201d function. Marker genes detected in at least 25% of the clustered cells and had a positive average log2FC were reported. Muscle cells identified from the complete dataset were subclustered using the \u201csubset\u201d function for subcluster analysis. The muscle subset was again normalized and scaled using the \u201cSCTransform\u201d function with glmGamPoi method Ahlmann Eltze and Huber 2021. Fifty principal components were used and the resolution parameter was set to 0.4. Downstream analysis was done as described above for the integrated analysis. We used a zebrafish single atlas Sur et al. 2023 to generate a database of markers for each tissue and cell type Table S1. The differentially expressed markers of each cluster were crossreferenced with our compiled database using our \u201cDE Marker Scoring\u201d algorithm Saraswathy et al. 2024. For every matching marker gene one point was given to the respective cluster under the column name with matching cell identity. Iteration over every marker gene was performed to generate a scoring matrix with varying points for each cluster against the different cell identities compiled in the database Table S2 sheet: scoring. The \u201cphyper\u201d function in R was then used to calculate one tailed binomial probabilities using hypergeometric distribution for the total score obtained from each cluster against each cell identity in the database Table S2 sheet: Binomial probability. \u2212log10 of probability values were obtained for plotting the heatmap Table S2 sheet:\u2212log10P. The resulting values were scaled from 0 to 100 and plotted as a heatmap using GraphPad prism. Each cluster was given an identity based on the maximum \u2212log10 p score obtained in the heatmap. The top DE markers of clusters with ambiguous scores were manually annotated using the \u201cident genes\u201d from the zebrafish single atlas Sur et al. 2023 and literature search McKellar et al. 2021. Top DE markers generated for each cluster is given in Table S3 sheet:topDEmarkers.all.clusters \u201cRenameIdents\u201d function was used to assign identity to each cluster. To confirm the assigned cluster identities enrichment of classical markers of respective cell types were tested using Dot plot. The R package CellChat v2.1.2 was used to evaluate regenerative cell cell interactions post local and systemic muscle injury Jin et al. 2021. CellChat models the probability of cell cell communication by integrating our gene expression data with a database of known interaction between signaling ligands receptors and their cofactors CellChatDB. The RNA data was used to create CellChat object using \u201ccreateCellChat\u201d function followed by the recommended preprocessing functions with default parameters for the analysis of individual datasets. Truncated mean method with 10% trimmed observation was used to compute average gene expression per cell group for the complete dataset. The default trimean method was used to compute average gene expression for the CellChat analysis. CellChatDB.zebrafish was used to infer cell cell communication. All categories of ligand receptor interactions in the database were used in the analysis. Communications involving less than 10 cells were excluded. The \u201cnetAnalysis computeCentrality\u201d function was used to calculate network centrality scores at each time point. Functions such as \u201cnetVisual circle\u201d \u201cnetAnalysis contribution\u201d \u201cnetVisual aggregate\u201d \u201cnetVisual bubble\u201d \u201cnetAnalysis signalingRole heatmap\u201d and \u201cnetAnalysis signalingRole scatter\u201d were used to generate different plots used in this paper. Assembly: zebrafish reference genome GRCz11 and the sorted Gene Transfer Format file v4.3.2 from the improved zebrafish transcriptome annotation Lawson et al. 2020. Supplementary files format and content: Compressed Filtered Feature and Barcode files as .tsv file and count matrices in .mtx file format.", "Trunk", "Fish were treated with 12 hours of metronidazole or were stuck locally with a needle", "15 larvae per cohort were dissected to remove the head caudal fin and internal organs and then processed as described Farnsworth DB 459 2020. For tissue lysis 500\u03bcL of dissociation buffer 2ug/ul Collagenase P 2mM CaCl2 0.2 ul DNaseI 0.25% Trypsin in 1X PBS was added to the samples and incubated at 28 \u00b0C until samples were visually dissociated 15min. Dissociation was stopped with equal volume of stop buffer 10% FBS 0.001mM EDTA in 1X PBS. Samples were centrifuged at 750rcf for 7min at 4\u00b0C the supernatant was discarded and the pellet was resuspended in 100\u03bcL of resuspension buffer 1% FBS 2mM CaCl2 1X Penicillin/Streptomycin in DMEM. The suspension was strained through 20\u03bcm cell strainer Pluriselect USA 43 10020 40 centrifuged once 500rcf 1 min 4\u00b0C to pass cells through the strainer and centrifuged a second time 750rcf 7 min 4\u00b0C to pellet the cells. The cells were resuspended in 100\u03bcL of resuspension buffer centrifugated 750rcf 7min 4\u00b0C and the pellet was resuspended in 50\u03bcL 0.04% BSA in PBS. 5\u03bcl of cells were then combined with 5\u03bcl of Hoechst Invitrogen H3570 incubated for 10min and transferred to a hemocytometer Bulldogbio NC1731934 to determine cell concentration. An additional 5\u03bcl of cells were incubated with Trypan blue Sigma T8154 for 5min transferred to a hemocytometer and counted to assess cell viability. Samples with > 70% viability were then submitted for single cell sequencing. For snRNA seq 30 \u00b5l of isolated nuclei at a concentration of 1000 nuclei/\u00b5l was submitted to Genome Technology Access Center at McDonnel Genome Institute of Washington University. Two biological replicates of each genotype were used. cDNA was prepared post the GEM generation and barcoding followed by the GEM RT reaction and bead cleanup steps. cDNA was amplified for 11 13 cycles then purified using SPRIselect beads. Purified cDNA samples were then run on a Bioanalyzer to determine the cDNA concentration. GEX libraries were prepared as recommended by the 10x Genomics Chromium Single Cell 3\u2019 Reagent Kits User Guide v3.1 Chemistry Dual Index with appropriate modifications to the PCR cycles based on the calculated cDNA concentration. For sample preparation on the 10x Genomics platform the Chromium Next GEM Single Cell 3\u2019 Kit v3.1 16 rxns PN 1000268 Chromium Next GEM Chip G Single Cell Kit 48 rxns PN 1000120 and Dual Index Kit TT Set A 96 rxns PN 1000215 were used. The concentration of each library was accurately determined through qPCR utilizing the KAPA library Quantification Kit according to the manufacturer\u2019s protocol KAPA Biosystems/Roche to produce cluster counts appropriate for the Illumina NovaSeq6000 instrument. Normalized libraries were sequenced on a NovaSeq6000 S4 Flow Cell using the XP workflow and a 50x10x16x150 sequencing recipe according to manufacturer protocol. A median sequencing depth of 50 000 reads/cell was targeted for each Gene Expression Library.", "Larval zebrafish of 4 dpf underwent drug treatments or needle stick injuries for muscle ablation", "tissue:Trunk|genotype:Tgactc1b:NTR mCherry|treatment:Fish Water|batch:11/4/2024", "GSM9034427", "GSM9034427: larval trunk 1dpi Negative Control; Danio rerio; RNA Seq", "GSM9034427 r1", "GSM9034427", "1", "15 larvae per cohort were dissected to remove the head caudal fin and internal organs and then processed as described Farnsworth DB 459 2020. For tissue lysis 500\u03bcL of dissociation buffer 2ug/ul Collagenase P 2mM CaCl2 0.2 ul DNaseI 0.25% Trypsin in 1X PBS was added to the samples and incubated at 28 \u00b0C until samples were visually dissociated 15min. Dissociation was stopped with equal volume of stop buffer 10% FBS 0.001mM EDTA in 1X PBS. Samples were centrifuged at 750rcf for 7min at 4\u00b0C the supernatant was discarded and the pellet was resuspended in 100\u03bcL of resuspension buffer 1% FBS 2mM CaCl2 1X Penicillin/Streptomycin in DMEM. The suspension was strained through 20\u03bcm cell strainer Pluriselect USA 43 10020 40 centrifuged once 500rcf 1 min 4\u00b0C to pass cells through the strainer and centrifuged a second time 750rcf 7 min 4\u00b0C to pellet the cells. The cells were resuspended in 100\u03bcL of resuspension buffer centrifugated 750rcf 7min 4\u00b0C and the pellet was resuspended in 50\u03bcL 0.04% BSA in PBS. 5\u03bcl of cells were then combined with 5\u03bcl of Hoechst Invitrogen H3570 incubated for 10min and transferred to a hemocytometer Bulldogbio NC1731934 to determine cell concentration. An additional 5\u03bcl of cells were incubated with Trypan blue Sigma T8154 for 5min transferred to a hemocytometer and counted to assess cell viability. Samples with > 70% viability were then submitted for single cell sequencing. For snRNA seq 30 \u00b5l of isolated nuclei at a concentration of 1000 nuclei/\u00b5l was submitted to Genome Technology Access Center at McDonnel Genome Institute of Washington University. Two biological replicates of each genotype were used. cDNA was prepared post the GEM generation and barcoding followed by the GEM RT reaction and bead cleanup steps. cDNA was amplified for 11 13 cycles then purified using SPRIselect beads. Purified cDNA samples were then run on a Bioanalyzer to determine the cDNA concentration. GEX libraries were prepared as recommended by the 10x Genomics Chromium Single Cell three prime Reagent Kits User Guide v3.1 Chemistry Dual Index with appropriate modifications to the PCR cycles based on the calculated cDNA concentration. For sample preparation on the 10x Genomics platform the Chromium Next GEM Single Cell three prime Kit v3.1 16 rxns PN 1000268 Chromium Next GEM Chip G Single Cell Kit 48 rxns PN 1000120 and Dual Index Kit TT Set A 96 rxns PN 1000215 were used. The concentration of each library was accurately determined through qPCR utilizing the KAPA library Quantification Kit according to the manufacturer's protocol KAPA Biosystems/Roche to produce cluster counts appropriate for the Illumina NovaSeq6000 instrument. Normalized libraries were sequenced on a NovaSeq6000 S4 Flow Cell using the XP workflow and a 50x10x16x150 sequencing recipe according to manufacturer protocol. A median sequencing depth of 50 000 reads/cell was targeted for each Gene Expression Library.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP590547", null, null, "LIB065814-DIL01_22CNHTLT4_S90_L008_R1_001.fastq.gz LIB065814-DIL01_22CNHTLT4_S90_L008_R2_001.fastq.gz", "fastq fastq", 96199623993.0, 537428067.0, "GSM9034427 r1", "0:28 1:151", "A:26836117761;C:21626512077;G:22419696915;T:25306734573;N:10562667", 28, 151, null, null, 26836117761, 21626512077, 22419696915, 25306734573, 10562667, "SRX29085352", "SRS25297140", "SRA2144659", "Johnson Lab, Developmental Biology, Washington University in St.Louis", "Johnson Lab, Developmental Biology, Washington University in St.Louis", 2, 0.01026, 0.90959, 0.00375, 0.1621, 0.99019, 0.80945, 0.41304, 0.54052, 28, 151, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2025-06-06", "Larval", "Larval", "Trunk", "Surface Structure"], [43983, "SRR6811832", "SRX3768872", "SRS3023386", "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, "Larva F1 2 scar", "GSM3032175", null, "source name:Full organism|strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva", "Larva F1 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. Genome build: N/A Supplementary files format and content: List of scar transcripts with CIGAR cell name cell barcode and UMI sequence.", "Full organism", null, "Single cell dissociation. 10X Genomics Chromium", null, "strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva", "GSM3032175", "GSM3032175: Larva F1 2 scar; Danio rerio; OTHER", "GSM3032175", null, "1", "Single cell dissociation. 10X Genomics Chromium", "GEO Accession:GSM3032175", "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina HiSeq 2500", null, "SRP121343", null, null, "F1_2_scar_R1.fastq.gz F1_2_scar_R2.fastq.gz", "fastq fastq", 9301928572.0, 75015553.0, "GSM3032175 r1", "0:26 1:98", "A:2682085389;C:3008788535;G:2093169318;T:1516220703;N:1664627", 26, 98, null, null, 2682085389, 3008788535, 2093169318, 1516220703, 1664627, "SRX3768872", "SRS3023386", "SRA623333", "GEO", "Max Delbr\u00fcck Center", 2, 0.0001, 0.00173, 4e-05, 8e-05, 0.99983, 0.99667, 0.33333, 0.531, 26, 98, "T", "T", "mates < 9% mapping rate", "illumina", "hiseq_era", "unknown", "other", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2018-03-06", "Larval", "Larval", "Trunk", "Surface Structure"], [43984, "SRR6811831", "SRX3768871", "SRS3023388", "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, "Larva F1 1 scar", "GSM3032174", null, "source name:Full organism|strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva", "Larva F1 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. Genome build: N/A Supplementary files format and content: List of scar transcripts with CIGAR cell name cell barcode and UMI sequence.", "Full organism", null, "Single cell dissociation. 10X Genomics Chromium", null, "strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva", "GSM3032174", "GSM3032174: Larva F1 1 scar; Danio rerio; OTHER", "GSM3032174", null, "1", "Single cell dissociation. 10X Genomics Chromium", "GEO Accession:GSM3032174", "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina HiSeq 2500", null, "SRP121343", null, null, "F1_1_scar_R1.fastq.gz F1_1_scar_R2.fastq.gz", "fastq fastq", 7772713576.0, 62683174.0, "GSM3032174 r1", "0:26 1:98", "A:2222016153;C:2555237987;G:1722216404;T:1271855931;N:1387101", 26, 98, null, null, 2222016153, 2555237987, 1722216404, 1271855931, 1387101, "SRX3768871", "SRS3023388", "SRA623333", "GEO", "Max Delbr\u00fcck Center", 2, 0.00014, 0.00171, 8e-05, 0.00012, 0.99985, 0.99642, 0.44444, 0.45454, 26, 98, "T", "T", "mates < 9% mapping rate", "illumina", "hiseq_era", "unknown", "other", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2018-03-06", "Larval", "Larval", "Trunk", "Surface Structure"], [43985, "SRR6811830", "SRX3768870", "SRS3023387", "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, "Larva F1 2 mRNA", "GSM3032173", null, "source name:Full organism|strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva", "Larva F1 2 mRNA", "Alignment and transcript counting of libraries were done using Cell Ranger 2.0.2. Cell numbers to be extracted were set at a minimum of 6000 but were increased if there were substantially more cells with more than 500 unique transcripts. Exact numbers can be found in Supplementary Table 1 of publication. Genome build: GRCz10 release 90 Supplementary files format and content: * matrix.mtx: Single cell transcript count table; * barcodes.tsv: List of cell barcodes.", "Full organism", null, "Single cell dissociation. 10X Genomics Chromium", null, "strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva", "GSM3032173", "GSM3032173: Larva F1 2 mRNA; Danio rerio; RNA Seq", "GSM3032173", null, "1", "Single cell dissociation. 10X Genomics Chromium", "GEO Accession:GSM3032173", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina HiSeq 2500", null, "SRP121343", null, null, "F1_2_wt_R1.fastq.gz F1_2_wt_R2.fastq.gz", "fastq fastq", 29997480708.0, 241915167.0, "GSM3032173 r1", "0:26 1:98", "A:8264355452;C:6830431714;G:7093261338;T:7804053400;N:5378804", 26, 98, null, null, 8264355452, 6830431714, 7093261338, 7804053400, 5378804, "SRX3768870", "SRS3023387", "SRA623333", "GEO", "Max Delbr\u00fcck Center", 2, 0.00307, 0.94486, 0.00051, 0.08199, 0.99431, 0.82509, 0.36875, 0.43599, 26, 98, "T", "B", "sc-like readlen", "illumina", "hiseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2018-03-06", "Larval", "Larval", "Trunk", "Surface Structure"], [43986, "SRR6811829", "SRX3768869", "SRS3023385", "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, "Larva F1 1 mRNA", "GSM3032172", null, "source name:Full organism|strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva", "Larva F1 1 mRNA", "Alignment and transcript counting of libraries were done using Cell Ranger 2.0.2. Cell numbers to be extracted were set at a minimum of 6000 but were increased if there were substantially more cells with more than 500 unique transcripts. Exact numbers can be found in Supplementary Table 1 of publication. Genome build: GRCz10 release 90 Supplementary files format and content: * matrix.mtx: Single cell transcript count table; * barcodes.tsv: List of cell barcodes.", "Full organism", null, "Single cell dissociation. 10X Genomics Chromium", null, "strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva", "GSM3032172", "GSM3032172: Larva F1 1 mRNA; Danio rerio; RNA Seq", "GSM3032172", null, "1", "Single cell dissociation. 10X Genomics Chromium", "GEO Accession:GSM3032172", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina HiSeq 2500", null, "SRP121343", null, null, "F1_1_wt_R1.fastq.gz F1_1_wt_R2.fastq.gz", "fastq fastq", 26685876072.0, 215208678.0, "GSM3032172 r1", "0:26 1:98", "A:7365353958;C:6068313931;G:6251004125;T:6996410946;N:4793112", 26, 98, null, null, 7365353958, 6068313931, 6251004125, 6996410946, 4793112, "SRX3768869", "SRS3023385", "SRA623333", "GEO", "Max Delbr\u00fcck Center", 2, 0.00255, 0.93758, 0.00046, 0.08179, 0.99515, 0.82637, 0.35368, 0.46605, 26, 98, "T", "B", "sc-like readlen", "illumina", "hiseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2018-03-06", "Larval", "Larval", "Trunk", "Surface Structure"], [43991, "SRR6811824", "SRX3768864", "SRS3023381", "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, "Larva 5 scar", "GSM3032167", null, "source name:Full organism|strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva", "Larva 5 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.", "Full organism", null, "Single cell dissociation. 10X Genomics Chromium", null, "strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva", "GSM3032167", "GSM3032167: Larva 5 scar; Danio rerio; OTHER", "GSM3032167", null, "1", "Single cell dissociation. 10X Genomics Chromium", "GEO Accession:GSM3032167", "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina HiSeq 2500", null, "SRP121343", null, null, "Z5_scar_R1.fastq.gz Z5_scar_R2.fastq.gz", "fastq fastq", 7672645700.0, 61876175.0, "GSM3032167 r1", "0:26 1:98", "A:2173948352;C:2439410929;G:1714624642;T:1343296377;N:1365400", 26, 98, null, null, 2173948352, 2439410929, 1714624642, 1343296377, 1365400, "SRX3768864", "SRS3023381", "SRA623333", "GEO", "Max Delbr\u00fcck Center", 2, 0.00013, 0.00164, 9e-05, 8e-05, 0.99989, 0.99669, 0.83333, 0.4918, 26, 98, "T", "T", "mates < 9% mapping rate", "illumina", "hiseq_era", "unknown", "other", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2018-03-06", "Larval", "Larval", "Trunk", "Surface Structure"], [43992, "SRR6811823", "SRX3768863", "SRS3023380", "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, "Larva 4 scar", "GSM3032166", null, "source name:Full organism|strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva", "Larva 4 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.", "Full organism", null, "Single cell dissociation. 10X Genomics Chromium", null, "strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva", "GSM3032166", "GSM3032166: Larva 4 scar; Danio rerio; OTHER", "GSM3032166", null, "1", "Single cell dissociation. 10X Genomics Chromium", "GEO Accession:GSM3032166", "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina HiSeq 2500", null, "SRP121343", null, null, "Z4_scar_R1.fastq.gz Z4_scar_R2.fastq.gz", "fastq fastq", 7236183804.0, 58356321.0, "GSM3032166 r1", "0:26 1:98", "A:2080254513;C:2296727471;G:1625115068;T:1232786300;N:1300452", 26, 98, null, null, 2080254513, 2296727471, 1625115068, 1232786300, 1300452, "SRX3768863", "SRS3023380", "SRA623333", "GEO", "Max Delbr\u00fcck Center", 2, 0.00014, 0.0016, 0.00011, 7e-05, 0.99993, 0.99634, 0.33333, 0.46694, 26, 98, "T", "T", "mates < 9% mapping rate", "illumina", "hiseq_era", "unknown", "other", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2018-03-06", "Larval", "Larval", "Trunk", "Surface Structure"], [43997, "SRR6811818", "SRX3768858", "SRS3023376", "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, "Larva 5 mRNA", "GSM3032161", null, "source name:Full organism|strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva", "Larva 5 mRNA", "Alignment and transcript counting of libraries were done using Cell Ranger 2.0.2. Cell numbers to be extracted were set at a minimum of 6000 but were increased if there were substantially more cells with more than 500 unique transcripts. Exact numbers can be found in Supplementary Table 1 of publication. Genome build: GRCz10 release 90 Supplementary files format and content: * matrix.mtx: Single cell transcript count table; * barcodes.tsv: List of cell barcodes.", "Full organism", null, "Single cell dissociation. 10X Genomics Chromium", null, "strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva", "GSM3032161", "GSM3032161: Larva 5 mRNA; Danio rerio; RNA Seq", "GSM3032161", null, "1", "Single cell dissociation. 10X Genomics Chromium", "GEO Accession:GSM3032161", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina HiSeq 2500", null, "SRP121343", null, null, "Z5_wt_R1.fastq.gz Z5_wt_R2.fastq.gz", "fastq fastq", 27409556812.0, 221044813.0, "GSM3032161 r1", "0:26 1:98", "A:7637677199;C:6210942203;G:6438364980;T:7117667800;N:4904630", 26, 98, null, null, 7637677199, 6210942203, 6438364980, 7117667800, 4904630, "SRX3768858", "SRS3023376", "SRA623333", "GEO", "Max Delbr\u00fcck Center", 2, 0.00523, 0.92734, 0.0008, 0.0687, 0.98916, 0.81479, 0.44117, 0.50243, 26, 98, "T", "B", "sc-like readlen", "illumina", "hiseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2018-03-06", "Larval", "Larval", "Trunk", "Surface Structure"], [43998, "SRR6811817", "SRX3768857", "SRS3023374", "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, "Larva 4 mRNA", "GSM3032160", null, "source name:Full organism|strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva", "Larva 4 mRNA", "Alignment and transcript counting of libraries were done using Cell Ranger 2.0.2. Cell numbers to be extracted were set at a minimum of 6000 but were increased if there were substantially more cells with more than 500 unique transcripts. Exact numbers can be found in Supplementary Table 1 of publication. Genome build: GRCz10 release 90 Supplementary files format and content: * matrix.mtx: Single cell transcript count table; * barcodes.tsv: List of cell barcodes.", "Full organism", null, "Single cell dissociation. 10X Genomics Chromium", null, "strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva", "GSM3032160", "GSM3032160: Larva 4 mRNA; Danio rerio; RNA Seq", "GSM3032160", null, "1", "Single cell dissociation. 10X Genomics Chromium", "GEO Accession:GSM3032160", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina HiSeq 2500", null, "SRP121343", null, null, "Z4_wt_R2.fastq.gz Z4_wt_R1.fastq.gz", "fastq fastq", 19775711456.0, 159481544.0, "GSM3032160 r1", "0:26 1:98", "A:5483727144;C:4548396363;G:4737957565;T:5002119078;N:3511306", 26, 98, null, null, 5483727144, 4548396363, 4737957565, 5002119078, 3511306, "SRX3768857", "SRS3023374", "SRA623333", "GEO", "Max Delbr\u00fcck Center", 2, 0.00331, 0.93006, 0.00057, 0.05973, 0.99253, 0.82369, 0.38666, 0.48899, 26, 98, "T", "B", "sc-like readlen", "illumina", "hiseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2018-03-06", "Larval", "Larval", "Trunk", "Surface Structure"], [43999, "SRR6811816", "SRX3768856", "SRS3023373", "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, "Larva 3 mRNA", "GSM3032159", null, "source name:Full organism|strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva", "Larva 3 mRNA", "Alignment and transcript counting of libraries were done using Cell Ranger 2.0.2. Cell numbers to be extracted were set at a minimum of 6000 but were increased if there were substantially more cells with more than 500 unique transcripts. Exact numbers can be found in Supplementary Table 1 of publication. Genome build: GRCz10 release 90 Supplementary files format and content: * matrix.mtx: Single cell transcript count table; * barcodes.tsv: List of cell barcodes.", "Full organism", null, "Single cell dissociation. 10X Genomics Chromium", null, "strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva", "GSM3032159", "GSM3032159: Larva 3 mRNA; Danio rerio; RNA Seq", "GSM3032159", null, "1", "Single cell dissociation. 10X Genomics Chromium", "GEO Accession:GSM3032159", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina HiSeq 2500", null, "SRP121343", null, null, "Z3_wt_R1.fastq.gz Z3_wt_R2.fastq.gz Z3_wt_R3.fastq.gz", "fastq fastq fastq", 8016913120.0, 50105707.0, "GSM3032159 r1", "0:130 1:14 2:16", "A:2047850756;C:1318672327;G:1403772432;T:1743394108;N:52287", 130, 14, 16, null, 2047850756, 1318672327, 1403772432, 1743394108, 52287, "SRX3768856", "SRS3023373", "SRA623333", "GEO", "Max Delbr\u00fcck Center", 1, 0.87661, null, 0.06466, null, 0.86614, null, 0.53364, null, 130, null, "B", null, "usable mapping rate", "illumina", "hiseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2018-03-06", "Larval", "Larval", "Trunk", "Surface Structure"], [44005, "SRR6211487", "SRX3320762", "SRS2626335", "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, "Larva 2 mRNA", "GSM2830057", null, "source name:Full organism|strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva", "Larva 2 mRNA", "Alignment and transcript counting of libraries were done using Cell Ranger 2.0.2. Cell numbers to be extracted were set at a minimum of 6000 but were increased if there were substantially more cells with more than 500 unique transcripts. Exact numbers can be found in Supplementary Table 1 in publication. Every sequencing read consists of a cellular barcode a UMI and a transcript sequence originating from an mRNA molecule. These transcript sequences were aligned using bwa aln3 with setting ' q 50' to a reference transcriptome constructed from Ensembl release 74 www.ensembl.org with extended three prime UTR regions. We filtered out all unmapped reads and all reads that were not uniquely mapped. post alignment we determined which cellular barcodes corresponded to cells. We defined a cell to be a cellular barcode with at least five hundred uniquely mapped molecules. For each cellular barcode we counted the number of molecules mapped to each gene using the UMI correction method described by Gr\u00fcn et al. This method corrects for the possibility of the same UMI being used for two different transcripts in the same cell with the formula t = K ln1 \u2013 k o/K with t the final number of transcripts k o the observed UMIs and K the total number of UMIs possible. As protection against barcode sequencing errors we counted the occurrence of each nucleotide for each barcode and filtered out barcodes in which one nucleotide occurred ten or more times. Furthermore we filtered out barcodes that were one nucleotide substitution removed from a barcode with at least eight times as many transcripts. Genome build: GRCz10 release 90 Supplementary files format and content: * matrix.mtx: Single cell transcript count table; * barcodes.tsv: List of cell barcodes.", "Full organism", null, "Single cell dissociation. 10X Genomics Chromium", null, "strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva", "GSM2830057", "GSM2830057: Larva 2 mRNA; Danio rerio; RNA Seq", "GSM2830057", null, "1", "Single cell dissociation. 10X Genomics Chromium", "GEO Accession:GSM2830057", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina HiSeq 2500", null, "SRP121343", null, null, "Z1_wt_R3.fastq.gz Z1_wt_R2.fastq.gz Z1_wt_R1.fastq.gz", "fastq fastq fastq", 28368351950.0, 232527475.0, "GSM2830057 r1", "0:98 1:14 2:10", "A:6582076349;C:4985163175;G:5131319282;T:6085835988;N:3297756", 98, 14, 10, null, 6582076349, 4985163175, 5131319282, 6085835988, 3297756, "SRX3320762", "SRS2626335", "SRA623333", "GEO", "Max Delbr\u00fcck Center", 1, 0.9378, null, 0.05825, null, 0.79687, null, 0.50342, null, 98, null, "B", null, "usable mapping rate", "illumina", "hiseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2017-10-24", "Larval", "Larval", "Trunk", "Surface Structure"], [44006, "SRR6211485", "SRX3320760", "SRS2626333", "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, "Larva 1 mRNA", "GSM2830056", null, "source name:Full organism|strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva", "Larva 1 mRNA", "Alignment and transcript counting of libraries were done using Cell Ranger 2.0.2. Cell numbers to be extracted were set at a minimum of 6000 but were increased if there were substantially more cells with more than 500 unique transcripts. Exact numbers can be found in Supplementary Table 1 in publication. Every sequencing read consists of a cellular barcode a UMI and a transcript sequence originating from an mRNA molecule. These transcript sequences were aligned using bwa aln3 with setting ' q 50' to a reference transcriptome constructed from Ensembl release 74 www.ensembl.org with extended three prime UTR regions. We filtered out all unmapped reads and all reads that were not uniquely mapped. post alignment we determined which cellular barcodes corresponded to cells. We defined a cell to be a cellular barcode with at least five hundred uniquely mapped molecules. For each cellular barcode we counted the number of molecules mapped to each gene using the UMI correction method described by Gr\u00fcn et al. This method corrects for the possibility of the same UMI being used for two different transcripts in the same cell with the formula t = K ln1 \u2013 k o/K with t the final number of transcripts k o the observed UMIs and K the total number of UMIs possible. As protection against barcode sequencing errors we counted the occurrence of each nucleotide for each barcode and filtered out barcodes in which one nucleotide occurred ten or more times. Furthermore we filtered out barcodes that were one nucleotide substitution removed from a barcode with at least eight times as many transcripts. Genome build: GRCz10 release 90 Supplementary files format and content: * matrix.mtx: Single cell transcript count table; * barcodes.tsv: List of cell barcodes.", "Full organism", null, "Single cell dissociation. 10X Genomics Chromium", null, "strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva", "GSM2830056", "GSM2830056: Larva 1 mRNA; Danio rerio; RNA Seq", "GSM2830056", null, "1", "Single cell dissociation. 10X Genomics Chromium", "GEO Accession:GSM2830056", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina HiSeq 2500", null, "SRP121343", null, null, "Z2_1_wt_R1.fastq.gz Z2_1_wt_R2.fastq.gz Z2_1_wt_R3.fastq.gz", "fastq fastq fastq", 36065037280.0, 225406483.0, "GSM2830056 r1", "0:130 1:14 2:16", "A:9121762570;C:5889322717;G:6251660049;T:8039869338;N:228116", 130, 14, 16, null, 9121762570, 5889322717, 6251660049, 8039869338, 228116, "SRX3320760", "SRS2626333", "SRA623333", "GEO", "Max Delbr\u00fcck Center", 1, 0.88569, null, 0.08353, null, 0.86016, null, 0.53379, null, 130, null, "B", null, "usable mapping rate", "illumina", "hiseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2017-10-24", "Larval", "Larval", "Trunk", "Surface Structure"], [44007, "SRR6211486", "SRX3320760", "SRS2626333", "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, "Larva 1 mRNA", "GSM2830056", null, "source name:Full organism|strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva", "Larva 1 mRNA", "Alignment and transcript counting of libraries were done using Cell Ranger 2.0.2. Cell numbers to be extracted were set at a minimum of 6000 but were increased if there were substantially more cells with more than 500 unique transcripts. Exact numbers can be found in Supplementary Table 1 in publication. Every sequencing read consists of a cellular barcode a UMI and a transcript sequence originating from an mRNA molecule. These transcript sequences were aligned using bwa aln3 with setting ' q 50' to a reference transcriptome constructed from Ensembl release 74 www.ensembl.org with extended three prime UTR regions. We filtered out all unmapped reads and all reads that were not uniquely mapped. post alignment we determined which cellular barcodes corresponded to cells. We defined a cell to be a cellular barcode with at least five hundred uniquely mapped molecules. For each cellular barcode we counted the number of molecules mapped to each gene using the UMI correction method described by Gr\u00fcn et al. This method corrects for the possibility of the same UMI being used for two different transcripts in the same cell with the formula t = K ln1 \u2013 k o/K with t the final number of transcripts k o the observed UMIs and K the total number of UMIs possible. As protection against barcode sequencing errors we counted the occurrence of each nucleotide for each barcode and filtered out barcodes in which one nucleotide occurred ten or more times. Furthermore we filtered out barcodes that were one nucleotide substitution removed from a barcode with at least eight times as many transcripts. Genome build: GRCz10 release 90 Supplementary files format and content: * matrix.mtx: Single cell transcript count table; * barcodes.tsv: List of cell barcodes.", "Full organism", null, "Single cell dissociation. 10X Genomics Chromium", null, "strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva", "GSM2830056", "GSM2830056: Larva 1 mRNA; Danio rerio; RNA Seq", "GSM2830056", null, "1", "Single cell dissociation. 10X Genomics Chromium", "GEO Accession:GSM2830056", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina HiSeq 2500", null, "SRP121343", null, null, "Z2_2_wt_R1.fastq.gz Z2_2_wt_R2.fastq.gz Z2_2_wt_R3.fastq.gz", "fastq fastq fastq", 7700646560.0, 48129041.0, "GSM2830056 r2", "0:130 1:14 2:16", "A:1890861891;C:1307860042;G:1403340071;T:1654667424;N:45902", 130, 14, 16, null, 1890861891, 1307860042, 1403340071, 1654667424, 45902, "SRX3320760", "SRS2626333", "SRA623333", "GEO", "Max Delbr\u00fcck Center", 1, 0.89198, null, 0.07477, null, 0.87288, null, 0.49519, null, 130, null, "B", null, "usable mapping rate", "illumina", "hiseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2017-10-24", "Larval", "Larval", "Trunk", "Surface Structure"], [44013, "SRR6211477", "SRX3320753", "SRS2626327", "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, "Larva 1 scar", "GSM2830049", null, "source name:Full organism|strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva", "Larva 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.", "Full organism", null, "Single cell dissociation. 10X Genomics Chromium", null, "strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva", "GSM2830049", "GSM2830049: Larva 1 scar; Danio rerio; OTHER", "GSM2830049", null, "1", "Single cell dissociation. 10X Genomics Chromium", "GEO Accession:GSM2830049", "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina HiSeq 2500", null, "SRP121343", null, null, "Z2_1_scar_R1.fastq.gz Z2_1_scar_R2.fastq.gz Z2_1_scar_R3.fastq.gz", "fastq fastq fastq", 1358915680.0, 8493223.0, "GSM2830049 r1", "0:130 1:14 2:16", "A:286107087;C:390283378;G:268551180;T:159171790;N:5555", 130, 14, 16, null, 286107087, 390283378, 268551180, 159171790, 5555, "SRX3320753", "SRS2626327", "SRA623333", "GEO", "Max Delbr\u00fcck Center", 1, 0.00515, null, 8e-05, null, 0.99959, null, 0.24561, null, 130, null, "T", null, "under 1.2% mapping rate", "illumina", "hiseq_era", "unknown", "other", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2017-10-24", "Larval", "Larval", "Trunk", "Surface Structure"], [44014, "SRR6211478", "SRX3320753", "SRS2626327", "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, "Larva 1 scar", "GSM2830049", null, "source name:Full organism|strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva", "Larva 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.", "Full organism", null, "Single cell dissociation. 10X Genomics Chromium", null, "strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva", "GSM2830049", "GSM2830049: Larva 1 scar; Danio rerio; OTHER", "GSM2830049", null, "1", "Single cell dissociation. 10X Genomics Chromium", "GEO Accession:GSM2830049", "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina HiSeq 2500", null, "SRP121343", null, null, "Z2_2_scar_R1.fastq.gz Z2_2_scar_R2.fastq.gz Z2_2_scar_R3.fastq.gz", "fastq fastq fastq", 1103410080.0, 6896313.0, "GSM2830049 r2", "0:130 1:14 2:16", "A:232542409;C:315925727;G:218437491;T:129610895;N:4168", 130, 14, 16, null, 232542409, 315925727, 218437491, 129610895, 4168, "SRX3320753", "SRS2626327", "SRA623333", "GEO", "Max Delbr\u00fcck Center", 1, 0.00786, null, 0.0, null, 0.99922, null, 0.31764, null, 130, null, "T", null, "under 1.2% mapping rate", "illumina", "hiseq_era", "unknown", "other", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2017-10-24", "Larval", "Larval", "Trunk", "Surface Structure"], [52244, "SRR9050631", "SRX5827022", "SRS4754836", "SRP198298", "PRJNA542704", "Thyroid hormone regulates distinct paths to maturation in pigment cell lineages", "GSE131136", "Transcriptome Analysis", "Early and post embryonic neural crest derived lineages in the zebrafish trunk in response to thyroid hormone modulation Overall design: Single cell RNA seq experiments were performed on the 10X Genomics platform from FAC sorted Sox10:CRE positive cells from 5dpf and post embryonic zebrafish trunks with and without xxx hormone.", null, "pubmed:31140974;pubmed:33933422", null, "Neural crest derived cells from hypothyroid post embryonic zebrafish trunks biological replicate 7", "GSM3764578", null, "tissue:sox10:Cre+ cells from post embryonic zebrafish trunk tissue|cell type:2650 cells from Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB FAC sorted mCherry+ cells from trunks. Fish range in stage from 7.2 10.4 SSL stage zebrafish. Thyroid ablation was performed at 4 dpf with metronidazole treatment.|treatment:Hypothyroid", "Neural crest derived cells from hypothyroid post embryonic zebrafish trunks biological replicate 7", "Expression matrix files and BAM files were generated using cellranger 10X genomics version 2.0.2 as described by the manufacturer using the commands cellranger demux and cellranger count. UMI count matrices representing the filtered set of barcodes representing cells were used as determined by cellranger. All samples were aggregated using the aggregate option in cellranger to normalize mean number of reads per cell across 10X libraries. Genome build: GRCz11 Supplementary files format and content: Expression matrix files and BAM files were generated using cellranger 10X genomics version 2.0.2 as described by the manufacturer using the commands cellranger demux and cellranger count. UMI count matrices representing the filtered set of barcodes representing cells were used as determined by cellranger. Expression matrices are output by cellranger and are in Matrix Market Exchange format and the gene and cell barcode name files that accompany these file are provided as TSV files.", "sox10:Cre+ cells from post embryonic zebrafish trunk tissue", "Transgenic zebrafish Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB were treated either metronidazole 10mM or a vehicle control DMSO at 4dpf. Trunks or skins were collected at a stage range of 7.2 10.4 SSL or 5 dpf as indicated in the sample name. Tissue was dissociated into a single cell suspension and FAC sorted for the presence of mCherry. Then cells were washed and loaded into the 10X chromium chip according to manufacturer recommendations.", "10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.", "Zebrafish were maintained at 28.5 \u00b0C under 14:10 light:dark cycles. All thyroid ablated Mtz treated and control DMSO treated Tgtg:nVenus v2a nfnB fish were kept under TH free conditions and were fed only Artemia rotifers enriched with TH free Algamac Aquafauna and bloodworms.", "cell type:2650 cells from Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB FAC sorted mCherry+ cells from trunks. Fish range in stage from 7.2 10.4 SSL stage zebrafish. Thyroid ablation was performed at 4 dpf with metronidazole treatment.|treatment:Hypothyroid", "GSM3764578", "GSM3764578: Neural crest derived cells from hypothyroid post embryonic zebrafish trunks biological replicate 7; Danio rerio; RNA Seq", "GSM3764578", null, "1", "10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.", null, "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP198298", null, "dangling references:treat as unmapped", "hypo5_possorted_genome_bam.bam", "10X Genomics bam file", 6174558858.0, 108325594.0, "GSM3764578 r1", "0:57", "A:1897524564;C:1180297377;G:1360942367;T:1732425907;N:3368643", 57, null, null, null, 1897524564, 1180297377, 1360942367, 1732425907, 3368643, "SRX5827022", "SRS4754836", "SRA886020", "GEO", "Biology, University of Virginia", 1, 0.91289, null, 0.25388, null, 0.82856, null, 0.50847, null, 57, null, "B", null, "usable mapping rate", "illumina", "nextseq", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2019-05-13", "Larval", "Larval", "Trunk", "Surface Structure"], [52245, "SRR9050630", "SRX5827021", "SRS4754835", "SRP198298", "PRJNA542704", "Thyroid hormone regulates distinct paths to maturation in pigment cell lineages", "GSE131136", "Transcriptome Analysis", "Early and post embryonic neural crest derived lineages in the zebrafish trunk in response to thyroid hormone modulation Overall design: Single cell RNA seq experiments were performed on the 10X Genomics platform from FAC sorted Sox10:CRE positive cells from 5dpf and post embryonic zebrafish trunks with and without xxx hormone.", null, "pubmed:31140974;pubmed:33933422", null, "Neural crest derived cells from hypothyroid post embryonic zebrafish trunks biological replicate 6", "GSM3764577", null, "tissue:sox10:Cre+ cells from post embryonic zebrafish trunk tissue|cell type:1888 cells from Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB FAC sorted mCherry+ cells from trunks. Fish range in stage from 7.2 10.4 SSL stage zebrafish. Thyroid ablation was performed at 4 dpf with metronidazole treatment.|treatment:Hypothyroid", "Neural crest derived cells from hypothyroid post embryonic zebrafish trunks biological replicate 6", "Expression matrix files and BAM files were generated using cellranger 10X genomics version 2.0.2 as described by the manufacturer using the commands cellranger demux and cellranger count. UMI count matrices representing the filtered set of barcodes representing cells were used as determined by cellranger. All samples were aggregated using the aggregate option in cellranger to normalize mean number of reads per cell across 10X libraries. Genome build: GRCz11 Supplementary files format and content: Expression matrix files and BAM files were generated using cellranger 10X genomics version 2.0.2 as described by the manufacturer using the commands cellranger demux and cellranger count. UMI count matrices representing the filtered set of barcodes representing cells were used as determined by cellranger. Expression matrices are output by cellranger and are in Matrix Market Exchange format and the gene and cell barcode name files that accompany these file are provided as TSV files.", "sox10:Cre+ cells from post embryonic zebrafish trunk tissue", "Transgenic zebrafish Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB were treated either metronidazole 10mM or a vehicle control DMSO at 4dpf. Trunks or skins were collected at a stage range of 7.2 10.4 SSL or 5 dpf as indicated in the sample name. Tissue was dissociated into a single cell suspension and FAC sorted for the presence of mCherry. Then cells were washed and loaded into the 10X chromium chip according to manufacturer recommendations.", "10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.", "Zebrafish were maintained at 28.5 \u00b0C under 14:10 light:dark cycles. All thyroid ablated Mtz treated and control DMSO treated Tgtg:nVenus v2a nfnB fish were kept under TH free conditions and were fed only Artemia rotifers enriched with TH free Algamac Aquafauna and bloodworms.", "cell type:1888 cells from Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB FAC sorted mCherry+ cells from trunks. Fish range in stage from 7.2 10.4 SSL stage zebrafish. Thyroid ablation was performed at 4 dpf with metronidazole treatment.|treatment:Hypothyroid", "GSM3764577", "GSM3764577: Neural crest derived cells from hypothyroid post embryonic zebrafish trunks biological replicate 6; Danio rerio; RNA Seq", "GSM3764577", null, "1", "10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.", null, "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP198298", null, "dangling references:treat as unmapped", "hypo4_possorted_genome_bam.bam", "10X Genomics bam file", 4410277587.0, 77373291.0, "GSM3764577 r1", "0:57", "A:1320513576;C:874241368;G:1044266437;T:1169033783;N:2222423", 57, null, null, null, 1320513576, 874241368, 1044266437, 1169033783, 2222423, "SRX5827021", "SRS4754835", "SRA886020", "GEO", "Biology, University of Virginia", 1, 0.92536, null, 0.20155, null, 0.83473, null, 0.50983, null, 57, null, "B", null, "usable mapping rate", "illumina", "nextseq", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2019-05-13", "Larval", "Larval", "Trunk", "Surface Structure"], [52246, "SRR9050629", "SRX5827020", "SRS4754834", "SRP198298", "PRJNA542704", "Thyroid hormone regulates distinct paths to maturation in pigment cell lineages", "GSE131136", "Transcriptome Analysis", "Early and post embryonic neural crest derived lineages in the zebrafish trunk in response to thyroid hormone modulation Overall design: Single cell RNA seq experiments were performed on the 10X Genomics platform from FAC sorted Sox10:CRE positive cells from 5dpf and post embryonic zebrafish trunks with and without xxx hormone.", null, "pubmed:31140974;pubmed:33933422", null, "Neural crest derived cells from hypothyroid post embryonic zebrafish trunks biological replicate 5", "GSM3764576", null, "tissue:sox10:Cre+ cells from post embryonic zebrafish trunk tissue|cell type:774 cells from Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB FAC sorted mCherry+ cells from trunks. Fish range in stage from 7.2 10.4 SSL stage zebrafish. Thyroid ablation was performed at 4 dpf with metronidazole treatment.|treatment:Hypothyroid", "Neural crest derived cells from hypothyroid post embryonic zebrafish trunks biological replicate 5", "Expression matrix files and BAM files were generated using cellranger 10X genomics version 2.0.2 as described by the manufacturer using the commands cellranger demux and cellranger count. UMI count matrices representing the filtered set of barcodes representing cells were used as determined by cellranger. All samples were aggregated using the aggregate option in cellranger to normalize mean number of reads per cell across 10X libraries. Genome build: GRCz11 Supplementary files format and content: Expression matrix files and BAM files were generated using cellranger 10X genomics version 2.0.2 as described by the manufacturer using the commands cellranger demux and cellranger count. UMI count matrices representing the filtered set of barcodes representing cells were used as determined by cellranger. Expression matrices are output by cellranger and are in Matrix Market Exchange format and the gene and cell barcode name files that accompany these file are provided as TSV files.", "sox10:Cre+ cells from post embryonic zebrafish trunk tissue", "Transgenic zebrafish Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB were treated either metronidazole 10mM or a vehicle control DMSO at 4dpf. Trunks or skins were collected at a stage range of 7.2 10.4 SSL or 5 dpf as indicated in the sample name. Tissue was dissociated into a single cell suspension and FAC sorted for the presence of mCherry. Then cells were washed and loaded into the 10X chromium chip according to manufacturer recommendations.", "10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.", "Zebrafish were maintained at 28.5 \u00b0C under 14:10 light:dark cycles. All thyroid ablated Mtz treated and control DMSO treated Tgtg:nVenus v2a nfnB fish were kept under TH free conditions and were fed only Artemia rotifers enriched with TH free Algamac Aquafauna and bloodworms.", "cell type:774 cells from Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB FAC sorted mCherry+ cells from trunks. Fish range in stage from 7.2 10.4 SSL stage zebrafish. Thyroid ablation was performed at 4 dpf with metronidazole treatment.|treatment:Hypothyroid", "GSM3764576", "GSM3764576: Neural crest derived cells from hypothyroid post embryonic zebrafish trunks biological replicate 5; Danio rerio; RNA Seq", "GSM3764576", null, "1", "10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.", null, "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP198298", null, "dangling references:treat as unmapped", "hypo3_possorted_genome_bam.bam", "10X Genomics bam file", 8444232738.0, 148144434.0, "GSM3764576 r1", "0:57", "A:2380116568;C:1626615273;G:2248860789;T:2185343861;N:3296247", 57, null, null, null, 2380116568, 1626615273, 2248860789, 2185343861, 3296247, "SRX5827020", "SRS4754834", "SRA886020", "GEO", "Biology, University of Virginia", 1, 0.91177, null, 0.16393, null, 0.80509, null, 0.514, null, 57, null, "B", null, "usable mapping rate", "illumina", "nextseq", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2019-05-13", "Larval", "Larval", "Trunk", "Surface Structure"], [52247, "SRR9050628", "SRX5827019", "SRS4754833", "SRP198298", "PRJNA542704", "Thyroid hormone regulates distinct paths to maturation in pigment cell lineages", "GSE131136", "Transcriptome Analysis", "Early and post embryonic neural crest derived lineages in the zebrafish trunk in response to thyroid hormone modulation Overall design: Single cell RNA seq experiments were performed on the 10X Genomics platform from FAC sorted Sox10:CRE positive cells from 5dpf and post embryonic zebrafish trunks with and without xxx hormone.", null, "pubmed:31140974;pubmed:33933422", null, "Neural crest derived cells from hypothyroid post embryonic zebrafish trunks biological replicate 4", "GSM3764575", null, "tissue:sox10:Cre+ cells from post embryonic zebrafish trunk tissue|cell type:941 cells from Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB FAC sorted mCherry+ cells from trunks. Fish range in stage from 7.2 10.4 SSL stage zebrafish. Thyroid ablation was performed at 4 dpf with metronidazole treatment.|treatment:Hypothyroid", "Neural crest derived cells from hypothyroid post embryonic zebrafish trunks biological replicate 4", "Expression matrix files and BAM files were generated using cellranger 10X genomics version 2.0.2 as described by the manufacturer using the commands cellranger demux and cellranger count. UMI count matrices representing the filtered set of barcodes representing cells were used as determined by cellranger. All samples were aggregated using the aggregate option in cellranger to normalize mean number of reads per cell across 10X libraries. Genome build: GRCz11 Supplementary files format and content: Expression matrix files and BAM files were generated using cellranger 10X genomics version 2.0.2 as described by the manufacturer using the commands cellranger demux and cellranger count. UMI count matrices representing the filtered set of barcodes representing cells were used as determined by cellranger. Expression matrices are output by cellranger and are in Matrix Market Exchange format and the gene and cell barcode name files that accompany these file are provided as TSV files.", "sox10:Cre+ cells from post embryonic zebrafish trunk tissue", "Transgenic zebrafish Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB were treated either metronidazole 10mM or a vehicle control DMSO at 4dpf. Trunks or skins were collected at a stage range of 7.2 10.4 SSL or 5 dpf as indicated in the sample name. Tissue was dissociated into a single cell suspension and FAC sorted for the presence of mCherry. Then cells were washed and loaded into the 10X chromium chip according to manufacturer recommendations.", "10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.", "Zebrafish were maintained at 28.5 \u00b0C under 14:10 light:dark cycles. All thyroid ablated Mtz treated and control DMSO treated Tgtg:nVenus v2a nfnB fish were kept under TH free conditions and were fed only Artemia rotifers enriched with TH free Algamac Aquafauna and bloodworms.", "cell type:941 cells from Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB FAC sorted mCherry+ cells from trunks. Fish range in stage from 7.2 10.4 SSL stage zebrafish. Thyroid ablation was performed at 4 dpf with metronidazole treatment.|treatment:Hypothyroid", "GSM3764575", "GSM3764575: Neural crest derived cells from hypothyroid post embryonic zebrafish trunks biological replicate 4; Danio rerio; RNA Seq", "GSM3764575", null, "1", "10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.", null, "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP198298", null, "dangling references:treat as unmapped", "hypo2_possorted_genome_bam.bam", "10X Genomics bam file", 8711801454.0, 152838622.0, "GSM3764575 r1", "0:57", "A:2469579044;C:1654897730;G:2303443265;T:2280478208;N:3403207", 57, null, null, null, 2469579044, 1654897730, 2303443265, 2280478208, 3403207, "SRX5827019", "SRS4754833", "SRA886020", "GEO", "Biology, University of Virginia", 1, 0.90749, null, 0.17908, null, 0.8017, null, 0.5124, null, 57, null, "B", null, "usable mapping rate", "illumina", "nextseq", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2019-05-13", "Larval", "Larval", "Trunk", "Surface Structure"], [52248, "SRR9050627", "SRX5827018", "SRS4754832", "SRP198298", "PRJNA542704", "Thyroid hormone regulates distinct paths to maturation in pigment cell lineages", "GSE131136", "Transcriptome Analysis", "Early and post embryonic neural crest derived lineages in the zebrafish trunk in response to thyroid hormone modulation Overall design: Single cell RNA seq experiments were performed on the 10X Genomics platform from FAC sorted Sox10:CRE positive cells from 5dpf and post embryonic zebrafish trunks with and without xxx hormone.", null, "pubmed:31140974;pubmed:33933422", null, "Neural crest derived cells from hypothyroid post embryonic zebrafish trunks biological replicate 3", "GSM3764574", null, "tissue:sox10:Cre+ cells from post embryonic zebrafish trunk tissue|cell type:1073 cells from Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB FAC sorted mCherry+ cells from trunks. Fish range in stage from 7.2 10.4 SSL stage zebrafish. Thyroid ablation was performed at 4 dpf with metronidazole treatment.|treatment:Hypothyroid", "Neural crest derived cells from hypothyroid post embryonic zebrafish trunks biological replicate 3", "Expression matrix files and BAM files were generated using cellranger 10X genomics version 2.0.2 as described by the manufacturer using the commands cellranger demux and cellranger count. UMI count matrices representing the filtered set of barcodes representing cells were used as determined by cellranger. All samples were aggregated using the aggregate option in cellranger to normalize mean number of reads per cell across 10X libraries. Genome build: GRCz11 Supplementary files format and content: Expression matrix files and BAM files were generated using cellranger 10X genomics version 2.0.2 as described by the manufacturer using the commands cellranger demux and cellranger count. UMI count matrices representing the filtered set of barcodes representing cells were used as determined by cellranger. Expression matrices are output by cellranger and are in Matrix Market Exchange format and the gene and cell barcode name files that accompany these file are provided as TSV files.", "sox10:Cre+ cells from post embryonic zebrafish trunk tissue", "Transgenic zebrafish Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB were treated either metronidazole 10mM or a vehicle control DMSO at 4dpf. Trunks or skins were collected at a stage range of 7.2 10.4 SSL or 5 dpf as indicated in the sample name. Tissue was dissociated into a single cell suspension and FAC sorted for the presence of mCherry. Then cells were washed and loaded into the 10X chromium chip according to manufacturer recommendations.", "10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.", "Zebrafish were maintained at 28.5 \u00b0C under 14:10 light:dark cycles. All thyroid ablated Mtz treated and control DMSO treated Tgtg:nVenus v2a nfnB fish were kept under TH free conditions and were fed only Artemia rotifers enriched with TH free Algamac Aquafauna and bloodworms.", "cell type:1073 cells from Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB FAC sorted mCherry+ cells from trunks. Fish range in stage from 7.2 10.4 SSL stage zebrafish. Thyroid ablation was performed at 4 dpf with metronidazole treatment.|treatment:Hypothyroid", "GSM3764574", "GSM3764574: Neural crest derived cells from hypothyroid post embryonic zebrafish trunks biological replicate 3; Danio rerio; RNA Seq", "GSM3764574", null, "1", "10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.", null, "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP198298", null, "dangling references:treat as unmapped", "hypo1_possorted_genome_bam.bam", "10X Genomics bam file", 15530826765.0, 272470645.0, "GSM3764574 r1", "0:57", "A:4458931221;C:3243678800;G:3916155957;T:3908839406;N:3221381", 57, null, null, null, 4458931221, 3243678800, 3916155957, 3908839406, 3221381, "SRX5827018", "SRS4754832", "SRA886020", "GEO", "Biology, University of Virginia", 1, 0.94166, null, 0.13327, null, 0.79304, null, 0.49472, null, 57, null, "B", null, "usable mapping rate", "illumina", "nextseq", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2019-05-13", "Larval", "Larval", "Trunk", "Surface Structure"], [52250, "SRR9050625", "SRX5827016", "SRS4754830", "SRP198298", "PRJNA542704", "Thyroid hormone regulates distinct paths to maturation in pigment cell lineages", "GSE131136", "Transcriptome Analysis", "Early and post embryonic neural crest derived lineages in the zebrafish trunk in response to thyroid hormone modulation Overall design: Single cell RNA seq experiments were performed on the 10X Genomics platform from FAC sorted Sox10:CRE positive cells from 5dpf and post embryonic zebrafish trunks with and without xxx hormone.", null, "pubmed:31140974;pubmed:33933422", null, "Neural crest derived cells from hypothyroid juvenile zebrafish trunks biological replicate 1", "GSM3764572", null, "tissue:sox10:Cre+ cells from post embryonic zebrafish trunk tissue|cell type:2135 cells from Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB FAC sorted mCherry+ cells from trunks. Fish range in stage from 11 SSL stage zebrafish. Thyroid ablation was performed at 4 dpf with metronidazole treatment.|treatment:Hypothyroid", "Neural crest derived cells from hypothyroid juvenile zebrafish trunks biological replicate 1", "Expression matrix files and BAM files were generated using cellranger 10X genomics version 2.0.2 as described by the manufacturer using the commands cellranger demux and cellranger count. UMI count matrices representing the filtered set of barcodes representing cells were used as determined by cellranger. All samples were aggregated using the aggregate option in cellranger to normalize mean number of reads per cell across 10X libraries. Genome build: GRCz11 Supplementary files format and content: Expression matrix files and BAM files were generated using cellranger 10X genomics version 2.0.2 as described by the manufacturer using the commands cellranger demux and cellranger count. UMI count matrices representing the filtered set of barcodes representing cells were used as determined by cellranger. Expression matrices are output by cellranger and are in Matrix Market Exchange format and the gene and cell barcode name files that accompany these file are provided as TSV files.", "sox10:Cre+ cells from post embryonic zebrafish trunk tissue", "Transgenic zebrafish Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB were treated either metronidazole 10mM or a vehicle control DMSO at 4dpf. Trunks or skins were collected at a stage range of 7.2 10.4 SSL or 5 dpf as indicated in the sample name. Tissue was dissociated into a single cell suspension and FAC sorted for the presence of mCherry. Then cells were washed and loaded into the 10X chromium chip according to manufacturer recommendations.", "10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.", "Zebrafish were maintained at 28.5 \u00b0C under 14:10 light:dark cycles. All thyroid ablated Mtz treated and control DMSO treated Tgtg:nVenus v2a nfnB fish were kept under TH free conditions and were fed only Artemia rotifers enriched with TH free Algamac Aquafauna and bloodworms.", "cell type:2135 cells from Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB FAC sorted mCherry+ cells from trunks. Fish range in stage from 11 SSL stage zebrafish. Thyroid ablation was performed at 4 dpf with metronidazole treatment.|treatment:Hypothyroid", "GSM3764572", "GSM3764572: Neural crest derived cells from hypothyroid juvenile zebrafish trunks biological replicate 1; Danio rerio; RNA Seq", "GSM3764572", null, "1", "10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.", null, "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP198298", null, "dangling references:treat as unmapped", "hypo7_possorted_genome_bam.bam", "10X Genomics bam file", 5078170983.0, 89090719.0, "GSM3764572 r1", "0:57", "A:1526791201;C:989860604;G:1192544480;T:1366270035;N:2704663", 57, null, null, null, 1526791201, 989860604, 1192544480, 1366270035, 2704663, "SRX5827016", "SRS4754830", "SRA886020", "GEO", "Biology, University of Virginia", 1, 0.92899, null, 0.25348, null, 0.83571, null, 0.48794, null, 57, null, "B", null, "usable mapping rate", "illumina", "nextseq", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2019-05-13", "Multi-stage", "Multi-stage", "Trunk", "Surface Structure"], [52251, "SRR9050624", "SRX5827015", "SRS4754829", "SRP198298", "PRJNA542704", "Thyroid hormone regulates distinct paths to maturation in pigment cell lineages", "GSE131136", "Transcriptome Analysis", "Early and post embryonic neural crest derived lineages in the zebrafish trunk in response to thyroid hormone modulation Overall design: Single cell RNA seq experiments were performed on the 10X Genomics platform from FAC sorted Sox10:CRE positive cells from 5dpf and post embryonic zebrafish trunks with and without xxx hormone.", null, "pubmed:31140974;pubmed:33933422", null, "Neural crest derived cells from euthyroid post embryonic zebrafish trunks biological replicate 6", "GSM3764571", null, "tissue:sox10:Cre+ cells from post embryonic zebrafish trunk tissue|cell type:2384 cells from Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB FAC sorted mCherry+ cells from trunks. Fish range in stage from 7.2 10.4 SSL stage zebrafish|treatment:Euthyroid", "Neural crest derived cells from euthyroid post embryonic zebrafish trunks biological replicate 6", "Expression matrix files and BAM files were generated using cellranger 10X genomics version 2.0.2 as described by the manufacturer using the commands cellranger demux and cellranger count. UMI count matrices representing the filtered set of barcodes representing cells were used as determined by cellranger. All samples were aggregated using the aggregate option in cellranger to normalize mean number of reads per cell across 10X libraries. Genome build: GRCz11 Supplementary files format and content: Expression matrix files and BAM files were generated using cellranger 10X genomics version 2.0.2 as described by the manufacturer using the commands cellranger demux and cellranger count. UMI count matrices representing the filtered set of barcodes representing cells were used as determined by cellranger. Expression matrices are output by cellranger and are in Matrix Market Exchange format and the gene and cell barcode name files that accompany these file are provided as TSV files.", "sox10:Cre+ cells from post embryonic zebrafish trunk tissue", "Transgenic zebrafish Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB were treated either metronidazole 10mM or a vehicle control DMSO at 4dpf. Trunks or skins were collected at a stage range of 7.2 10.4 SSL or 5 dpf as indicated in the sample name. Tissue was dissociated into a single cell suspension and FAC sorted for the presence of mCherry. Then cells were washed and loaded into the 10X chromium chip according to manufacturer recommendations.", "10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.", "Zebrafish were maintained at 28.5 \u00b0C under 14:10 light:dark cycles. All thyroid ablated Mtz treated and control DMSO treated Tgtg:nVenus v2a nfnB fish were kept under TH free conditions and were fed only Artemia rotifers enriched with TH free Algamac Aquafauna and bloodworms.", "cell type:2384 cells from Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB FAC sorted mCherry+ cells from trunks. Fish range in stage from 7.2 10.4 SSL stage zebrafish|treatment:Euthyroid", "GSM3764571", "GSM3764571: Neural crest derived cells from euthyroid post embryonic zebrafish trunks biological replicate 6; Danio rerio; RNA Seq", "GSM3764571", null, "1", "10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.", null, "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP198298", null, "dangling references:treat as unmapped", "eu4_possorted_genome_bam.bam", "10X Genomics bam file", 5411416524.0, 94937132.0, "GSM3764571 r1", "0:57", "A:1638197208;C:1052881199;G:1241396499;T:1476057783;N:2883835", 57, null, null, null, 1638197208, 1052881199, 1241396499, 1476057783, 2883835, "SRX5827015", "SRS4754829", "SRA886020", "GEO", "Biology, University of Virginia", 1, 0.91678, null, 0.23274, null, 0.83435, null, 0.51765, null, 57, null, "B", null, "usable mapping rate", "illumina", "nextseq", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2019-05-13", "Larval", "Larval", "Trunk", "Surface Structure"], [52252, "SRR9050623", "SRX5827014", "SRS4754828", "SRP198298", "PRJNA542704", "Thyroid hormone regulates distinct paths to maturation in pigment cell lineages", "GSE131136", "Transcriptome Analysis", "Early and post embryonic neural crest derived lineages in the zebrafish trunk in response to thyroid hormone modulation Overall design: Single cell RNA seq experiments were performed on the 10X Genomics platform from FAC sorted Sox10:CRE positive cells from 5dpf and post embryonic zebrafish trunks with and without xxx hormone.", null, "pubmed:31140974;pubmed:33933422", null, "Neural crest derived cells from euthyroid post embryonic zebrafish trunks biological replicate 5", "GSM3764570", null, "tissue:sox10:Cre+ cells from post embryonic zebrafish trunk tissue|cell type:807 cells from Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB FAC sorted mCherry+ cells from trunks. Fish range in stage from 7.2 10.4 SSL stage zebrafish|treatment:Euthyroid", "Neural crest derived cells from euthyroid post embryonic zebrafish trunks biological replicate 5", "Expression matrix files and BAM files were generated using cellranger 10X genomics version 2.0.2 as described by the manufacturer using the commands cellranger demux and cellranger count. UMI count matrices representing the filtered set of barcodes representing cells were used as determined by cellranger. All samples were aggregated using the aggregate option in cellranger to normalize mean number of reads per cell across 10X libraries. Genome build: GRCz11 Supplementary files format and content: Expression matrix files and BAM files were generated using cellranger 10X genomics version 2.0.2 as described by the manufacturer using the commands cellranger demux and cellranger count. UMI count matrices representing the filtered set of barcodes representing cells were used as determined by cellranger. Expression matrices are output by cellranger and are in Matrix Market Exchange format and the gene and cell barcode name files that accompany these file are provided as TSV files.", "sox10:Cre+ cells from post embryonic zebrafish trunk tissue", "Transgenic zebrafish Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB were treated either metronidazole 10mM or a vehicle control DMSO at 4dpf. Trunks or skins were collected at a stage range of 7.2 10.4 SSL or 5 dpf as indicated in the sample name. Tissue was dissociated into a single cell suspension and FAC sorted for the presence of mCherry. Then cells were washed and loaded into the 10X chromium chip according to manufacturer recommendations.", "10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.", "Zebrafish were maintained at 28.5 \u00b0C under 14:10 light:dark cycles. All thyroid ablated Mtz treated and control DMSO treated Tgtg:nVenus v2a nfnB fish were kept under TH free conditions and were fed only Artemia rotifers enriched with TH free Algamac Aquafauna and bloodworms.", "cell type:807 cells from Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB FAC sorted mCherry+ cells from trunks. Fish range in stage from 7.2 10.4 SSL stage zebrafish|treatment:Euthyroid", "GSM3764570", "GSM3764570: Neural crest derived cells from euthyroid post embryonic zebrafish trunks biological replicate 5; Danio rerio; RNA Seq", "GSM3764570", null, "1", "10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.", null, "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP198298", null, "dangling references:treat as unmapped", "eu3_possorted_genome_bam.bam", "10X Genomics bam file", 8326974105.0, 146087265.0, "GSM3764570 r1", "0:57", "A:2330538697;C:1602893033;G:2265568086;T:2124697512;N:3276777", 57, null, null, null, 2330538697, 1602893033, 2265568086, 2124697512, 3276777, "SRX5827014", "SRS4754828", "SRA886020", "GEO", "Biology, University of Virginia", 1, 0.91032, null, 0.14841, null, 0.81207, null, 0.52798, null, 57, null, "B", null, "usable mapping rate", "illumina", "nextseq", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2019-05-13", "Larval", "Larval", "Trunk", "Surface Structure"], [52253, "SRR9050622", "SRX5827013", "SRS4754827", "SRP198298", "PRJNA542704", "Thyroid hormone regulates distinct paths to maturation in pigment cell lineages", "GSE131136", "Transcriptome Analysis", "Early and post embryonic neural crest derived lineages in the zebrafish trunk in response to thyroid hormone modulation Overall design: Single cell RNA seq experiments were performed on the 10X Genomics platform from FAC sorted Sox10:CRE positive cells from 5dpf and post embryonic zebrafish trunks with and without xxx hormone.", null, "pubmed:31140974;pubmed:33933422", null, "Neural crest derived cells from euthyroid post embryonic zebrafish trunks biological replicate 4", "GSM3764569", null, "tissue:sox10:Cre+ cells from post embryonic zebrafish trunk tissue|cell type:808 cells from Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB FAC sorted mCherry+ cells from trunks. Fish range in stage from 7.2 10.4 SSL stage zebrafish|treatment:Euthyroid", "Neural crest derived cells from euthyroid post embryonic zebrafish trunks biological replicate 4", "Expression matrix files and BAM files were generated using cellranger 10X genomics version 2.0.2 as described by the manufacturer using the commands cellranger demux and cellranger count. UMI count matrices representing the filtered set of barcodes representing cells were used as determined by cellranger. All samples were aggregated using the aggregate option in cellranger to normalize mean number of reads per cell across 10X libraries. Genome build: GRCz11 Supplementary files format and content: Expression matrix files and BAM files were generated using cellranger 10X genomics version 2.0.2 as described by the manufacturer using the commands cellranger demux and cellranger count. UMI count matrices representing the filtered set of barcodes representing cells were used as determined by cellranger. Expression matrices are output by cellranger and are in Matrix Market Exchange format and the gene and cell barcode name files that accompany these file are provided as TSV files.", "sox10:Cre+ cells from post embryonic zebrafish trunk tissue", "Transgenic zebrafish Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB were treated either metronidazole 10mM or a vehicle control DMSO at 4dpf. Trunks or skins were collected at a stage range of 7.2 10.4 SSL or 5 dpf as indicated in the sample name. Tissue was dissociated into a single cell suspension and FAC sorted for the presence of mCherry. Then cells were washed and loaded into the 10X chromium chip according to manufacturer recommendations.", "10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.", "Zebrafish were maintained at 28.5 \u00b0C under 14:10 light:dark cycles. All thyroid ablated Mtz treated and control DMSO treated Tgtg:nVenus v2a nfnB fish were kept under TH free conditions and were fed only Artemia rotifers enriched with TH free Algamac Aquafauna and bloodworms.", "cell type:808 cells from Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB FAC sorted mCherry+ cells from trunks. Fish range in stage from 7.2 10.4 SSL stage zebrafish|treatment:Euthyroid", "GSM3764569", "GSM3764569: Neural crest derived cells from euthyroid post embryonic zebrafish trunks biological replicate 4; Danio rerio; RNA Seq", "GSM3764569", null, "1", "10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.", null, "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP198298", null, "dangling references:treat as unmapped", "eu2_possorted_genome_bam.bam", "10X Genomics bam file", 9524985741.0, 167105013.0, "GSM3764569 r1", "0:57", "A:2659154932;C:1836434156;G:2596847773;T:2428811653;N:3737227", 57, null, null, null, 2659154932, 1836434156, 2596847773, 2428811653, 3737227, "SRX5827013", "SRS4754827", "SRA886020", "GEO", "Biology, University of Virginia", 1, 0.91042, null, 0.14492, null, 0.81148, null, 0.53287, null, 57, null, "B", null, "usable mapping rate", "illumina", "nextseq", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2019-05-13", "Larval", "Larval", "Trunk", "Surface Structure"], [52254, "SRR9050621", "SRX5827012", "SRS4754826", "SRP198298", "PRJNA542704", "Thyroid hormone regulates distinct paths to maturation in pigment cell lineages", "GSE131136", "Transcriptome Analysis", "Early and post embryonic neural crest derived lineages in the zebrafish trunk in response to thyroid hormone modulation Overall design: Single cell RNA seq experiments were performed on the 10X Genomics platform from FAC sorted Sox10:CRE positive cells from 5dpf and post embryonic zebrafish trunks with and without xxx hormone.", null, "pubmed:31140974;pubmed:33933422", null, "Neural crest derived cells from euthyroid post embryonic zebrafish trunks biological replicate 3", "GSM3764568", null, "tissue:sox10:Cre+ cells from post embryonic zebrafish trunk tissue|cell type:944 cells from Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB FAC sorted mCherry+ cells from trunks. Fish range in stage from 7.2 10.4 SSL stage zebrafish|treatment:Euthyroid", "Neural crest derived cells from euthyroid post embryonic zebrafish trunks biological replicate 3", "Expression matrix files and BAM files were generated using cellranger 10X genomics version 2.0.2 as described by the manufacturer using the commands cellranger demux and cellranger count. UMI count matrices representing the filtered set of barcodes representing cells were used as determined by cellranger. All samples were aggregated using the aggregate option in cellranger to normalize mean number of reads per cell across 10X libraries. Genome build: GRCz11 Supplementary files format and content: Expression matrix files and BAM files were generated using cellranger 10X genomics version 2.0.2 as described by the manufacturer using the commands cellranger demux and cellranger count. UMI count matrices representing the filtered set of barcodes representing cells were used as determined by cellranger. Expression matrices are output by cellranger and are in Matrix Market Exchange format and the gene and cell barcode name files that accompany these file are provided as TSV files.", "sox10:Cre+ cells from post embryonic zebrafish trunk tissue", "Transgenic zebrafish Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB were treated either metronidazole 10mM or a vehicle control DMSO at 4dpf. Trunks or skins were collected at a stage range of 7.2 10.4 SSL or 5 dpf as indicated in the sample name. Tissue was dissociated into a single cell suspension and FAC sorted for the presence of mCherry. Then cells were washed and loaded into the 10X chromium chip according to manufacturer recommendations.", "10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.", "Zebrafish were maintained at 28.5 \u00b0C under 14:10 light:dark cycles. All thyroid ablated Mtz treated and control DMSO treated Tgtg:nVenus v2a nfnB fish were kept under TH free conditions and were fed only Artemia rotifers enriched with TH free Algamac Aquafauna and bloodworms.", "cell type:944 cells from Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB FAC sorted mCherry+ cells from trunks. Fish range in stage from 7.2 10.4 SSL stage zebrafish|treatment:Euthyroid", "GSM3764568", "GSM3764568: Neural crest derived cells from euthyroid post embryonic zebrafish trunks biological replicate 3; Danio rerio; RNA Seq", "GSM3764568", null, "1", "10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.", null, "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP198298", null, "dangling references:treat as unmapped", "eu1_possorted_genome_bam.bam", "10X Genomics bam file", 14548569306.0, 255238058.0, "GSM3764568 r1", "0:57", "A:4144426475;C:3024945467;G:3685756189;T:3690427238;N:3013937", 57, null, null, null, 4144426475, 3024945467, 3685756189, 3690427238, 3013937, "SRX5827012", "SRS4754826", "SRA886020", "GEO", "Biology, University of Virginia", 1, 0.94033, null, 0.12393, null, 0.79338, null, 0.50069, null, 57, null, "B", null, "usable mapping rate", "illumina", "nextseq", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2019-05-13", "Larval", "Larval", "Trunk", "Surface Structure"], [52256, "SRR9050619", "SRX5827010", "SRS4754824", "SRP198298", "PRJNA542704", "Thyroid hormone regulates distinct paths to maturation in pigment cell lineages", "GSE131136", "Transcriptome Analysis", "Early and post embryonic neural crest derived lineages in the zebrafish trunk in response to thyroid hormone modulation Overall design: Single cell RNA seq experiments were performed on the 10X Genomics platform from FAC sorted Sox10:CRE positive cells from 5dpf and post embryonic zebrafish trunks with and without xxx hormone.", null, "pubmed:31140974;pubmed:33933422", null, "Neural crest derived cells from euthyroid post embryonic zebrafish trunks biological replicate 1", "GSM3764566", null, "tissue:sox10:Cre+ cells from post embryonic zebrafish trunk tissue|cell type:2168 cells from Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB FAC sorted mCherry+ cells from trunks. Zebrafish were stage 11 SSL stage juvenile.|treatment:Euthyroid", "Neural crest derived cells from euthyroid post embryonic zebrafish trunks biological replicate 1", "Expression matrix files and BAM files were generated using cellranger 10X genomics version 2.0.2 as described by the manufacturer using the commands cellranger demux and cellranger count. UMI count matrices representing the filtered set of barcodes representing cells were used as determined by cellranger. All samples were aggregated using the aggregate option in cellranger to normalize mean number of reads per cell across 10X libraries. Genome build: GRCz11 Supplementary files format and content: Expression matrix files and BAM files were generated using cellranger 10X genomics version 2.0.2 as described by the manufacturer using the commands cellranger demux and cellranger count. UMI count matrices representing the filtered set of barcodes representing cells were used as determined by cellranger. Expression matrices are output by cellranger and are in Matrix Market Exchange format and the gene and cell barcode name files that accompany these file are provided as TSV files.", "sox10:Cre+ cells from post embryonic zebrafish trunk tissue", "Transgenic zebrafish Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB were treated either metronidazole 10mM or a vehicle control DMSO at 4dpf. Trunks or skins were collected at a stage range of 7.2 10.4 SSL or 5 dpf as indicated in the sample name. Tissue was dissociated into a single cell suspension and FAC sorted for the presence of mCherry. Then cells were washed and loaded into the 10X chromium chip according to manufacturer recommendations.", "10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.", "Zebrafish were maintained at 28.5 \u00b0C under 14:10 light:dark cycles. All thyroid ablated Mtz treated and control DMSO treated Tgtg:nVenus v2a nfnB fish were kept under TH free conditions and were fed only Artemia rotifers enriched with TH free Algamac Aquafauna and bloodworms.", "cell type:2168 cells from Tgsox10:Cre; ubi:switch; tg:nVenus 2a nfnB FAC sorted mCherry+ cells from trunks. Zebrafish were stage 11 SSL stage juvenile.|treatment:Euthyroid", "GSM3764566", "GSM3764566: Neural crest derived cells from euthyroid post embryonic zebrafish trunks biological replicate 1; Danio rerio; RNA Seq", "GSM3764566", null, "1", "10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.", null, "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP198298", null, "dangling references:treat as unmapped", "eu6_possorted_genome_bam.bam", "10X Genomics bam file", 5005233954.0, 87811122.0, "GSM3764566 r1", "0:57", "A:1531421605;C:966957285;G:1151579626;T:1352667292;N:2608146", 57, null, null, null, 1531421605, 966957285, 1151579626, 1352667292, 2608146, "SRX5827010", "SRS4754824", "SRA886020", "GEO", "Biology, University of Virginia", 1, 0.92288, null, 0.25231, null, 0.83479, null, 0.5014, null, 57, null, "B", null, "usable mapping rate", "illumina", "nextseq", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2019-05-13", "Multi-stage", "Multi-stage", "Trunk", "Surface Structure"], [59887, "SRR12067711", "SRX8595501", "SRS6886082", "SRP268312", "PRJNA641114", "Single cell transcriptomic analysis 30 hpf Zebrafish trunks", "GSE152982", "Other", "Here we performed single cell RNAseq analysis of whole wildtype zebrafish trunks at 30hpf using 10x Genomics' Chromium platform. 22 distinct cell populations were identified spanning all three embryonic germ layers. Overall design: Whole trunks excised from 30 embryos at 30 hpf were dissociated using a cold protease dissociation protocol. Barcoding of cells and and cDNA library construction was carried out using 10X Genomics' Chromium platform.", null, "pubmed:34234366", null, "Zf 30h trunk", "GSM4631066", null, "source name:Zebrafish Trunks|age:30 hpf|tissue:trunk|genotype:wildtype", "Zf 30h trunk", "All processing was performed in 10X Genomics CellRanger v3.0.2 using default parameters Raw basecall files were assembled into fastq files using 'mkfastq' function The 'count' function was used to align Fastq files to zebrafish genome v.11 and to obtain the gene expression matrices Genome build: GRCz11 Supplementary files format and content: mtx matrix files", "Zebrafish Trunks", null, "Whole wildtype zebrafish trunks at 30 hpf were dissociated into a single cell suspension using a cold protease treatment.Single cell suspensions were processed through the Chromium platform 10X Genomics to generate single cell cDNA libraries cDNA was amplified by PCR and the three prime end of the cDNA prepared for sequencing using a modified Nextera XT protocol", null, "age:30 hpf|tissue:trunk|genotype:wildtype", "GSM4631066", "GSM4631066: Zf 30h trunk; Danio rerio; RNA Seq", "GSM4631066", null, "1", "Whole wildtype zebrafish trunks at 30 hpf were dissociated into a single cell suspension using a cold protease treatment.Single cell suspensions were processed through the Chromium platform 10X Genomics to generate single cell cDNA libraries cDNA was amplified by PCR and the three prime end of the cDNA prepared for sequencing using a modified Nextera XT protocol", "GEO Accession:GSM4631066", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina HiSeq 2500", null, "SRP268312", null, "loader:fastq load.py|options: platform=Illumina readTypes=TTB read1PairFiles=Zf30hTrunk S1 L001 I1 001.fastq.gz read2PairFiles=Zf30hTrunk S1 L001 R1 001.fastq.gz read3PairFiles=Zf30hTrunk S1 L001 R2 001.fastq.gz", "Zf30hTrunk_S1_L001_I1_001.fastq.gz Zf30hTrunk_S1_L001_R1_001.fastq.gz Zf30hTrunk_S1_L001_R2_001.fastq.gz", "fastq fastq fastq", 30568523622.0, 167958921.0, "GSM4631066 r1", "0:8 1:27 2:147", "A:8739694698;C:6736998816;G:6903125001;T:8168427703;N:20277404", 8, 27, 147, null, 8739694698, 6736998816, 6903125001, 8168427703, 20277404, "SRX8595501", "SRS6886082", "SRA1089692", "GEO", "University of South Florida", 1, 0.88066, null, 0.09296, null, 0.8506, null, 0.50586, null, 147, null, "B", null, "usable mapping rate", "illumina", "hiseq_era", "3prime", "cdna_unspecified", "nextera", "sc", "single_cell_droplet", "10x", null, "United States", "2020-06-22", "Pharyngula", "Embryo", "Trunk", "Surface Structure"], [59888, "SRR12067712", "SRX8595501", "SRS6886082", "SRP268312", "PRJNA641114", "Single cell transcriptomic analysis 30 hpf Zebrafish trunks", "GSE152982", "Other", "Here we performed single cell RNAseq analysis of whole wildtype zebrafish trunks at 30hpf using 10x Genomics' Chromium platform. 22 distinct cell populations were identified spanning all three embryonic germ layers. Overall design: Whole trunks excised from 30 embryos at 30 hpf were dissociated using a cold protease dissociation protocol. Barcoding of cells and and cDNA library construction was carried out using 10X Genomics' Chromium platform.", null, "pubmed:34234366", null, "Zf 30h trunk", "GSM4631066", null, "source name:Zebrafish Trunks|age:30 hpf|tissue:trunk|genotype:wildtype", "Zf 30h trunk", "All processing was performed in 10X Genomics CellRanger v3.0.2 using default parameters Raw basecall files were assembled into fastq files using 'mkfastq' function The 'count' function was used to align Fastq files to zebrafish genome v.11 and to obtain the gene expression matrices Genome build: GRCz11 Supplementary files format and content: mtx matrix files", "Zebrafish Trunks", null, "Whole wildtype zebrafish trunks at 30 hpf were dissociated into a single cell suspension using a cold protease treatment.Single cell suspensions were processed through the Chromium platform 10X Genomics to generate single cell cDNA libraries cDNA was amplified by PCR and the three prime end of the cDNA prepared for sequencing using a modified Nextera XT protocol", null, "age:30 hpf|tissue:trunk|genotype:wildtype", "GSM4631066", "GSM4631066: Zf 30h trunk; Danio rerio; RNA Seq", "GSM4631066", null, "1", "Whole wildtype zebrafish trunks at 30 hpf were dissociated into a single cell suspension using a cold protease treatment.Single cell suspensions were processed through the Chromium platform 10X Genomics to generate single cell cDNA libraries cDNA was amplified by PCR and the three prime end of the cDNA prepared for sequencing using a modified Nextera XT protocol", "GEO Accession:GSM4631066", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina HiSeq 2500", null, "SRP268312", null, "loader:fastq load.py|options: platform=Illumina readTypes=TTB read1PairFiles=Zf30hTrunk S1 L002 I1 001.fastq.gz read2PairFiles=Zf30hTrunk S1 L002 R1 001.fastq.gz read3PairFiles=Zf30hTrunk S1 L002 R2 001.fastq.gz", "Zf30hTrunk_S1_L002_I1_001.fastq.gz Zf30hTrunk_S1_L002_R1_001.fastq.gz Zf30hTrunk_S1_L002_R2_001.fastq.gz", "fastq fastq fastq", 31428372976.0, 172683368.0, "GSM4631066 r2", "0:8 1:27 2:147", "A:8978925123;C:6926043302;G:7091713953;T:8399543364;N:32147234", 8, 27, 147, null, 8978925123, 6926043302, 7091713953, 8399543364, 32147234, "SRX8595501", "SRS6886082", "SRA1089692", "GEO", "University of South Florida", 1, 0.87666, null, 0.09235, null, 0.85277, null, 0.49776, null, 147, null, "B", null, "usable mapping rate", "illumina", "hiseq_era", "3prime", "cdna_unspecified", "nextera", "sc", "single_cell_droplet", "10x", null, "United States", "2020-06-22", "Pharyngula", "Embryo", "Trunk", "Surface Structure"], [65124, "SRR14935604", "SRX11248236", "SRS9294118", "SRP325962", "PRJNA742206", "Heterogeneity and molecular programming of progenitors for motor neurons and oligodendrocytes", "GSE179096", "Other", "The pMN domain is a restricted domain in the ventral spinal cords defined by the expression of olig2 gene. The fate determination of pMN progenitors is highly temporally and spatially regulated with motor neurons and oligodendrocyte progenitor cells OPCs developing sequentially. Insight into the heterogeneity and molecular programs of pMN progenitors is currently lacking. With the zebrafish model we identified multiple states of neural progenitors using single cell sequencing: proliferating progenitors common progenitors for both motor neurons and OPCs and restricted precursors for either motor neurons or OPCs. We found specific molecular programs for neural progenitor fate transition and manipulations of representative genes in the motor neuron or OPC lineage confirmed their critical role in cell fate determination. Deciphering progenitor heterogeneity and molecular mechanisms for these transitions will elucidate the formation of complex neuron glia networks in the central nervous system during development and understand the basis of neurodevelopmental disorders. Overall design: olig2+ cells were isolated from the trunks of Tgolig2:dsred by FACS and underwent scRNA seq", null, "pubmed:36063998", null, "olig2+ cells in zebrafish trunks", "GSM5406686", null, "source name:Tgolig2:dsred trunks|developmental stage:42 hpf|genotype:Tg olig2:dsred|tissue:trunk|cell type:fluorescent cells from Tgolig2:dsred trunks", "olig2+ cells in zebrafish trunks", "Alignment filtering barcode counting and UMI counting were performed with cellranger count module to generate feature barcode matrix and determine clusters. Genes detectable in more than two cells were defined as \u201cexpressed\u201d. Cells with <1000 genes detected were removed. Counts were normalized to 10000 and transformed into logarithmic scales. A neighborhood graph was embedded using UMAP displaying the top 4000 highly variable genes across cells. Cells were clustered by the Louvain Algorithm. The trajectory interface of all cell clusters was done using the layout 'fa'. These analyses were performed by the Python based SCANPY package Genome build: GRCz11 Supplementary files format and content: Matrix table with raw gene counts for every gene and every sample", "Tgolig2:dsred trunks", null, "Tgolig2:dsred trunks were dissected and dissociated with 0.25% trypsin. Fluorescent cells were isolated with FACS. RNA was extracted with Trizol. cDNAs were amplified and libraries were generated with the Single Cell 3\u2019 Library and Gel Bead kit V3", null, "developmental stage:42 hpf|genotype:Tg olig2:dsred|tissue:trunk|cell type:fluorescent cells from Tgolig2:dsred trunks", "GSM5406686", "GSM5406686: olig2+ cells in zebrafish trunks; Danio rerio; RNA Seq", "GSM5406686", null, "1", "Tgolig2:dsred trunks were dissected and dissociated with 0.25% trypsin. Fluorescent cells were isolated with FACS. RNA was extracted with Trizol. cDNAs were amplified and libraries were generated with the Single Cell three prime Library and Gel Bead kit V3", "GEO Accession:GSM5406686", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP325962", null, null, "191269A_Z_Olig2_1_1_R1.fq.gz 191269A_Z_Olig2_1_1_R2.fq.gz", "fastq fastq", 31400412000.0, 104668040.0, "GSM5406686 r1", "0:150 1:150", "A:6848745621;C:5731974961;G:10959380121;T:7859959179;N:352118", 150, 150, null, null, 6848745621, 5731974961, 10959380121, 7859959179, 352118, "SRX11248236", "SRS9294118", "SRA1251944", "GEO", "Nantong University", 2, 0.0, 0.89636, 0.0, 0.20375, 1.0, 0.78575, null, 0.50155, 150, 150, "T", "B", "mate1 technical by mapping diff", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "China", "2021-06-29", "Pharyngula", "Embryo", "Trunk", "Surface Structure"], [65125, "SRR14935605", "SRX11248236", "SRS9294118", "SRP325962", "PRJNA742206", "Heterogeneity and molecular programming of progenitors for motor neurons and oligodendrocytes", "GSE179096", "Other", "The pMN domain is a restricted domain in the ventral spinal cords defined by the expression of olig2 gene. The fate determination of pMN progenitors is highly temporally and spatially regulated with motor neurons and oligodendrocyte progenitor cells OPCs developing sequentially. Insight into the heterogeneity and molecular programs of pMN progenitors is currently lacking. With the zebrafish model we identified multiple states of neural progenitors using single cell sequencing: proliferating progenitors common progenitors for both motor neurons and OPCs and restricted precursors for either motor neurons or OPCs. We found specific molecular programs for neural progenitor fate transition and manipulations of representative genes in the motor neuron or OPC lineage confirmed their critical role in cell fate determination. Deciphering progenitor heterogeneity and molecular mechanisms for these transitions will elucidate the formation of complex neuron glia networks in the central nervous system during development and understand the basis of neurodevelopmental disorders. Overall design: olig2+ cells were isolated from the trunks of Tgolig2:dsred by FACS and underwent scRNA seq", null, "pubmed:36063998", null, "olig2+ cells in zebrafish trunks", "GSM5406686", null, "source name:Tgolig2:dsred trunks|developmental stage:42 hpf|genotype:Tg olig2:dsred|tissue:trunk|cell type:fluorescent cells from Tgolig2:dsred trunks", "olig2+ cells in zebrafish trunks", "Alignment filtering barcode counting and UMI counting were performed with cellranger count module to generate feature barcode matrix and determine clusters. Genes detectable in more than two cells were defined as \u201cexpressed\u201d. Cells with <1000 genes detected were removed. Counts were normalized to 10000 and transformed into logarithmic scales. A neighborhood graph was embedded using UMAP displaying the top 4000 highly variable genes across cells. Cells were clustered by the Louvain Algorithm. The trajectory interface of all cell clusters was done using the layout 'fa'. These analyses were performed by the Python based SCANPY package Genome build: GRCz11 Supplementary files format and content: Matrix table with raw gene counts for every gene and every sample", "Tgolig2:dsred trunks", null, "Tgolig2:dsred trunks were dissected and dissociated with 0.25% trypsin. Fluorescent cells were isolated with FACS. RNA was extracted with Trizol. cDNAs were amplified and libraries were generated with the Single Cell 3\u2019 Library and Gel Bead kit V3", null, "developmental stage:42 hpf|genotype:Tg olig2:dsred|tissue:trunk|cell type:fluorescent cells from Tgolig2:dsred trunks", "GSM5406686", "GSM5406686: olig2+ cells in zebrafish trunks; Danio rerio; RNA Seq", "GSM5406686", null, "1", "Tgolig2:dsred trunks were dissected and dissociated with 0.25% trypsin. Fluorescent cells were isolated with FACS. RNA was extracted with Trizol. cDNAs were amplified and libraries were generated with the Single Cell three prime Library and Gel Bead kit V3", "GEO Accession:GSM5406686", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP325962", null, null, "191269A_Z_Olig2_2_1_R1.fq.gz 191269A_Z_Olig2_2_1_R2.fq.gz", "fastq fastq", 24958600500.0, 83195335.0, "GSM5406686 r2", "0:150 1:150", "A:5431710090;C:4568888734;G:8717963207;T:6239757593;N:280876", 150, 150, null, null, 5431710090, 4568888734, 8717963207, 6239757593, 280876, "SRX11248236", "SRS9294118", "SRA1251944", "GEO", "Nantong University", 2, 0.0, 0.89635, 0.0, 0.20299, 1.0, 0.78453, null, 0.50241, 150, 150, "T", "B", "mate1 technical by mapping diff", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "China", "2021-06-29", "Pharyngula", "Embryo", "Trunk", "Surface Structure"], [65126, "SRR14935606", "SRX11248236", "SRS9294118", "SRP325962", "PRJNA742206", "Heterogeneity and molecular programming of progenitors for motor neurons and oligodendrocytes", "GSE179096", "Other", "The pMN domain is a restricted domain in the ventral spinal cords defined by the expression of olig2 gene. The fate determination of pMN progenitors is highly temporally and spatially regulated with motor neurons and oligodendrocyte progenitor cells OPCs developing sequentially. Insight into the heterogeneity and molecular programs of pMN progenitors is currently lacking. With the zebrafish model we identified multiple states of neural progenitors using single cell sequencing: proliferating progenitors common progenitors for both motor neurons and OPCs and restricted precursors for either motor neurons or OPCs. We found specific molecular programs for neural progenitor fate transition and manipulations of representative genes in the motor neuron or OPC lineage confirmed their critical role in cell fate determination. Deciphering progenitor heterogeneity and molecular mechanisms for these transitions will elucidate the formation of complex neuron glia networks in the central nervous system during development and understand the basis of neurodevelopmental disorders. Overall design: olig2+ cells were isolated from the trunks of Tgolig2:dsred by FACS and underwent scRNA seq", null, "pubmed:36063998", null, "olig2+ cells in zebrafish trunks", "GSM5406686", null, "source name:Tgolig2:dsred trunks|developmental stage:42 hpf|genotype:Tg olig2:dsred|tissue:trunk|cell type:fluorescent cells from Tgolig2:dsred trunks", "olig2+ cells in zebrafish trunks", "Alignment filtering barcode counting and UMI counting were performed with cellranger count module to generate feature barcode matrix and determine clusters. Genes detectable in more than two cells were defined as \u201cexpressed\u201d. Cells with <1000 genes detected were removed. Counts were normalized to 10000 and transformed into logarithmic scales. A neighborhood graph was embedded using UMAP displaying the top 4000 highly variable genes across cells. Cells were clustered by the Louvain Algorithm. The trajectory interface of all cell clusters was done using the layout 'fa'. These analyses were performed by the Python based SCANPY package Genome build: GRCz11 Supplementary files format and content: Matrix table with raw gene counts for every gene and every sample", "Tgolig2:dsred trunks", null, "Tgolig2:dsred trunks were dissected and dissociated with 0.25% trypsin. Fluorescent cells were isolated with FACS. RNA was extracted with Trizol. cDNAs were amplified and libraries were generated with the Single Cell 3\u2019 Library and Gel Bead kit V3", null, "developmental stage:42 hpf|genotype:Tg olig2:dsred|tissue:trunk|cell type:fluorescent cells from Tgolig2:dsred trunks", "GSM5406686", "GSM5406686: olig2+ cells in zebrafish trunks; Danio rerio; RNA Seq", "GSM5406686", null, "1", "Tgolig2:dsred trunks were dissected and dissociated with 0.25% trypsin. Fluorescent cells were isolated with FACS. RNA was extracted with Trizol. cDNAs were amplified and libraries were generated with the Single Cell three prime Library and Gel Bead kit V3", "GEO Accession:GSM5406686", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP325962", null, null, "191269A_Z_Olig2_3_1_R1.fq.gz 191269A_Z_Olig2_3_1_R2.fq.gz", "fastq fastq", 20693368500.0, 68977895.0, "GSM5406686 r3", "0:150 1:150", "A:4513259900;C:3774781009;G:7221748955;T:5183345869;N:232767", 150, 150, null, null, 4513259900, 3774781009, 7221748955, 5183345869, 232767, "SRX11248236", "SRS9294118", "SRA1251944", "GEO", "Nantong University", 2, 0.0, 0.89637, 0.0, 0.20432, 1.0, 0.78439, null, 0.4973, 150, 150, "T", "B", "mate1 technical by mapping diff", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "China", "2021-06-29", "Pharyngula", "Embryo", "Trunk", "Surface Structure"], [65127, "SRR14935607", "SRX11248236", "SRS9294118", "SRP325962", "PRJNA742206", "Heterogeneity and molecular programming of progenitors for motor neurons and oligodendrocytes", "GSE179096", "Other", "The pMN domain is a restricted domain in the ventral spinal cords defined by the expression of olig2 gene. The fate determination of pMN progenitors is highly temporally and spatially regulated with motor neurons and oligodendrocyte progenitor cells OPCs developing sequentially. Insight into the heterogeneity and molecular programs of pMN progenitors is currently lacking. With the zebrafish model we identified multiple states of neural progenitors using single cell sequencing: proliferating progenitors common progenitors for both motor neurons and OPCs and restricted precursors for either motor neurons or OPCs. We found specific molecular programs for neural progenitor fate transition and manipulations of representative genes in the motor neuron or OPC lineage confirmed their critical role in cell fate determination. Deciphering progenitor heterogeneity and molecular mechanisms for these transitions will elucidate the formation of complex neuron glia networks in the central nervous system during development and understand the basis of neurodevelopmental disorders. Overall design: olig2+ cells were isolated from the trunks of Tgolig2:dsred by FACS and underwent scRNA seq", null, "pubmed:36063998", null, "olig2+ cells in zebrafish trunks", "GSM5406686", null, "source name:Tgolig2:dsred trunks|developmental stage:42 hpf|genotype:Tg olig2:dsred|tissue:trunk|cell type:fluorescent cells from Tgolig2:dsred trunks", "olig2+ cells in zebrafish trunks", "Alignment filtering barcode counting and UMI counting were performed with cellranger count module to generate feature barcode matrix and determine clusters. Genes detectable in more than two cells were defined as \u201cexpressed\u201d. Cells with <1000 genes detected were removed. Counts were normalized to 10000 and transformed into logarithmic scales. A neighborhood graph was embedded using UMAP displaying the top 4000 highly variable genes across cells. Cells were clustered by the Louvain Algorithm. The trajectory interface of all cell clusters was done using the layout 'fa'. These analyses were performed by the Python based SCANPY package Genome build: GRCz11 Supplementary files format and content: Matrix table with raw gene counts for every gene and every sample", "Tgolig2:dsred trunks", null, "Tgolig2:dsred trunks were dissected and dissociated with 0.25% trypsin. Fluorescent cells were isolated with FACS. RNA was extracted with Trizol. cDNAs were amplified and libraries were generated with the Single Cell 3\u2019 Library and Gel Bead kit V3", null, "developmental stage:42 hpf|genotype:Tg olig2:dsred|tissue:trunk|cell type:fluorescent cells from Tgolig2:dsred trunks", "GSM5406686", "GSM5406686: olig2+ cells in zebrafish trunks; Danio rerio; RNA Seq", "GSM5406686", null, "1", "Tgolig2:dsred trunks were dissected and dissociated with 0.25% trypsin. Fluorescent cells were isolated with FACS. RNA was extracted with Trizol. cDNAs were amplified and libraries were generated with the Single Cell three prime Library and Gel Bead kit V3", "GEO Accession:GSM5406686", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP325962", null, null, "191269A_Z_Olig2_4_1_R1.fq.gz 191269A_Z_Olig2_4_1_R2.fq.gz", "fastq fastq", 22347557700.0, 74491859.0, "GSM5406686 r4", "0:150 1:150", "A:4874539429;C:4084280591;G:7793747016;T:5594741104;N:249560", 150, 150, null, null, 4874539429, 4084280591, 7793747016, 5594741104, 249560, "SRX11248236", "SRS9294118", "SRA1251944", "GEO", "Nantong University", 2, 0.0, 0.89737, 0.0, 0.20476, 1.0, 0.78675, null, 0.5017, 150, 150, "T", "B", "mate1 technical by mapping diff", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "China", "2021-06-29", "Pharyngula", "Embryo", "Trunk", "Surface Structure"], [65593, "SRR15390207", "SRX11692437", "SRS9724034", "SRP331755", "PRJNA753151", "scRNA seq of fin and body zebrafish melanocytes", "GSE181748", "Transcriptome Analysis", "Oncogenic alterations to DNA are not transforming in all cellular contexts. This may be due to pre existing transcriptional programs in the cell of origin. Here we define anatomic position as a major determinant of why cells respond to specific oncogenes. Cutaneous melanoma arises throughout the body whereas the acral subtype arises on the palms of the hands soles of the feet or under the nails3. We sequenced the DNA of cutaneous and acral melanomas from a large cohort of human patients and found a specific enrichment for BRAF mutations in cutaneous melanoma but CRKL amplifications in acral melanoma. We modeled these changes in transgenic zebrafish models and found that CRKL driven tumors predominantly formed in the fins of the fish. The fins are the evolutionary precursors to tetrapod limbs indicating that melanocytes in these acral locations may be uniquely susceptible to CRKL. RNA profiling of these fin/limb melanocytes compared to body melanocytes revealed a positional identity gene program typified by posterior HOX13 genes. This positional gene program synergized with CRKL to drive tumors at acral sites. Abrogation of this CRKL driven program eliminated the anatomic specificity of acral melanoma. These data suggest that the anatomic position of the cell of origin endows it with a unique transcriptional state that makes it susceptible to only certain oncogenic insults. Overall design: For this experiment we used our zebrafish transgenic model of Acral melanoma which was generated by injecting Casper fish with MniCoopR GFP mitfa:hsCRKL mitfa:hsGAB2 mitfa:hsTERT mitfa:Cas9 mCherry;U6nf1a gRNA mitfa:Cas9 mCherry;U6 nf1b gRNA. Fish were dissected to collect body skin and fins digested using liberase and then FACS sorted for GFP+ melanocytes and GFP microenviornmental cells. Each sample constituted a pooling of 2 males and 2 females that were 6 mpf This led to generation of 4 samples total GFP+ body cells GFP body cells GFP+ fin cells GFP fin cells. Data was then analyzed and pooled together taking note of their sample origin.", null, "pubmed:35355015", null, "XBN", "GSM5510265", null, "source name:Zebrafish body skin|model:Acral melanoma model Caspers with MiniCoopR eGFP mitfa:hsCRKL mitfa:hsGAB2 mitfa:hsTERT mitfa:Cas9 mCherry;U6 nf1a gRNA mitfa:Cas9 mCherry;U6 nf1b gRNA|tissue:Body|cell type:GFP ", "XBN", "Data was processed using R version 4.0.4 and Seurat version 4.0.3 Hao Hao et al. 2021. Each of the four reactions were processed separately before merging into a single object. Cells with fewer than 200 unique genes were filtered out. Expression data was normalized with SCTransform Hafemeister and Satija 2019. Principal component analysis Joliffe 1986 and UMAP dimensionality reduction McInnes 2018 were performed using default parameters with 15 principal components used for UMAP calculations. Clustering was done using the Seurat function FindMarkers with a resolution of 0.2. Clusters were annotated based on expression of zebrafish cell type marker genes as done previously Baron et al. 2020; Hunter Moncada et al. 2021. Genome build: GRCz10 Supplementary files format and content: csv file containing counts from all 4 samples Supplementary files format and content: Cell ranger output", "Zebrafish body skin", null, "Droplet based scRNA seq was performed using the Chromium Single Cell 3\u2019 Library and Gel Bead Kit v3 10X Genomics and Chromium Single Cell 3\u2019 Chip G 10X Genomics. Approximately 10 000 cells were encapsulated per each of the four reactions. GEM generation and library preparation was performed according to kit instructions. Libraries were sequenced on a NovaSeq S4 flow cell. Sequencing parameters were: Read1 28 cycles i5 10 cycles i7 10 cycles Read2 90 cycles. Sequencing depth was approximately 40 000 reads per cell. Sequencing data was aligned to our reference zebrafish genome using CellRanger version 5.0.1 10X Genomics. scRNA seq 10X genomics", null, "model:Acral melanoma model Caspers with MiniCoopR eGFP mitfa:hsCRKL mitfa:hsGAB2 mitfa:hsTERT mitfa:Cas9 mCherry;U6 nf1a gRNA mitfa:Cas9 mCherry;U6 nf1b gRNA|tissue:Body|cell type:GFP ", "GSM5510265", "GSM5510265: XBN; Danio rerio; RNA Seq", "GSM5510265", null, "1", "Droplet based scRNA seq was performed using the Chromium Single Cell three prime Library and Gel Bead Kit v3 10X Genomics and Chromium Single Cell three prime Chip G 10X Genomics. Approximately 10 000 cells were encapsulated per each of the four reactions. GEM generation and library preparation was performed according to kit instructions. Libraries were sequenced on a NovaSeq S4 flow cell. Sequencing parameters were: Read1 28 cycles i5 10 cycles i7 10 cycles Read2 90 cycles. Sequencing depth was approximately 40 000 reads per cell. Sequencing data was aligned to our reference zebrafish genome using CellRanger version 5.0.1 10X Genomics. scRNA seq 10X genomics", "GEO Accession:GSM5510265", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP331755", null, null, "2387_XBN_IGO_11718_6_S6_L001_R1_001.fastq.gz 2387_XBN_IGO_11718_6_S6_L001_R2_001.fastq.gz", "fastq fastq", 19425231072.0, 166027616.0, "GSM5510265 r1", "0:29 1:88", "A:5317276529;C:4456617510;G:4523328168;T:5127353259;N:655606", 29, 88, null, null, 5317276529, 4456617510, 4523328168, 5127353259, 655606, "SRX11692437", "SRS9724034", "SRA1274997", "GEO", "White, Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center", 2, 0.00419, 0.81051, 0.00138, 0.0994, 0.9936, 0.81523, 0.4397, 0.5459, 29, 88, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2021-08-09", "Undetermined", "Adult", "Trunk", "Surface Structure"], [65594, "SRR15390208", "SRX11692437", "SRS9724034", "SRP331755", "PRJNA753151", "scRNA seq of fin and body zebrafish melanocytes", "GSE181748", "Transcriptome Analysis", "Oncogenic alterations to DNA are not transforming in all cellular contexts. This may be due to pre existing transcriptional programs in the cell of origin. Here we define anatomic position as a major determinant of why cells respond to specific oncogenes. Cutaneous melanoma arises throughout the body whereas the acral subtype arises on the palms of the hands soles of the feet or under the nails3. We sequenced the DNA of cutaneous and acral melanomas from a large cohort of human patients and found a specific enrichment for BRAF mutations in cutaneous melanoma but CRKL amplifications in acral melanoma. We modeled these changes in transgenic zebrafish models and found that CRKL driven tumors predominantly formed in the fins of the fish. The fins are the evolutionary precursors to tetrapod limbs indicating that melanocytes in these acral locations may be uniquely susceptible to CRKL. RNA profiling of these fin/limb melanocytes compared to body melanocytes revealed a positional identity gene program typified by posterior HOX13 genes. This positional gene program synergized with CRKL to drive tumors at acral sites. Abrogation of this CRKL driven program eliminated the anatomic specificity of acral melanoma. These data suggest that the anatomic position of the cell of origin endows it with a unique transcriptional state that makes it susceptible to only certain oncogenic insults. Overall design: For this experiment we used our zebrafish transgenic model of Acral melanoma which was generated by injecting Casper fish with MniCoopR GFP mitfa:hsCRKL mitfa:hsGAB2 mitfa:hsTERT mitfa:Cas9 mCherry;U6nf1a gRNA mitfa:Cas9 mCherry;U6 nf1b gRNA. Fish were dissected to collect body skin and fins digested using liberase and then FACS sorted for GFP+ melanocytes and GFP microenviornmental cells. Each sample constituted a pooling of 2 males and 2 females that were 6 mpf This led to generation of 4 samples total GFP+ body cells GFP body cells GFP+ fin cells GFP fin cells. Data was then analyzed and pooled together taking note of their sample origin.", null, "pubmed:35355015", null, "XBN", "GSM5510265", null, "source name:Zebrafish body skin|model:Acral melanoma model Caspers with MiniCoopR eGFP mitfa:hsCRKL mitfa:hsGAB2 mitfa:hsTERT mitfa:Cas9 mCherry;U6 nf1a gRNA mitfa:Cas9 mCherry;U6 nf1b gRNA|tissue:Body|cell type:GFP ", "XBN", "Data was processed using R version 4.0.4 and Seurat version 4.0.3 Hao Hao et al. 2021. Each of the four reactions were processed separately before merging into a single object. Cells with fewer than 200 unique genes were filtered out. Expression data was normalized with SCTransform Hafemeister and Satija 2019. Principal component analysis Joliffe 1986 and UMAP dimensionality reduction McInnes 2018 were performed using default parameters with 15 principal components used for UMAP calculations. Clustering was done using the Seurat function FindMarkers with a resolution of 0.2. Clusters were annotated based on expression of zebrafish cell type marker genes as done previously Baron et al. 2020; Hunter Moncada et al. 2021. Genome build: GRCz10 Supplementary files format and content: csv file containing counts from all 4 samples Supplementary files format and content: Cell ranger output", "Zebrafish body skin", null, "Droplet based scRNA seq was performed using the Chromium Single Cell 3\u2019 Library and Gel Bead Kit v3 10X Genomics and Chromium Single Cell 3\u2019 Chip G 10X Genomics. Approximately 10 000 cells were encapsulated per each of the four reactions. GEM generation and library preparation was performed according to kit instructions. Libraries were sequenced on a NovaSeq S4 flow cell. Sequencing parameters were: Read1 28 cycles i5 10 cycles i7 10 cycles Read2 90 cycles. Sequencing depth was approximately 40 000 reads per cell. Sequencing data was aligned to our reference zebrafish genome using CellRanger version 5.0.1 10X Genomics. scRNA seq 10X genomics", null, "model:Acral melanoma model Caspers with MiniCoopR eGFP mitfa:hsCRKL mitfa:hsGAB2 mitfa:hsTERT mitfa:Cas9 mCherry;U6 nf1a gRNA mitfa:Cas9 mCherry;U6 nf1b gRNA|tissue:Body|cell type:GFP ", "GSM5510265", "GSM5510265: XBN; Danio rerio; RNA Seq", "GSM5510265", null, "1", "Droplet based scRNA seq was performed using the Chromium Single Cell three prime Library and Gel Bead Kit v3 10X Genomics and Chromium Single Cell three prime Chip G 10X Genomics. Approximately 10 000 cells were encapsulated per each of the four reactions. GEM generation and library preparation was performed according to kit instructions. Libraries were sequenced on a NovaSeq S4 flow cell. Sequencing parameters were: Read1 28 cycles i5 10 cycles i7 10 cycles Read2 90 cycles. Sequencing depth was approximately 40 000 reads per cell. Sequencing data was aligned to our reference zebrafish genome using CellRanger version 5.0.1 10X Genomics. scRNA seq 10X genomics", "GEO Accession:GSM5510265", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP331755", null, null, "2387_XBN_IGO_11718_6_S6_L002_R1_001.fastq.gz 2387_XBN_IGO_11718_6_S6_L002_R2_001.fastq.gz", "fastq fastq", 19057747059.0, 162886727.0, "GSM5510265 r2", "0:29 1:88", "A:5220986791;C:4370566015;G:4433233229;T:5032336069;N:624955", 29, 88, null, null, 5220986791, 4370566015, 4433233229, 5032336069, 624955, "SRX11692437", "SRS9724034", "SRA1274997", "GEO", "White, Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center", 2, 0.00434, 0.81103, 0.00156, 0.09907, 0.99417, 0.81274, 0.44052, 0.54695, 29, 88, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2021-08-09", "Undetermined", "Adult", "Trunk", "Surface Structure"], [65595, "SRR15390205", "SRX11692435", "SRS9724032", "SRP331755", "PRJNA753151", "scRNA seq of fin and body zebrafish melanocytes", "GSE181748", "Transcriptome Analysis", "Oncogenic alterations to DNA are not transforming in all cellular contexts. This may be due to pre existing transcriptional programs in the cell of origin. Here we define anatomic position as a major determinant of why cells respond to specific oncogenes. Cutaneous melanoma arises throughout the body whereas the acral subtype arises on the palms of the hands soles of the feet or under the nails3. We sequenced the DNA of cutaneous and acral melanomas from a large cohort of human patients and found a specific enrichment for BRAF mutations in cutaneous melanoma but CRKL amplifications in acral melanoma. We modeled these changes in transgenic zebrafish models and found that CRKL driven tumors predominantly formed in the fins of the fish. The fins are the evolutionary precursors to tetrapod limbs indicating that melanocytes in these acral locations may be uniquely susceptible to CRKL. RNA profiling of these fin/limb melanocytes compared to body melanocytes revealed a positional identity gene program typified by posterior HOX13 genes. This positional gene program synergized with CRKL to drive tumors at acral sites. Abrogation of this CRKL driven program eliminated the anatomic specificity of acral melanoma. These data suggest that the anatomic position of the cell of origin endows it with a unique transcriptional state that makes it susceptible to only certain oncogenic insults. Overall design: For this experiment we used our zebrafish transgenic model of Acral melanoma which was generated by injecting Casper fish with MniCoopR GFP mitfa:hsCRKL mitfa:hsGAB2 mitfa:hsTERT mitfa:Cas9 mCherry;U6nf1a gRNA mitfa:Cas9 mCherry;U6 nf1b gRNA. Fish were dissected to collect body skin and fins digested using liberase and then FACS sorted for GFP+ melanocytes and GFP microenviornmental cells. Each sample constituted a pooling of 2 males and 2 females that were 6 mpf This led to generation of 4 samples total GFP+ body cells GFP body cells GFP+ fin cells GFP fin cells. Data was then analyzed and pooled together taking note of their sample origin.", null, "pubmed:35355015", null, "XBG", "GSM5510264", null, "source name:Zebrafish body skin|model:Acral melanoma model Caspers with MiniCoopR eGFP mitfa:hsCRKL mitfa:hsGAB2 mitfa:hsTERT mitfa:Cas9 mCherry;U6 nf1a gRNA mitfa:Cas9 mCherry;U6 nf1b gRNA|tissue:Body|cell type:GFP+", "XBG", "Data was processed using R version 4.0.4 and Seurat version 4.0.3 Hao Hao et al. 2021. Each of the four reactions were processed separately before merging into a single object. Cells with fewer than 200 unique genes were filtered out. Expression data was normalized with SCTransform Hafemeister and Satija 2019. Principal component analysis Joliffe 1986 and UMAP dimensionality reduction McInnes 2018 were performed using default parameters with 15 principal components used for UMAP calculations. Clustering was done using the Seurat function FindMarkers with a resolution of 0.2. Clusters were annotated based on expression of zebrafish cell type marker genes as done previously Baron et al. 2020; Hunter Moncada et al. 2021. Genome build: GRCz10 Supplementary files format and content: csv file containing counts from all 4 samples Supplementary files format and content: Cell ranger output", "Zebrafish body skin", null, "Droplet based scRNA seq was performed using the Chromium Single Cell 3\u2019 Library and Gel Bead Kit v3 10X Genomics and Chromium Single Cell 3\u2019 Chip G 10X Genomics. Approximately 10 000 cells were encapsulated per each of the four reactions. GEM generation and library preparation was performed according to kit instructions. Libraries were sequenced on a NovaSeq S4 flow cell. Sequencing parameters were: Read1 28 cycles i5 10 cycles i7 10 cycles Read2 90 cycles. Sequencing depth was approximately 40 000 reads per cell. Sequencing data was aligned to our reference zebrafish genome using CellRanger version 5.0.1 10X Genomics. scRNA seq 10X genomics", null, "model:Acral melanoma model Caspers with MiniCoopR eGFP mitfa:hsCRKL mitfa:hsGAB2 mitfa:hsTERT mitfa:Cas9 mCherry;U6 nf1a gRNA mitfa:Cas9 mCherry;U6 nf1b gRNA|tissue:Body|cell type:GFP+", "GSM5510264", "GSM5510264: XBG; Danio rerio; RNA Seq", "GSM5510264", null, "1", "Droplet based scRNA seq was performed using the Chromium Single Cell three prime Library and Gel Bead Kit v3 10X Genomics and Chromium Single Cell three prime Chip G 10X Genomics. Approximately 10 000 cells were encapsulated per each of the four reactions. GEM generation and library preparation was performed according to kit instructions. Libraries were sequenced on a NovaSeq S4 flow cell. Sequencing parameters were: Read1 28 cycles i5 10 cycles i7 10 cycles Read2 90 cycles. Sequencing depth was approximately 40 000 reads per cell. Sequencing data was aligned to our reference zebrafish genome using CellRanger version 5.0.1 10X Genomics. scRNA seq 10X genomics", "GEO Accession:GSM5510264", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP331755", null, null, "2386_XBG_IGO_11718_5_S5_L001_R1_001.fastq.gz 2386_XBG_IGO_11718_5_S5_L001_R2_001.fastq.gz", "fastq fastq", 21756379320.0, 185951960.0, "GSM5510264 r1", "0:29 1:88", "A:6175271825;C:4793640120;G:4981225446;T:5805505185;N:736744", 29, 88, null, null, 6175271825, 4793640120, 4981225446, 5805505185, 736744, "SRX11692435", "SRS9724032", "SRA1274997", "GEO", "White, Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center", 2, 0.00899, 0.8935, 0.00261, 0.14469, 0.99056, 0.79849, 0.434, 0.5426, 29, 88, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2021-08-09", "Undetermined", "Adult", "Trunk", "Surface Structure"], [65596, "SRR15390206", "SRX11692435", "SRS9724032", "SRP331755", "PRJNA753151", "scRNA seq of fin and body zebrafish melanocytes", "GSE181748", "Transcriptome Analysis", "Oncogenic alterations to DNA are not transforming in all cellular contexts. This may be due to pre existing transcriptional programs in the cell of origin. Here we define anatomic position as a major determinant of why cells respond to specific oncogenes. Cutaneous melanoma arises throughout the body whereas the acral subtype arises on the palms of the hands soles of the feet or under the nails3. We sequenced the DNA of cutaneous and acral melanomas from a large cohort of human patients and found a specific enrichment for BRAF mutations in cutaneous melanoma but CRKL amplifications in acral melanoma. We modeled these changes in transgenic zebrafish models and found that CRKL driven tumors predominantly formed in the fins of the fish. The fins are the evolutionary precursors to tetrapod limbs indicating that melanocytes in these acral locations may be uniquely susceptible to CRKL. RNA profiling of these fin/limb melanocytes compared to body melanocytes revealed a positional identity gene program typified by posterior HOX13 genes. This positional gene program synergized with CRKL to drive tumors at acral sites. Abrogation of this CRKL driven program eliminated the anatomic specificity of acral melanoma. These data suggest that the anatomic position of the cell of origin endows it with a unique transcriptional state that makes it susceptible to only certain oncogenic insults. Overall design: For this experiment we used our zebrafish transgenic model of Acral melanoma which was generated by injecting Casper fish with MniCoopR GFP mitfa:hsCRKL mitfa:hsGAB2 mitfa:hsTERT mitfa:Cas9 mCherry;U6nf1a gRNA mitfa:Cas9 mCherry;U6 nf1b gRNA. Fish were dissected to collect body skin and fins digested using liberase and then FACS sorted for GFP+ melanocytes and GFP microenviornmental cells. Each sample constituted a pooling of 2 males and 2 females that were 6 mpf This led to generation of 4 samples total GFP+ body cells GFP body cells GFP+ fin cells GFP fin cells. Data was then analyzed and pooled together taking note of their sample origin.", null, "pubmed:35355015", null, "XBG", "GSM5510264", null, "source name:Zebrafish body skin|model:Acral melanoma model Caspers with MiniCoopR eGFP mitfa:hsCRKL mitfa:hsGAB2 mitfa:hsTERT mitfa:Cas9 mCherry;U6 nf1a gRNA mitfa:Cas9 mCherry;U6 nf1b gRNA|tissue:Body|cell type:GFP+", "XBG", "Data was processed using R version 4.0.4 and Seurat version 4.0.3 Hao Hao et al. 2021. Each of the four reactions were processed separately before merging into a single object. Cells with fewer than 200 unique genes were filtered out. Expression data was normalized with SCTransform Hafemeister and Satija 2019. Principal component analysis Joliffe 1986 and UMAP dimensionality reduction McInnes 2018 were performed using default parameters with 15 principal components used for UMAP calculations. Clustering was done using the Seurat function FindMarkers with a resolution of 0.2. Clusters were annotated based on expression of zebrafish cell type marker genes as done previously Baron et al. 2020; Hunter Moncada et al. 2021. Genome build: GRCz10 Supplementary files format and content: csv file containing counts from all 4 samples Supplementary files format and content: Cell ranger output", "Zebrafish body skin", null, "Droplet based scRNA seq was performed using the Chromium Single Cell 3\u2019 Library and Gel Bead Kit v3 10X Genomics and Chromium Single Cell 3\u2019 Chip G 10X Genomics. Approximately 10 000 cells were encapsulated per each of the four reactions. GEM generation and library preparation was performed according to kit instructions. Libraries were sequenced on a NovaSeq S4 flow cell. Sequencing parameters were: Read1 28 cycles i5 10 cycles i7 10 cycles Read2 90 cycles. Sequencing depth was approximately 40 000 reads per cell. Sequencing data was aligned to our reference zebrafish genome using CellRanger version 5.0.1 10X Genomics. scRNA seq 10X genomics", null, "model:Acral melanoma model Caspers with MiniCoopR eGFP mitfa:hsCRKL mitfa:hsGAB2 mitfa:hsTERT mitfa:Cas9 mCherry;U6 nf1a gRNA mitfa:Cas9 mCherry;U6 nf1b gRNA|tissue:Body|cell type:GFP+", "GSM5510264", "GSM5510264: XBG; Danio rerio; RNA Seq", "GSM5510264", null, "1", "Droplet based scRNA seq was performed using the Chromium Single Cell three prime Library and Gel Bead Kit v3 10X Genomics and Chromium Single Cell three prime Chip G 10X Genomics. Approximately 10 000 cells were encapsulated per each of the four reactions. GEM generation and library preparation was performed according to kit instructions. Libraries were sequenced on a NovaSeq S4 flow cell. Sequencing parameters were: Read1 28 cycles i5 10 cycles i7 10 cycles Read2 90 cycles. Sequencing depth was approximately 40 000 reads per cell. Sequencing data was aligned to our reference zebrafish genome using CellRanger version 5.0.1 10X Genomics. scRNA seq 10X genomics", "GEO Accession:GSM5510264", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP331755", null, null, "2386_XBG_IGO_11718_5_S5_L002_R1_001.fastq.gz 2386_XBG_IGO_11718_5_S5_L002_R2_001.fastq.gz", "fastq fastq", 21271780062.0, 181810086.0, "GSM5510264 r2", "0:29 1:88", "A:6043225103;C:4683532253;G:4864212050;T:5680108261;N:702395", 29, 88, null, null, 6043225103, 4683532253, 4864212050, 5680108261, 702395, "SRX11692435", "SRS9724032", "SRA1274997", "GEO", "White, Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center", 2, 0.00858, 0.89419, 0.00266, 0.14661, 0.99034, 0.79622, 0.39545, 0.56688, 29, 88, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2021-08-09", "Undetermined", "Adult", "Trunk", "Surface Structure"], [66719, "SRR16490785", "SRX12693895", "SRS10644777", "SRP342165", "PRJNA772761", "Single cell transcriptomics reveals critical molecular programming of progenitors for motor neurons and oligodendrocytes in zebrafish", "GSE186163", "Transcriptome Analysis", "pmn progenitors and their offspring in spinal cords are isolated for sc RNAseq Overall design: olig2+ cells were isolated from the trunks of Tgolig2:dsred by FACS and underwent scRNA seq", null, "pubmed:36063998", null, "olig2+ cells in zebrafish trunks 60hpf", "GSM5639644", null, "source name:Tgolig2:dsred trunks|Stage:60 hpf|genotype:Tg olig2:dsred|tissue:trunk", "olig2+ cells in zebrafish trunks 60hpf", "Alignment filtering barcode counting and UMI counting were performed with cellranger count module to generate feature barcode matrix and determine clusters. Genes detectable in more than two cells were defined as \u201cexpressed\u201d. Cells with <1000 genes detected were removed. Counts were normalized to 10000 and transformed into logarithmic scales. A neighborhood graph was embedded using UMAP displaying the top 4000 highly variable genes across cells. Cells were clustered by the Louvain Algorithm. The trajectory interface of all cell clusters was done using the layout 'fa'. These analyses were performed by the Python based SCANPY package Genome build: GRCz11 Supplementary files format and content: Matrix table with raw gene counts for every gene and every sample", "Tgolig2:dsred trunks", null, "Tgolig2:dsred trunks were dissected and dissociated with 0.25% trypsin. Fluorescent cells were isolated with FACS. RNA was extracted with Trizol. cDNAs were amplified and libraries were generated with the Single Cell 3\u2019 Library and Gel Bead kit V3", null, "Stage:60 hpf|genotype:Tg olig2:dsred|tissue:trunk", "GSM5639644", "GSM5639644: olig2+ cells in zebrafish trunks 60hpf; Danio rerio; RNA Seq", "GSM5639644 r1", "GSM5639644", "1", "Tgolig2:dsred trunks were dissected and dissociated with 0.25% trypsin. Fluorescent cells were isolated with FACS. RNA was extracted with Trizol. cDNAs were amplified and libraries were generated with the Single Cell three prime Library and Gel Bead kit V3", null, "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP342165", null, null, "200326C_z60hpf_S1_L001_R1_001.fastq.gz 200326C_z60hpf_S1_L001_R2_001.fastq.gz", "fastq fastq", 27364318800.0, 91214396.0, "GSM5639644 r1", "0:150 1:150", "A:10071536495;C:5175486957;G:4924076777;T:7192804284;N:414287", 150, 150, null, null, 10071536495, 5175486957, 4924076777, 7192804284, 414287, "SRX12693895", "SRS10644777", "SRA1322635", "Nantong University", "Nantong University", 2, 0.0, 0.90895, 0.0, 0.13505, 1.0, 0.79797, null, 0.51047, 150, 150, "T", "B", "mate1 technical by mapping diff", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "China", "2021-10-19", "Hatching", "Embryo", "Trunk", "Surface Structure"], [66720, "SRR16490786", "SRX12693895", "SRS10644777", "SRP342165", "PRJNA772761", "Single cell transcriptomics reveals critical molecular programming of progenitors for motor neurons and oligodendrocytes in zebrafish", "GSE186163", "Transcriptome Analysis", "pmn progenitors and their offspring in spinal cords are isolated for sc RNAseq Overall design: olig2+ cells were isolated from the trunks of Tgolig2:dsred by FACS and underwent scRNA seq", null, "pubmed:36063998", null, "olig2+ cells in zebrafish trunks 60hpf", "GSM5639644", null, "source name:Tgolig2:dsred trunks|Stage:60 hpf|genotype:Tg olig2:dsred|tissue:trunk", "olig2+ cells in zebrafish trunks 60hpf", "Alignment filtering barcode counting and UMI counting were performed with cellranger count module to generate feature barcode matrix and determine clusters. Genes detectable in more than two cells were defined as \u201cexpressed\u201d. Cells with <1000 genes detected were removed. Counts were normalized to 10000 and transformed into logarithmic scales. A neighborhood graph was embedded using UMAP displaying the top 4000 highly variable genes across cells. Cells were clustered by the Louvain Algorithm. The trajectory interface of all cell clusters was done using the layout 'fa'. These analyses were performed by the Python based SCANPY package Genome build: GRCz11 Supplementary files format and content: Matrix table with raw gene counts for every gene and every sample", "Tgolig2:dsred trunks", null, "Tgolig2:dsred trunks were dissected and dissociated with 0.25% trypsin. Fluorescent cells were isolated with FACS. RNA was extracted with Trizol. cDNAs were amplified and libraries were generated with the Single Cell 3\u2019 Library and Gel Bead kit V3", null, "Stage:60 hpf|genotype:Tg olig2:dsred|tissue:trunk", "GSM5639644", "GSM5639644: olig2+ cells in zebrafish trunks 60hpf; Danio rerio; RNA Seq", "GSM5639644 r1", "GSM5639644", "1", "Tgolig2:dsred trunks were dissected and dissociated with 0.25% trypsin. Fluorescent cells were isolated with FACS. RNA was extracted with Trizol. cDNAs were amplified and libraries were generated with the Single Cell three prime Library and Gel Bead kit V3", null, "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP342165", null, null, "200326C_z60hpf_S1_L002_R1_001.fastq.gz 200326C_z60hpf_S1_L002_R2_001.fastq.gz", "fastq fastq", 25135796400.0, 83785988.0, "GSM5639644 r2", "0:150 1:150", "A:9233555166;C:4754173569;G:4523141240;T:6624550958;N:375467", 150, 150, null, null, 9233555166, 4754173569, 4523141240, 6624550958, 375467, "SRX12693895", "SRS10644777", "SRA1322635", "Nantong University", "Nantong University", 2, 0.0, 0.91014, 0.0, 0.13408, 1.0, 0.79805, null, 0.50682, 150, 150, "T", "B", "mate1 technical by mapping diff", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "China", "2021-10-19", "Hatching", "Embryo", "Trunk", "Surface Structure"], [66721, "SRR16490787", "SRX12693895", "SRS10644777", "SRP342165", "PRJNA772761", "Single cell transcriptomics reveals critical molecular programming of progenitors for motor neurons and oligodendrocytes in zebrafish", "GSE186163", "Transcriptome Analysis", "pmn progenitors and their offspring in spinal cords are isolated for sc RNAseq Overall design: olig2+ cells were isolated from the trunks of Tgolig2:dsred by FACS and underwent scRNA seq", null, "pubmed:36063998", null, "olig2+ cells in zebrafish trunks 60hpf", "GSM5639644", null, "source name:Tgolig2:dsred trunks|Stage:60 hpf|genotype:Tg olig2:dsred|tissue:trunk", "olig2+ cells in zebrafish trunks 60hpf", "Alignment filtering barcode counting and UMI counting were performed with cellranger count module to generate feature barcode matrix and determine clusters. Genes detectable in more than two cells were defined as \u201cexpressed\u201d. Cells with <1000 genes detected were removed. Counts were normalized to 10000 and transformed into logarithmic scales. A neighborhood graph was embedded using UMAP displaying the top 4000 highly variable genes across cells. Cells were clustered by the Louvain Algorithm. The trajectory interface of all cell clusters was done using the layout 'fa'. These analyses were performed by the Python based SCANPY package Genome build: GRCz11 Supplementary files format and content: Matrix table with raw gene counts for every gene and every sample", "Tgolig2:dsred trunks", null, "Tgolig2:dsred trunks were dissected and dissociated with 0.25% trypsin. Fluorescent cells were isolated with FACS. RNA was extracted with Trizol. cDNAs were amplified and libraries were generated with the Single Cell 3\u2019 Library and Gel Bead kit V3", null, "Stage:60 hpf|genotype:Tg olig2:dsred|tissue:trunk", "GSM5639644", "GSM5639644: olig2+ cells in zebrafish trunks 60hpf; Danio rerio; RNA Seq", "GSM5639644 r1", "GSM5639644", "1", "Tgolig2:dsred trunks were dissected and dissociated with 0.25% trypsin. Fluorescent cells were isolated with FACS. RNA was extracted with Trizol. cDNAs were amplified and libraries were generated with the Single Cell three prime Library and Gel Bead kit V3", null, "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP342165", null, null, "200326C_z60hpf_S1_L003_R1_001.fastq.gz 200326C_z60hpf_S1_L003_R2_001.fastq.gz", "fastq fastq", 26660624700.0, 88868749.0, "GSM5639644 r3", "0:150 1:150", "A:9806302304;C:5038591446;G:4797994616;T:7017333749;N:402585", 150, 150, null, null, 9806302304, 5038591446, 4797994616, 7017333749, 402585, "SRX12693895", "SRS10644777", "SRA1322635", "Nantong University", "Nantong University", 2, 0.0, 0.90794, 0.0, 0.13331, 1.0, 0.79981, null, 0.50544, 150, 150, "T", "B", "mate1 technical by mapping diff", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "China", "2021-10-19", "Hatching", "Embryo", "Trunk", "Surface Structure"], [66722, "SRR16490788", "SRX12693895", "SRS10644777", "SRP342165", "PRJNA772761", "Single cell transcriptomics reveals critical molecular programming of progenitors for motor neurons and oligodendrocytes in zebrafish", "GSE186163", "Transcriptome Analysis", "pmn progenitors and their offspring in spinal cords are isolated for sc RNAseq Overall design: olig2+ cells were isolated from the trunks of Tgolig2:dsred by FACS and underwent scRNA seq", null, "pubmed:36063998", null, "olig2+ cells in zebrafish trunks 60hpf", "GSM5639644", null, "source name:Tgolig2:dsred trunks|Stage:60 hpf|genotype:Tg olig2:dsred|tissue:trunk", "olig2+ cells in zebrafish trunks 60hpf", "Alignment filtering barcode counting and UMI counting were performed with cellranger count module to generate feature barcode matrix and determine clusters. Genes detectable in more than two cells were defined as \u201cexpressed\u201d. Cells with <1000 genes detected were removed. Counts were normalized to 10000 and transformed into logarithmic scales. A neighborhood graph was embedded using UMAP displaying the top 4000 highly variable genes across cells. Cells were clustered by the Louvain Algorithm. The trajectory interface of all cell clusters was done using the layout 'fa'. These analyses were performed by the Python based SCANPY package Genome build: GRCz11 Supplementary files format and content: Matrix table with raw gene counts for every gene and every sample", "Tgolig2:dsred trunks", null, "Tgolig2:dsred trunks were dissected and dissociated with 0.25% trypsin. Fluorescent cells were isolated with FACS. RNA was extracted with Trizol. cDNAs were amplified and libraries were generated with the Single Cell 3\u2019 Library and Gel Bead kit V3", null, "Stage:60 hpf|genotype:Tg olig2:dsred|tissue:trunk", "GSM5639644", "GSM5639644: olig2+ cells in zebrafish trunks 60hpf; Danio rerio; RNA Seq", "GSM5639644 r1", "GSM5639644", "1", "Tgolig2:dsred trunks were dissected and dissociated with 0.25% trypsin. Fluorescent cells were isolated with FACS. RNA was extracted with Trizol. cDNAs were amplified and libraries were generated with the Single Cell three prime Library and Gel Bead kit V3", null, "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP342165", null, null, "200326C_z60hpf_S1_L004_R1_001.fastq.gz 200326C_z60hpf_S1_L004_R2_001.fastq.gz", "fastq fastq", 26473468500.0, 88244895.0, "GSM5639644 r4", "0:150 1:150", "A:9733096090;C:5005227733;G:4764331985;T:6970420076;N:392616", 150, 150, null, null, 9733096090, 5005227733, 4764331985, 6970420076, 392616, "SRX12693895", "SRS10644777", "SRA1322635", "Nantong University", "Nantong University", 2, 0.0, 0.90896, 0.0, 0.13496, 1.0, 0.79817, null, 0.51059, 150, 150, "T", "B", "mate1 technical by mapping diff", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "China", "2021-10-19", "Hatching", "Embryo", "Trunk", "Surface Structure"], [66723, "SRR16490789", "SRX12693894", "SRS10644776", "SRP342165", "PRJNA772761", "Single cell transcriptomics reveals critical molecular programming of progenitors for motor neurons and oligodendrocytes in zebrafish", "GSE186163", "Transcriptome Analysis", "pmn progenitors and their offspring in spinal cords are isolated for sc RNAseq Overall design: olig2+ cells were isolated from the trunks of Tgolig2:dsred by FACS and underwent scRNA seq", null, "pubmed:36063998", null, "olig2+ cells in zebrafish trunks 28hpf", "GSM5639643", null, "source name:Tgolig2:dsred trunks|Stage:28 hpf|genotype:Tg olig2:dsred|tissue:trunk", "olig2+ cells in zebrafish trunks 28hpf", "Alignment filtering barcode counting and UMI counting were performed with cellranger count module to generate feature barcode matrix and determine clusters. Genes detectable in more than two cells were defined as \u201cexpressed\u201d. Cells with <1000 genes detected were removed. Counts were normalized to 10000 and transformed into logarithmic scales. A neighborhood graph was embedded using UMAP displaying the top 4000 highly variable genes across cells. Cells were clustered by the Louvain Algorithm. The trajectory interface of all cell clusters was done using the layout 'fa'. These analyses were performed by the Python based SCANPY package Genome build: GRCz11 Supplementary files format and content: Matrix table with raw gene counts for every gene and every sample", "Tgolig2:dsred trunks", null, "Tgolig2:dsred trunks were dissected and dissociated with 0.25% trypsin. Fluorescent cells were isolated with FACS. RNA was extracted with Trizol. cDNAs were amplified and libraries were generated with the Single Cell 3\u2019 Library and Gel Bead kit V3", null, "Stage:28 hpf|genotype:Tg olig2:dsred|tissue:trunk", "GSM5639643", "GSM5639643: olig2+ cells in zebrafish trunks 28hpf; Danio rerio; RNA Seq", "GSM5639643 r1", "GSM5639643", "1", "Tgolig2:dsred trunks were dissected and dissociated with 0.25% trypsin. Fluorescent cells were isolated with FACS. RNA was extracted with Trizol. cDNAs were amplified and libraries were generated with the Single Cell three prime Library and Gel Bead kit V3", null, "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP342165", null, null, "200326C_z28hpf_S1_L001_R1_001.fastq.gz 200326C_z28hpf_S1_L001_R2_001.fastq.gz", "fastq fastq", 17790840000.0, 59302800.0, "GSM5639643 r1", "0:150 1:150", "A:6396040437;C:3363869870;G:3210547721;T:4820107751;N:274221", 150, 150, null, null, 6396040437, 3363869870, 3210547721, 4820107751, 274221, "SRX12693894", "SRS10644776", "SRA1322635", "Nantong University", "Nantong University", 2, 0.0, 0.89269, 0.0, 0.14196, 1.0, 0.80998, null, 0.49581, 150, 150, "T", "B", "mate1 technical by mapping diff", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "China", "2021-10-19", "Pharyngula", "Embryo", "Trunk", "Surface Structure"], [66724, "SRR16490790", "SRX12693894", "SRS10644776", "SRP342165", "PRJNA772761", "Single cell transcriptomics reveals critical molecular programming of progenitors for motor neurons and oligodendrocytes in zebrafish", "GSE186163", "Transcriptome Analysis", "pmn progenitors and their offspring in spinal cords are isolated for sc RNAseq Overall design: olig2+ cells were isolated from the trunks of Tgolig2:dsred by FACS and underwent scRNA seq", null, "pubmed:36063998", null, "olig2+ cells in zebrafish trunks 28hpf", "GSM5639643", null, "source name:Tgolig2:dsred trunks|Stage:28 hpf|genotype:Tg olig2:dsred|tissue:trunk", "olig2+ cells in zebrafish trunks 28hpf", "Alignment filtering barcode counting and UMI counting were performed with cellranger count module to generate feature barcode matrix and determine clusters. Genes detectable in more than two cells were defined as \u201cexpressed\u201d. Cells with <1000 genes detected were removed. Counts were normalized to 10000 and transformed into logarithmic scales. A neighborhood graph was embedded using UMAP displaying the top 4000 highly variable genes across cells. Cells were clustered by the Louvain Algorithm. The trajectory interface of all cell clusters was done using the layout 'fa'. These analyses were performed by the Python based SCANPY package Genome build: GRCz11 Supplementary files format and content: Matrix table with raw gene counts for every gene and every sample", "Tgolig2:dsred trunks", null, "Tgolig2:dsred trunks were dissected and dissociated with 0.25% trypsin. Fluorescent cells were isolated with FACS. RNA was extracted with Trizol. cDNAs were amplified and libraries were generated with the Single Cell 3\u2019 Library and Gel Bead kit V3", null, "Stage:28 hpf|genotype:Tg olig2:dsred|tissue:trunk", "GSM5639643", "GSM5639643: olig2+ cells in zebrafish trunks 28hpf; Danio rerio; RNA Seq", "GSM5639643 r1", "GSM5639643", "1", "Tgolig2:dsred trunks were dissected and dissociated with 0.25% trypsin. Fluorescent cells were isolated with FACS. RNA was extracted with Trizol. cDNAs were amplified and libraries were generated with the Single Cell three prime Library and Gel Bead kit V3", null, "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP342165", null, null, "200326C_z28hpf_S1_L002_R1_001.fastq.gz 200326C_z28hpf_S1_L002_R2_001.fastq.gz", "fastq fastq", 25907915400.0, 86359718.0, "GSM5639643 r2", "0:150 1:150", "A:9312085267;C:4909235081;G:4679112677;T:7007080032;N:402343", 150, 150, null, null, 9312085267, 4909235081, 4679112677, 7007080032, 402343, "SRX12693894", "SRS10644776", "SRA1322635", "Nantong University", "Nantong University", 2, 0.0, 0.89826, 0.0, 0.14235, 1.0, 0.80949, null, 0.50368, 150, 150, "T", "B", "mate1 technical by mapping diff", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "China", "2021-10-19", "Pharyngula", "Embryo", "Trunk", "Surface Structure"], [66725, "SRR16490791", "SRX12693894", "SRS10644776", "SRP342165", "PRJNA772761", "Single cell transcriptomics reveals critical molecular programming of progenitors for motor neurons and oligodendrocytes in zebrafish", "GSE186163", "Transcriptome Analysis", "pmn progenitors and their offspring in spinal cords are isolated for sc RNAseq Overall design: olig2+ cells were isolated from the trunks of Tgolig2:dsred by FACS and underwent scRNA seq", null, "pubmed:36063998", null, "olig2+ cells in zebrafish trunks 28hpf", "GSM5639643", null, "source name:Tgolig2:dsred trunks|Stage:28 hpf|genotype:Tg olig2:dsred|tissue:trunk", "olig2+ cells in zebrafish trunks 28hpf", "Alignment filtering barcode counting and UMI counting were performed with cellranger count module to generate feature barcode matrix and determine clusters. Genes detectable in more than two cells were defined as \u201cexpressed\u201d. Cells with <1000 genes detected were removed. Counts were normalized to 10000 and transformed into logarithmic scales. A neighborhood graph was embedded using UMAP displaying the top 4000 highly variable genes across cells. Cells were clustered by the Louvain Algorithm. The trajectory interface of all cell clusters was done using the layout 'fa'. These analyses were performed by the Python based SCANPY package Genome build: GRCz11 Supplementary files format and content: Matrix table with raw gene counts for every gene and every sample", "Tgolig2:dsred trunks", null, "Tgolig2:dsred trunks were dissected and dissociated with 0.25% trypsin. Fluorescent cells were isolated with FACS. RNA was extracted with Trizol. cDNAs were amplified and libraries were generated with the Single Cell 3\u2019 Library and Gel Bead kit V3", null, "Stage:28 hpf|genotype:Tg olig2:dsred|tissue:trunk", "GSM5639643", "GSM5639643: olig2+ cells in zebrafish trunks 28hpf; Danio rerio; RNA Seq", "GSM5639643 r1", "GSM5639643", "1", "Tgolig2:dsred trunks were dissected and dissociated with 0.25% trypsin. Fluorescent cells were isolated with FACS. RNA was extracted with Trizol. cDNAs were amplified and libraries were generated with the Single Cell three prime Library and Gel Bead kit V3", null, "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP342165", null, null, "200326C_z28hpf_S1_L003_R1_001.fastq.gz 200326C_z28hpf_S1_L003_R2_001.fastq.gz", "fastq fastq", 22487485800.0, 74958286.0, "GSM5639643 r3", "0:150 1:150", "A:8079631079;C:4246853980;G:4058165201;T:6102481857;N:353683", 150, 150, null, null, 8079631079, 4246853980, 4058165201, 6102481857, 353683, "SRX12693894", "SRS10644776", "SRA1322635", "Nantong University", "Nantong University", 2, 0.0, 0.89773, 0.0, 0.14164, 1.0, 0.80827, null, 0.50003, 150, 150, "T", "B", "mate1 technical by mapping diff", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "China", "2021-10-19", "Pharyngula", "Embryo", "Trunk", "Surface Structure"], [66726, "SRR16490792", "SRX12693894", "SRS10644776", "SRP342165", "PRJNA772761", "Single cell transcriptomics reveals critical molecular programming of progenitors for motor neurons and oligodendrocytes in zebrafish", "GSE186163", "Transcriptome Analysis", "pmn progenitors and their offspring in spinal cords are isolated for sc RNAseq Overall design: olig2+ cells were isolated from the trunks of Tgolig2:dsred by FACS and underwent scRNA seq", null, "pubmed:36063998", null, "olig2+ cells in zebrafish trunks 28hpf", "GSM5639643", null, "source name:Tgolig2:dsred trunks|Stage:28 hpf|genotype:Tg olig2:dsred|tissue:trunk", "olig2+ cells in zebrafish trunks 28hpf", "Alignment filtering barcode counting and UMI counting were performed with cellranger count module to generate feature barcode matrix and determine clusters. Genes detectable in more than two cells were defined as \u201cexpressed\u201d. Cells with <1000 genes detected were removed. Counts were normalized to 10000 and transformed into logarithmic scales. A neighborhood graph was embedded using UMAP displaying the top 4000 highly variable genes across cells. Cells were clustered by the Louvain Algorithm. The trajectory interface of all cell clusters was done using the layout 'fa'. These analyses were performed by the Python based SCANPY package Genome build: GRCz11 Supplementary files format and content: Matrix table with raw gene counts for every gene and every sample", "Tgolig2:dsred trunks", null, "Tgolig2:dsred trunks were dissected and dissociated with 0.25% trypsin. Fluorescent cells were isolated with FACS. RNA was extracted with Trizol. cDNAs were amplified and libraries were generated with the Single Cell 3\u2019 Library and Gel Bead kit V3", null, "Stage:28 hpf|genotype:Tg olig2:dsred|tissue:trunk", "GSM5639643", "GSM5639643: olig2+ cells in zebrafish trunks 28hpf; Danio rerio; RNA Seq", "GSM5639643 r1", "GSM5639643", "1", "Tgolig2:dsred trunks were dissected and dissociated with 0.25% trypsin. Fluorescent cells were isolated with FACS. RNA was extracted with Trizol. cDNAs were amplified and libraries were generated with the Single Cell three prime Library and Gel Bead kit V3", null, "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP342165", null, null, "200326C_z28hpf_S1_L004_R1_001.fastq.gz 200326C_z28hpf_S1_L004_R2_001.fastq.gz", "fastq fastq", 22801608900.0, 76005363.0, "GSM5639643 r4", "0:150 1:150", "A:8194753928;C:4313659172;G:4114764638;T:6178079087;N:352075", 150, 150, null, null, 8194753928, 4313659172, 4114764638, 6178079087, 352075, "SRX12693894", "SRS10644776", "SRA1322635", "Nantong University", "Nantong University", 2, 0.0, 0.89811, 0.0, 0.14101, 1.0, 0.80618, null, 0.4925, 150, 150, "T", "B", "mate1 technical by mapping diff", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "China", "2021-10-19", "Pharyngula", "Embryo", "Trunk", "Surface Structure"], [66757, "SRR23717090", "SRX19578259", "SRS16961241", "SRP342737", "PRJNA773778", "Activation of lineage competence in hemogenic endothelium precedes the formation of hematopoietic stem cell heterogeneity [Zebrafish.STRT seq]", "GSE186425", "Other", "Using a combination of single cell multi omics lineage tracing and functional assays we show that embryonic HSPCs are originated from heterogeneous hemogenic endothelial cells HECs during zebrafish embryogenesis. Overall design: Hematopoietic stem and progenitor cells HSPCs are considered as a heterogeneous population but where and how HSPC heterogeneity occurs remain unclear. Here we performed scRNA seq and scATAC seq with zebrafish 36 hpf VDA derived kdrl+runx1 kdrl+runx1+ and kdrl runx1+ cells. To determine the transcriptional signatures of spi2+ lineages in zebrafish we performed STRT seq with spi2: Gal4;UAS:GFP+ kdrl:mCherry+ HECs and spi2: Gal4;UAS:GFP+ kdrl:mCherry hematopoietic cells at 36 hpf. To investigate the underlying molecular mechanism upon spi2 deficiency we performed scRNA seq with the sorted ECs kdrl+runx1 HECs kdrl+runx1+ and hematopoietic cells kdrl runx1+ from spi2 morphants at 36 hpf. To determine whether spi2 can directly modulate transcriptional programs in EC/HEC we examined genome wide spi2 binding by cut tag assay in fli1a flag spi2 EGFP+ cells sorted from trunk region of Tg fli1a flag spi2 GFP embryos at 36 hpf.", "parent bioproject:PRJNA773771", "pubmed:37016019", null, "DP1 36hpf", "GSM7083138", null, "source name:Zebrafish trunk region|tissue:Zebrafish trunk region 36hpf|cells:single spi2: Gal4;UAS:GFP+ kdrl:mCherry+ HECs and spi2: Gal4;UAS:GFP+ kdrl:mCherry hematopoietic cells|Stage:36 hpf loc name:missing|collection date:missing", "DP1 36hpf", "For scRNA seq and scATAC seq based on 10x Genomics\uff0craw data files were processed by Cell Ranger software suite with default mapping parameters using the GRCz11 reference genome. For STRT seq raw reads were first de multiplexed by barcode sequences in reads 2 to yield separate read files for individual cells then the transcripts sequences of each cell in reads 1 were separated based on corresponding reads 2. Simultaneously UMI sequences in reads 2 were integrated into reads 1. The template switching oligo TSO sequence polyA sequence and the low quality reads N > 10% in reads 1 were subsequently removed by Python scripts and Trimmomatic version 0.36. Next the clean reads were aligned to the zebrafish genome GRCz11 from Ensembl using HISAT2 version 2.1.0 with known gene annotation. Only protein coding genes were retained and the abundance of each gene were estimated by counting the reads that duplicated UMIs have been excluded. For cut&tag reads were aligned to GRCz11 by Bowtie2. Only uniquely mapped reads with mapping quality score\u00a0\u2265 30 were kept using Samtools software. post merging replicates MACS2 was used for the peak calling. Assembly: GRCz11 Library strategy: STRT seq", "Zebrafish trunk region", null, "For 10x Genomics based scRNA seq and scATAC seq in zebrafish 40 000 mCherry+ GFP cells 40 000 mCherry+ GFP+ cells and 30 000 mCherry GFP+ cells were sorted from Tg kdrl:mCherry/runx1:enGFP at 36 hpf. For STRT seq in zebrafish single spi2: Gal4;UAS:GFP+ kdrl:mCherry+ HECs and spi2: Gal4;UAS:GFP+ kdrl:mCherry hematopoietic cells were sorted from the trunk region of Tg spi2: Gal4;UAS:GFP/ kdrl:mCherry at 36 hpf. For scRNA seq of spi2 morphants at 36 hpf in zebrafish ECs kdrl+runx1 HECs kdrl+runx1+ and hematopoietic cells kdrl runx1+ were sorted. For bulk CUT&TAG in zebrafish fli1a flag spi2 EGFP+ cells were sorted from the trunk region of Tg fli1a flag spi2 GFP embryos at 36 hpf. For 10x Genomics based scRNA seq and scATAC seq in zebrafish we loaded 20 000 cells for further 10x Genomics based scRNA seq and 90 000 cells for further 10x Genomics based scATAC seq. For scRNA seq libraries were prepared using Single Cell 3\u2019 Library and Gel Bead Kit V3.1. Sequencing was performed on an Illumina Novaseq6000 platform to generate 150 bp paired end reads. For ATAC seq nuclei were isolated and washed according to the methods supplied by 10x Genomics. Libraries were prepared using the Chromium Chip E Single Cell Kit and Chromium Single Cell ATAC Library & Gel Bead Kit and further sequenced on an Illumina Novaseq6000 platform to generate 50 bp paired end reads. For 10x Genomics based scRNA seq in mice libraries were prepared using Single Cell 3\u2019 Library and Gel Bead Kit V3.1. Sequencing was performed on an Illumina Novaseq6000 platform to generate 150 bp paired end reads. For STRT seq in zebrafish the end repair and dA tailing of the DNA fragments and ligation of the adaptors to the DNA fragments were performed according to the KAPA Hyper Prep Kits with PCR Library Amplification/Illumina series. post the adaptor ligation step the final PCR was performed. The libraries were sequenced on an Illumina Novaseq6000 platform to generate 150 bp paired end reads. For bulk CUT&TAG libraries were prepared according to Hyperactive In Situ ChIP Library Prep Kit for Illumina and sequenced on an Illumina NovaSeq6000 platform to generate 150 bp paired end reads.", null, "tissue:Zebrafish trunk region 36hpf|cells:single spi2: Gal4;UAS:GFP+ kdrl:mCherry+ HECs and spi2: Gal4;UAS:GFP+ kdrl:mCherry hematopoietic cells|Stage:36 hpf", "GSM7083138", "GSM7083138: DP1 36hpf; Danio rerio; OTHER", "GSM7083138 r1", "GSM7083138", "1", "For 10x Genomics based scRNA seq and scATAC seq in zebrafish 40 000 mCherry+ GFP cells 40 000 mCherry+ GFP+ cells and 30 000 mCherry GFP+ cells were sorted from Tg kdrl:mCherry/runx1:enGFP at 36 hpf. For STRT seq in zebrafish single spi2: Gal4;UAS:GFP+ kdrl:mCherry+ HECs and spi2: Gal4;UAS:GFP+ kdrl:mCherry hematopoietic cells were sorted from the trunk region of Tg spi2: Gal4;UAS:GFP/ kdrl:mCherry at 36 hpf. For scRNA seq of spi2 morphants at 36 hpf in zebrafish ECs kdrl+runx1 HECs kdrl+runx1+ and hematopoietic cells kdrl runx1+ were sorted. For bulk CUT&TAG in zebrafish fli1a flag spi2 EGFP+ cells were sorted from the trunk region of Tg fli1a flag spi2 GFP embryos at 36 hpf. For 10x Genomics based scRNA seq and scATAC seq in zebrafish we loaded 20 000 cells for further 10x Genomics based scRNA seq and 90 000 cells for further 10x Genomics based scATAC seq. For scRNA seq libraries were prepared using Single Cell three prime Library and Gel Bead Kit V3.1. Sequencing was performed on an Illumina Novaseq6000 platform to generate 150 bp paired end reads. For ATAC seq nuclei were isolated and washed according to the methods supplied by 10x Genomics. Libraries were prepared using the Chromium Chip E Single Cell Kit and Chromium Single Cell ATAC Library & Gel Bead Kit and further sequenced on an Illumina Novaseq6000 platform to generate 50 bp paired end reads. For 10x Genomics based scRNA seq in mice libraries were prepared using Single Cell three prime Library and Gel Bead Kit V3.1. Sequencing was performed on an Illumina Novaseq6000 platform to generate 150 bp paired end reads. For STRT seq in zebrafish the end repair and dA tailing of the DNA fragments and ligation of the adaptors to the DNA fragments were performed according to the KAPA Hyper Prep Kits with PCR Library Amplification/Illumina series. post the adaptor ligation step the final PCR was performed. The libraries were sequenced on an Illumina Novaseq6000 platform to generate 150 bp paired end reads. For bulk CUT&TAG libraries were prepared according to Hyperactive In Situ ChIP Library Prep Kit for Illumina and sequenced on an Illumina NovaSeq6000 platform to generate 150 bp paired end reads.", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP342737", null, null, "36hpf-DP1_FKDL202627688-1a_1.raw.fq.gz 36hpf-DP1_FKDL202627688-1a_2.raw.fq.gz", "fastq fastq", 36641999100.0, 122139997.0, "GSM7083138 r1", "0:150 1:150", "A:11840633171;C:5285812067;G:6638992204;T:12876249105;N:312553", 150, 150, null, null, 11840633171, 5285812067, 6638992204, 12876249105, 312553, "SRX19578259", "SRS16961241", "SRA1600575", "Group of Hematopoiesis and Cardiovascular Development, INSTITUTE OF ZOOLOGY, CHINESE ACADEMY OF SCIENCES", "Group of Hematopoiesis and Cardiovascular Development, INSTITUTE OF ZOOLOGY, CHINESE ACADEMY OF SCIENCES", 2, 0.8912, 0.01571, 0.09673, 0.00653, 0.86145, 0.99849, 0.61834, 0.72033, 150, 150, "B", "T", "mate2 technical by mapping diff", "illumina", "novaseq_era", "unknown", "poly_a", "unknown", "sc", "single_cell_droplet", "10x", null, "China", "2023-03-06", "Pharyngula", "Embryo", "Trunk", "Surface Structure"], [66758, "SRR23717091", "SRX19578258", "SRS16961240", "SRP342737", "PRJNA773778", "Activation of lineage competence in hemogenic endothelium precedes the formation of hematopoietic stem cell heterogeneity [Zebrafish.STRT seq]", "GSE186425", "Other", "Using a combination of single cell multi omics lineage tracing and functional assays we show that embryonic HSPCs are originated from heterogeneous hemogenic endothelial cells HECs during zebrafish embryogenesis. Overall design: Hematopoietic stem and progenitor cells HSPCs are considered as a heterogeneous population but where and how HSPC heterogeneity occurs remain unclear. Here we performed scRNA seq and scATAC seq with zebrafish 36 hpf VDA derived kdrl+runx1 kdrl+runx1+ and kdrl runx1+ cells. To determine the transcriptional signatures of spi2+ lineages in zebrafish we performed STRT seq with spi2: Gal4;UAS:GFP+ kdrl:mCherry+ HECs and spi2: Gal4;UAS:GFP+ kdrl:mCherry hematopoietic cells at 36 hpf. To investigate the underlying molecular mechanism upon spi2 deficiency we performed scRNA seq with the sorted ECs kdrl+runx1 HECs kdrl+runx1+ and hematopoietic cells kdrl runx1+ from spi2 morphants at 36 hpf. To determine whether spi2 can directly modulate transcriptional programs in EC/HEC we examined genome wide spi2 binding by cut tag assay in fli1a flag spi2 EGFP+ cells sorted from trunk region of Tg fli1a flag spi2 GFP embryos at 36 hpf.", "parent bioproject:PRJNA773771", "pubmed:37016019", null, "DP2 36hpf", "GSM7083139", null, "source name:Zebrafish trunk region|tissue:Zebrafish trunk region 36hpf|cells:single spi2: Gal4;UAS:GFP+ kdrl:mCherry+ HECs and spi2: Gal4;UAS:GFP+ kdrl:mCherry hematopoietic cells|Stage:36 hpf loc name:missing|collection date:missing", "DP2 36hpf", "For scRNA seq and scATAC seq based on 10x Genomics\uff0craw data files were processed by Cell Ranger software suite with default mapping parameters using the GRCz11 reference genome. For STRT seq raw reads were first de multiplexed by barcode sequences in reads 2 to yield separate read files for individual cells then the transcripts sequences of each cell in reads 1 were separated based on corresponding reads 2. Simultaneously UMI sequences in reads 2 were integrated into reads 1. The template switching oligo TSO sequence polyA sequence and the low quality reads N > 10% in reads 1 were subsequently removed by Python scripts and Trimmomatic version 0.36. Next the clean reads were aligned to the zebrafish genome GRCz11 from Ensembl using HISAT2 version 2.1.0 with known gene annotation. Only protein coding genes were retained and the abundance of each gene were estimated by counting the reads that duplicated UMIs have been excluded. For cut&tag reads were aligned to GRCz11 by Bowtie2. Only uniquely mapped reads with mapping quality score\u00a0\u2265 30 were kept using Samtools software. post merging replicates MACS2 was used for the peak calling. Assembly: GRCz11 Library strategy: STRT seq", "Zebrafish trunk region", null, "For 10x Genomics based scRNA seq and scATAC seq in zebrafish 40 000 mCherry+ GFP cells 40 000 mCherry+ GFP+ cells and 30 000 mCherry GFP+ cells were sorted from Tg kdrl:mCherry/runx1:enGFP at 36 hpf. For STRT seq in zebrafish single spi2: Gal4;UAS:GFP+ kdrl:mCherry+ HECs and spi2: Gal4;UAS:GFP+ kdrl:mCherry hematopoietic cells were sorted from the trunk region of Tg spi2: Gal4;UAS:GFP/ kdrl:mCherry at 36 hpf. For scRNA seq of spi2 morphants at 36 hpf in zebrafish ECs kdrl+runx1 HECs kdrl+runx1+ and hematopoietic cells kdrl runx1+ were sorted. For bulk CUT&TAG in zebrafish fli1a flag spi2 EGFP+ cells were sorted from the trunk region of Tg fli1a flag spi2 GFP embryos at 36 hpf. For 10x Genomics based scRNA seq and scATAC seq in zebrafish we loaded 20 000 cells for further 10x Genomics based scRNA seq and 90 000 cells for further 10x Genomics based scATAC seq. For scRNA seq libraries were prepared using Single Cell 3\u2019 Library and Gel Bead Kit V3.1. Sequencing was performed on an Illumina Novaseq6000 platform to generate 150 bp paired end reads. For ATAC seq nuclei were isolated and washed according to the methods supplied by 10x Genomics. Libraries were prepared using the Chromium Chip E Single Cell Kit and Chromium Single Cell ATAC Library & Gel Bead Kit and further sequenced on an Illumina Novaseq6000 platform to generate 50 bp paired end reads. For 10x Genomics based scRNA seq in mice libraries were prepared using Single Cell 3\u2019 Library and Gel Bead Kit V3.1. Sequencing was performed on an Illumina Novaseq6000 platform to generate 150 bp paired end reads. For STRT seq in zebrafish the end repair and dA tailing of the DNA fragments and ligation of the adaptors to the DNA fragments were performed according to the KAPA Hyper Prep Kits with PCR Library Amplification/Illumina series. post the adaptor ligation step the final PCR was performed. The libraries were sequenced on an Illumina Novaseq6000 platform to generate 150 bp paired end reads. For bulk CUT&TAG libraries were prepared according to Hyperactive In Situ ChIP Library Prep Kit for Illumina and sequenced on an Illumina NovaSeq6000 platform to generate 150 bp paired end reads.", null, "tissue:Zebrafish trunk region 36hpf|cells:single spi2: Gal4;UAS:GFP+ kdrl:mCherry+ HECs and spi2: Gal4;UAS:GFP+ kdrl:mCherry hematopoietic cells|Stage:36 hpf", "GSM7083139", "GSM7083139: DP2 36hpf; Danio rerio; OTHER", "GSM7083139 r1", "GSM7083139", "1", "For 10x Genomics based scRNA seq and scATAC seq in zebrafish 40 000 mCherry+ GFP cells 40 000 mCherry+ GFP+ cells and 30 000 mCherry GFP+ cells were sorted from Tg kdrl:mCherry/runx1:enGFP at 36 hpf. For STRT seq in zebrafish single spi2: Gal4;UAS:GFP+ kdrl:mCherry+ HECs and spi2: Gal4;UAS:GFP+ kdrl:mCherry hematopoietic cells were sorted from the trunk region of Tg spi2: Gal4;UAS:GFP/ kdrl:mCherry at 36 hpf. For scRNA seq of spi2 morphants at 36 hpf in zebrafish ECs kdrl+runx1 HECs kdrl+runx1+ and hematopoietic cells kdrl runx1+ were sorted. For bulk CUT&TAG in zebrafish fli1a flag spi2 EGFP+ cells were sorted from the trunk region of Tg fli1a flag spi2 GFP embryos at 36 hpf. For 10x Genomics based scRNA seq and scATAC seq in zebrafish we loaded 20 000 cells for further 10x Genomics based scRNA seq and 90 000 cells for further 10x Genomics based scATAC seq. For scRNA seq libraries were prepared using Single Cell three prime Library and Gel Bead Kit V3.1. Sequencing was performed on an Illumina Novaseq6000 platform to generate 150 bp paired end reads. For ATAC seq nuclei were isolated and washed according to the methods supplied by 10x Genomics. Libraries were prepared using the Chromium Chip E Single Cell Kit and Chromium Single Cell ATAC Library & Gel Bead Kit and further sequenced on an Illumina Novaseq6000 platform to generate 50 bp paired end reads. For 10x Genomics based scRNA seq in mice libraries were prepared using Single Cell three prime Library and Gel Bead Kit V3.1. Sequencing was performed on an Illumina Novaseq6000 platform to generate 150 bp paired end reads. For STRT seq in zebrafish the end repair and dA tailing of the DNA fragments and ligation of the adaptors to the DNA fragments were performed according to the KAPA Hyper Prep Kits with PCR Library Amplification/Illumina series. post the adaptor ligation step the final PCR was performed. The libraries were sequenced on an Illumina Novaseq6000 platform to generate 150 bp paired end reads. For bulk CUT&TAG libraries were prepared according to Hyperactive In Situ ChIP Library Prep Kit for Illumina and sequenced on an Illumina NovaSeq6000 platform to generate 150 bp paired end reads.", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP342737", null, null, "36hpf-DP2_FKDL202627692-1a_1.raw.fq.gz 36hpf-DP2_FKDL202627692-1a_2.raw.fq.gz", "fastq fastq", 45339599100.0, 151131997.0, "GSM7083139 r1", "0:150 1:150", "A:14092451998;C:7125629842;G:9985822921;T:14135305628;N:388711", 150, 150, null, null, 14092451998, 7125629842, 9985822921, 14135305628, 388711, "SRX19578258", "SRS16961240", "SRA1600575", "Group of Hematopoiesis and Cardiovascular Development, INSTITUTE OF ZOOLOGY, CHINESE ACADEMY OF SCIENCES", "Group of Hematopoiesis and Cardiovascular Development, INSTITUTE OF ZOOLOGY, CHINESE ACADEMY OF SCIENCES", 2, 0.79702, 0.00323, 0.08737, 0.00105, 0.88663, 0.99882, 0.62618, 0.6, 150, 150, "B", "T", "mate2 technical by mapping diff", "illumina", "novaseq_era", "unknown", "poly_a", "unknown", "sc", "single_cell_droplet", "10x", null, "China", "2023-03-06", "Pharyngula", "Embryo", "Trunk", "Surface Structure"], [66759, "SRR23717092", "SRX19578257", "SRS16961239", "SRP342737", "PRJNA773778", "Activation of lineage competence in hemogenic endothelium precedes the formation of hematopoietic stem cell heterogeneity [Zebrafish.STRT seq]", "GSE186425", "Other", "Using a combination of single cell multi omics lineage tracing and functional assays we show that embryonic HSPCs are originated from heterogeneous hemogenic endothelial cells HECs during zebrafish embryogenesis. Overall design: Hematopoietic stem and progenitor cells HSPCs are considered as a heterogeneous population but where and how HSPC heterogeneity occurs remain unclear. Here we performed scRNA seq and scATAC seq with zebrafish 36 hpf VDA derived kdrl+runx1 kdrl+runx1+ and kdrl runx1+ cells. To determine the transcriptional signatures of spi2+ lineages in zebrafish we performed STRT seq with spi2: Gal4;UAS:GFP+ kdrl:mCherry+ HECs and spi2: Gal4;UAS:GFP+ kdrl:mCherry hematopoietic cells at 36 hpf. To investigate the underlying molecular mechanism upon spi2 deficiency we performed scRNA seq with the sorted ECs kdrl+runx1 HECs kdrl+runx1+ and hematopoietic cells kdrl runx1+ from spi2 morphants at 36 hpf. To determine whether spi2 can directly modulate transcriptional programs in EC/HEC we examined genome wide spi2 binding by cut tag assay in fli1a flag spi2 EGFP+ cells sorted from trunk region of Tg fli1a flag spi2 GFP embryos at 36 hpf.", "parent bioproject:PRJNA773771", "pubmed:37016019", null, "SP 36hpf", "GSM7083140", null, "source name:Zebrafish trunk region|tissue:Zebrafish trunk region 36hpf|cells:single spi2: Gal4;UAS:GFP+ kdrl:mCherry+ HECs and spi2: Gal4;UAS:GFP+ kdrl:mCherry hematopoietic cells|Stage:36 hpf loc name:missing|collection date:missing", "SP 36hpf", "For scRNA seq and scATAC seq based on 10x Genomics\uff0craw data files were processed by Cell Ranger software suite with default mapping parameters using the GRCz11 reference genome. For STRT seq raw reads were first de multiplexed by barcode sequences in reads 2 to yield separate read files for individual cells then the transcripts sequences of each cell in reads 1 were separated based on corresponding reads 2. Simultaneously UMI sequences in reads 2 were integrated into reads 1. The template switching oligo TSO sequence polyA sequence and the low quality reads N > 10% in reads 1 were subsequently removed by Python scripts and Trimmomatic version 0.36. Next the clean reads were aligned to the zebrafish genome GRCz11 from Ensembl using HISAT2 version 2.1.0 with known gene annotation. Only protein coding genes were retained and the abundance of each gene were estimated by counting the reads that duplicated UMIs have been excluded. For cut&tag reads were aligned to GRCz11 by Bowtie2. Only uniquely mapped reads with mapping quality score\u00a0\u2265 30 were kept using Samtools software. post merging replicates MACS2 was used for the peak calling. Assembly: GRCz11 Library strategy: STRT seq", "Zebrafish trunk region", null, "For 10x Genomics based scRNA seq and scATAC seq in zebrafish 40 000 mCherry+ GFP cells 40 000 mCherry+ GFP+ cells and 30 000 mCherry GFP+ cells were sorted from Tg kdrl:mCherry/runx1:enGFP at 36 hpf. For STRT seq in zebrafish single spi2: Gal4;UAS:GFP+ kdrl:mCherry+ HECs and spi2: Gal4;UAS:GFP+ kdrl:mCherry hematopoietic cells were sorted from the trunk region of Tg spi2: Gal4;UAS:GFP/ kdrl:mCherry at 36 hpf. For scRNA seq of spi2 morphants at 36 hpf in zebrafish ECs kdrl+runx1 HECs kdrl+runx1+ and hematopoietic cells kdrl runx1+ were sorted. For bulk CUT&TAG in zebrafish fli1a flag spi2 EGFP+ cells were sorted from the trunk region of Tg fli1a flag spi2 GFP embryos at 36 hpf. For 10x Genomics based scRNA seq and scATAC seq in zebrafish we loaded 20 000 cells for further 10x Genomics based scRNA seq and 90 000 cells for further 10x Genomics based scATAC seq. For scRNA seq libraries were prepared using Single Cell 3\u2019 Library and Gel Bead Kit V3.1. Sequencing was performed on an Illumina Novaseq6000 platform to generate 150 bp paired end reads. For ATAC seq nuclei were isolated and washed according to the methods supplied by 10x Genomics. Libraries were prepared using the Chromium Chip E Single Cell Kit and Chromium Single Cell ATAC Library & Gel Bead Kit and further sequenced on an Illumina Novaseq6000 platform to generate 50 bp paired end reads. For 10x Genomics based scRNA seq in mice libraries were prepared using Single Cell 3\u2019 Library and Gel Bead Kit V3.1. Sequencing was performed on an Illumina Novaseq6000 platform to generate 150 bp paired end reads. For STRT seq in zebrafish the end repair and dA tailing of the DNA fragments and ligation of the adaptors to the DNA fragments were performed according to the KAPA Hyper Prep Kits with PCR Library Amplification/Illumina series. post the adaptor ligation step the final PCR was performed. The libraries were sequenced on an Illumina Novaseq6000 platform to generate 150 bp paired end reads. For bulk CUT&TAG libraries were prepared according to Hyperactive In Situ ChIP Library Prep Kit for Illumina and sequenced on an Illumina NovaSeq6000 platform to generate 150 bp paired end reads.", null, "tissue:Zebrafish trunk region 36hpf|cells:single spi2: Gal4;UAS:GFP+ kdrl:mCherry+ HECs and spi2: Gal4;UAS:GFP+ kdrl:mCherry hematopoietic cells|Stage:36 hpf", "GSM7083140", "GSM7083140: SP 36hpf; Danio rerio; OTHER", "GSM7083140 r1", "GSM7083140", "1", "For 10x Genomics based scRNA seq and scATAC seq in zebrafish 40 000 mCherry+ GFP cells 40 000 mCherry+ GFP+ cells and 30 000 mCherry GFP+ cells were sorted from Tg kdrl:mCherry/runx1:enGFP at 36 hpf. For STRT seq in zebrafish single spi2: Gal4;UAS:GFP+ kdrl:mCherry+ HECs and spi2: Gal4;UAS:GFP+ kdrl:mCherry hematopoietic cells were sorted from the trunk region of Tg spi2: Gal4;UAS:GFP/ kdrl:mCherry at 36 hpf. For scRNA seq of spi2 morphants at 36 hpf in zebrafish ECs kdrl+runx1 HECs kdrl+runx1+ and hematopoietic cells kdrl runx1+ were sorted. For bulk CUT&TAG in zebrafish fli1a flag spi2 EGFP+ cells were sorted from the trunk region of Tg fli1a flag spi2 GFP embryos at 36 hpf. For 10x Genomics based scRNA seq and scATAC seq in zebrafish we loaded 20 000 cells for further 10x Genomics based scRNA seq and 90 000 cells for further 10x Genomics based scATAC seq. For scRNA seq libraries were prepared using Single Cell three prime Library and Gel Bead Kit V3.1. Sequencing was performed on an Illumina Novaseq6000 platform to generate 150 bp paired end reads. For ATAC seq nuclei were isolated and washed according to the methods supplied by 10x Genomics. Libraries were prepared using the Chromium Chip E Single Cell Kit and Chromium Single Cell ATAC Library & Gel Bead Kit and further sequenced on an Illumina Novaseq6000 platform to generate 50 bp paired end reads. For 10x Genomics based scRNA seq in mice libraries were prepared using Single Cell three prime Library and Gel Bead Kit V3.1. Sequencing was performed on an Illumina Novaseq6000 platform to generate 150 bp paired end reads. For STRT seq in zebrafish the end repair and dA tailing of the DNA fragments and ligation of the adaptors to the DNA fragments were performed according to the KAPA Hyper Prep Kits with PCR Library Amplification/Illumina series. post the adaptor ligation step the final PCR was performed. The libraries were sequenced on an Illumina Novaseq6000 platform to generate 150 bp paired end reads. For bulk CUT&TAG libraries were prepared according to Hyperactive In Situ ChIP Library Prep Kit for Illumina and sequenced on an Illumina NovaSeq6000 platform to generate 150 bp paired end reads.", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP342737", null, null, "36hpf-SP_FKDL202627693-1a_1.raw.fq.gz 36hpf-SP_FKDL202627693-1a_2.raw.fq.gz", "fastq fastq", 44757872400.0, 149192908.0, "GSM7083140 r1", "0:150 1:150", "A:13194662551;C:6817138207;G:9879151250;T:14866177703;N:742689", 150, 150, null, null, 13194662551, 6817138207, 9879151250, 14866177703, 742689, "SRX19578257", "SRS16961239", "SRA1600575", "Group of Hematopoiesis and Cardiovascular Development, INSTITUTE OF ZOOLOGY, CHINESE ACADEMY OF SCIENCES", "Group of Hematopoiesis and Cardiovascular Development, INSTITUTE OF ZOOLOGY, CHINESE ACADEMY OF SCIENCES", 2, 0.7854, 0.00221, 0.062, 0.00084, 0.90995, 0.99904, 0.43661, 0.67741, 150, 150, "B", "T", "mate2 technical by mapping diff", "illumina", "novaseq_era", "unknown", "poly_a", "unknown", "sc", "single_cell_droplet", "10x", null, "China", "2023-03-06", "Pharyngula", "Embryo", "Trunk", "Surface Structure"], [70967, "SRR21007395", "SRX17024129", "SRS14609022", "SRP390913", "PRJNA868351", "Hematopoietic stem and progenitor cell heterogeneity is inherited from the embryonic hemogenic endothelium [scRNA seq]", "GSE210941", "Transcriptome Analysis", "Investigate the role of miR128 in the EHT process and the formation of nHSPCs Overall design: Comparative gene expression analysis of RNA seq data for WT and MT samples for miRNA128 in Human and Fish", "parent bioproject:PRJNA868347", "pubmed:37460694", null, "gRNA jag1 26HPF scRNAseq", "GSM6443156", null, "source name:trunk tissue containing the AGM|cell type:Endothelial Cells|tissue:trunk tissue containing the AGM|strain:Tgkdrl:GFP zn1|age:26HPF|geo loc name:missing|collection date:missing", "gRNA jag1 26HPF scRNAseq", "The barcoded processing gene counting and aggregation were made using the Cell Ranger software Version 5.0.0 Downstream analysis were performed on R studio using Seurat Assembly: Lawson Annotation V4.3.2 Supplementary files format and content: Tab separated values files and matrix files", "trunk tissue containing the AGM", null, "Wild type miR 128\u0394/\u0394 csnk1a1 and jag1b g3\u2019UTR mutants Tgkdrl:GFP zn1 trunk tissue containing the AGM were dissected at 26 hpf. Dissected trunk tissues were dissociated into single cell suspensions and subjected to FACS. GFP+ cells which had 85% cell viability were loaded onto the 10X Genomics Chromium instrument for a targeted recovery of 10 000 cells per sample 10X Genomics Chromium Next GEM Single Cell 3\u2019 Library Construction Kit V3.1 CG000204 was used to generate libraires according to manufacturer intructions", null, "cell type:Endothelial Cells|tissue:trunk tissue containing the AGM|strain:Tgkdrl:GFP zn1|age:26HPF", "GSM6443156", "GSM6443156: gRNA jag1 26HPF scRNAseq; Danio rerio; RNA Seq", "GSM6443156 r1", "GSM6443156", "1", "Wild type miR 128\u0394/\u0394 csnk1a1 and jag1b gthree primeUTR mutants Tgkdrl:GFP zn1 trunk tissue containing the AGM were dissected at 26 hpf. Dissected trunk tissues were dissociated into single cell suspensions and subjected to FACS. 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Dissected trunk tissues were dissociated into single cell suspensions and subjected to FACS. GFP+ cells which had 85% cell viability were loaded onto the 10X Genomics Chromium instrument for a targeted recovery of 10 000 cells per sample 10X Genomics Chromium Next GEM Single Cell 3\u2019 Library Construction Kit V3.1 CG000204 was used to generate libraires according to manufacturer intructions", null, "cell type:Endothelial Cells|tissue:trunk tissue containing the AGM|strain:Tgkdrl:GFP zn1|age:26HPF", "GSM6443156", "GSM6443156: gRNA jag1 26HPF scRNAseq; Danio rerio; RNA Seq", "GSM6443156 r1", "GSM6443156", "1", "Wild type miR 128\u0394/\u0394 csnk1a1 and jag1b gthree primeUTR mutants Tgkdrl:GFP zn1 trunk tissue containing the AGM were dissected at 26 hpf. Dissected trunk tissues were dissociated into single cell suspensions and subjected to FACS. GFP+ cells which had 85% cell viability were loaded onto the 10X Genomics Chromium instrument for a targeted recovery of 10 000 cells per sample 10X Genomics Chromium Next GEM Single Cell three prime Library Construction Kit V3.1 CG000204 was used to generate libraires according to manufacturer intructions", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina HiSeq 4000", null, "SRP390913", null, "loader:fastq load.py|options: readTypes=TBB read1PairFiles=jag1b DRT S3 L004 I1 001.fastq.gz read2PairFiles=jag1b DRT S3 L004 R1 001.fastq.gz read3PairFiles=jag1b DRT S3 L004 R2 001.fastq.gz", "jag1b_DRT_S3_L004_I1_001.fastq.gz jag1b_DRT_S3_L004_R1_001.fastq.gz jag1b_DRT_S3_L004_R2_001.fastq.gz", "fastq fastq fastq", 16084657188.0, 126650844.0, "GSM6443156 r2", "0:8 1:28 2:91", "A:4267990504;C:3319270032;G:3579390545;T:3904256142;N:543213", 8, 28, 91, null, 4267990504, 3319270032, 3579390545, 3904256142, 543213, "SRX17024129", "SRS14609022", "SRA1473366", "Nicoli Lab, Genetics/Internal Medicine, Yale University", "Nicoli Lab, Genetics/Internal Medicine, Yale University", 2, 0.00747, 0.8896, 0.00283, 0.21781, 0.98778, 0.79263, 0.36736, 0.53802, 28, 91, "T", "B", "sc-like readlen", "illumina", "hiseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2022-08-10", "Pharyngula", "Embryo", "Trunk", "Surface Structure"], [70969, "SRR21007397", "SRX17024128", "SRS14609021", "SRP390913", "PRJNA868351", "Hematopoietic stem and progenitor cell heterogeneity is inherited from the embryonic hemogenic endothelium [scRNA seq]", "GSE210941", "Transcriptome Analysis", "Investigate the role of miR128 in the EHT process and the formation of nHSPCs Overall design: Comparative gene expression analysis of RNA seq data for WT and MT samples for miRNA128 in Human and Fish", "parent bioproject:PRJNA868347", "pubmed:37460694", null, "gRNA csnk1 26HPF scRNAseq", "GSM6443155", null, "source name:trunk tissue containing the AGM|cell type:Endothelial Cells|tissue:trunk tissue containing the AGM|strain:Tgkdrl:GFP zn1|age:26HPF|geo loc name:missing|collection date:missing", "gRNA csnk1 26HPF scRNAseq", "The barcoded processing gene counting and aggregation were made using the Cell Ranger software Version 5.0.0 Downstream analysis were performed on R studio using Seurat Assembly: Lawson Annotation V4.3.2 Supplementary files format and content: Tab separated values files and matrix files", "trunk tissue containing the AGM", null, "Wild type miR 128\u0394/\u0394 csnk1a1 and jag1b g3\u2019UTR mutants Tgkdrl:GFP zn1 trunk tissue containing the AGM were dissected at 26 hpf. Dissected trunk tissues were dissociated into single cell suspensions and subjected to FACS. GFP+ cells which had 85% cell viability were loaded onto the 10X Genomics Chromium instrument for a targeted recovery of 10 000 cells per sample 10X Genomics Chromium Next GEM Single Cell 3\u2019 Library Construction Kit V3.1 CG000204 was used to generate libraires according to manufacturer intructions", null, "cell type:Endothelial Cells|tissue:trunk tissue containing the AGM|strain:Tgkdrl:GFP zn1|age:26HPF", "GSM6443155", "GSM6443155: gRNA csnk1 26HPF scRNAseq; Danio rerio; RNA Seq", "GSM6443155 r1", "GSM6443155", "1", "Wild type miR 128\u0394/\u0394 csnk1a1 and jag1b gthree primeUTR mutants Tgkdrl:GFP zn1 trunk tissue containing the AGM were dissected at 26 hpf. Dissected trunk tissues were dissociated into single cell suspensions and subjected to FACS. GFP+ cells which had 85% cell viability were loaded onto the 10X Genomics Chromium instrument for a targeted recovery of 10 000 cells per sample 10X Genomics Chromium Next GEM Single Cell three prime Library Construction Kit V3.1 CG000204 was used to generate libraires according to manufacturer intructions", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina HiSeq 4000", null, "SRP390913", null, "loader:fastq load.py|options: readTypes=TBB read1PairFiles=csnk1a DRT S2 L003 I1 001.fastq.gz read2PairFiles=csnk1a DRT S2 L003 R1 001.fastq.gz read3PairFiles=csnk1a DRT S2 L003 R2 001.fastq.gz", "csnk1a_DRT_S2_L003_I1_001.fastq.gz csnk1a_DRT_S2_L003_R1_001.fastq.gz csnk1a_DRT_S2_L003_R2_001.fastq.gz", "fastq fastq fastq", 17585727973.0, 138470299.0, "GSM6443155 r1", "0:8 1:28 2:91", "A:4685099762;C:3662694223;G:3795199750;T:4334481609;N:490237", 8, 28, 91, null, 4685099762, 3662694223, 3795199750, 4334481609, 490237, "SRX17024128", "SRS14609021", "SRA1473366", "Nicoli Lab, Genetics/Internal Medicine, Yale University", "Nicoli Lab, Genetics/Internal Medicine, Yale University", 2, 0.01126, 0.9112, 0.00402, 0.18979, 0.98137, 0.7838, 0.32952, 0.50602, 28, 91, "T", "B", "sc-like readlen", "illumina", "hiseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2022-08-10", "Pharyngula", "Embryo", "Trunk", "Surface Structure"], [70970, "SRR21007398", "SRX17024128", "SRS14609021", "SRP390913", "PRJNA868351", "Hematopoietic stem and progenitor cell heterogeneity is inherited from the embryonic hemogenic endothelium [scRNA seq]", "GSE210941", "Transcriptome Analysis", "Investigate the role of miR128 in the EHT process and the formation of nHSPCs Overall design: Comparative gene expression analysis of RNA seq data for WT and MT samples for miRNA128 in Human and Fish", "parent bioproject:PRJNA868347", "pubmed:37460694", null, "gRNA csnk1 26HPF scRNAseq", "GSM6443155", null, "source name:trunk tissue containing the AGM|cell type:Endothelial Cells|tissue:trunk tissue containing the AGM|strain:Tgkdrl:GFP zn1|age:26HPF|geo loc name:missing|collection date:missing", "gRNA csnk1 26HPF scRNAseq", "The barcoded processing gene counting and aggregation were made using the Cell Ranger software Version 5.0.0 Downstream analysis were performed on R studio using Seurat Assembly: Lawson Annotation V4.3.2 Supplementary files format and content: Tab separated values files and matrix files", "trunk tissue containing the AGM", null, "Wild type miR 128\u0394/\u0394 csnk1a1 and jag1b g3\u2019UTR mutants Tgkdrl:GFP zn1 trunk tissue containing the AGM were dissected at 26 hpf. Dissected trunk tissues were dissociated into single cell suspensions and subjected to FACS. GFP+ cells which had 85% cell viability were loaded onto the 10X Genomics Chromium instrument for a targeted recovery of 10 000 cells per sample 10X Genomics Chromium Next GEM Single Cell 3\u2019 Library Construction Kit V3.1 CG000204 was used to generate libraires according to manufacturer intructions", null, "cell type:Endothelial Cells|tissue:trunk tissue containing the AGM|strain:Tgkdrl:GFP zn1|age:26HPF", "GSM6443155", "GSM6443155: gRNA csnk1 26HPF scRNAseq; Danio rerio; RNA Seq", "GSM6443155 r1", "GSM6443155", "1", "Wild type miR 128\u0394/\u0394 csnk1a1 and jag1b gthree primeUTR mutants Tgkdrl:GFP zn1 trunk tissue containing the AGM were dissected at 26 hpf. Dissected trunk tissues were dissociated into single cell suspensions and subjected to FACS. GFP+ cells which had 85% cell viability were loaded onto the 10X Genomics Chromium instrument for a targeted recovery of 10 000 cells per sample 10X Genomics Chromium Next GEM Single Cell three prime Library Construction Kit V3.1 CG000204 was used to generate libraires according to manufacturer intructions", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina HiSeq 4000", null, "SRP390913", null, "loader:fastq load.py|options: readTypes=TBB read1PairFiles=csnk1a DRT S2 L004 I1 001.fastq.gz read2PairFiles=csnk1a DRT S2 L004 R1 001.fastq.gz read3PairFiles=csnk1a DRT S2 L004 R2 001.fastq.gz", "csnk1a_DRT_S2_L004_I1_001.fastq.gz csnk1a_DRT_S2_L004_R1_001.fastq.gz csnk1a_DRT_S2_L004_R2_001.fastq.gz", "fastq fastq fastq", 17642162328.0, 138914664.0, "GSM6443155 r2", "0:8 1:28 2:91", "A:4700864535;C:3672134070;G:3805292893;T:4351958835;N:594683", 8, 28, 91, null, 4700864535, 3672134070, 3805292893, 4351958835, 594683, "SRX17024128", "SRS14609021", "SRA1473366", "Nicoli Lab, Genetics/Internal Medicine, Yale University", "Nicoli Lab, Genetics/Internal Medicine, Yale University", 2, 0.01083, 0.91228, 0.00389, 0.19017, 0.98175, 0.78413, 0.34007, 0.51895, 28, 91, "T", "B", "sc-like readlen", "illumina", "hiseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2022-08-10", "Pharyngula", "Embryo", "Trunk", "Surface Structure"], [70971, "SRR21007399", "SRX17024127", "SRS14609020", "SRP390913", "PRJNA868351", "Hematopoietic stem and progenitor cell heterogeneity is inherited from the embryonic hemogenic endothelium [scRNA seq]", "GSE210941", "Transcriptome Analysis", "Investigate the role of miR128 in the EHT process and the formation of nHSPCs Overall design: Comparative gene expression analysis of RNA seq data for WT and MT samples for miRNA128 in Human and Fish", "parent bioproject:PRJNA868347", "pubmed:37460694", null, "MT 26HPF scRNAseq", "GSM6443154", null, "source name:trunk tissue containing the AGM|cell type:Endothelial Cells|tissue:trunk tissue containing the AGM|strain:Tgkdrl:GFP zn1|age:26HPF|geo loc name:missing|collection date:missing", "MT 26HPF scRNAseq", "The barcoded processing gene counting and aggregation were made using the Cell Ranger software Version 5.0.0 Downstream analysis were performed on R studio using Seurat Assembly: Lawson Annotation V4.3.2 Supplementary files format and content: Tab separated values files and matrix files", "trunk tissue containing the AGM", null, "Wild type miR 128\u0394/\u0394 csnk1a1 and jag1b g3\u2019UTR mutants Tgkdrl:GFP zn1 trunk tissue containing the AGM were dissected at 26 hpf. Dissected trunk tissues were dissociated into single cell suspensions and subjected to FACS. GFP+ cells which had 85% cell viability were loaded onto the 10X Genomics Chromium instrument for a targeted recovery of 10 000 cells per sample 10X Genomics Chromium Next GEM Single Cell 3\u2019 Library Construction Kit V3.1 CG000204 was used to generate libraires according to manufacturer intructions", null, "cell type:Endothelial Cells|tissue:trunk tissue containing the AGM|strain:Tgkdrl:GFP zn1|age:26HPF", "GSM6443154", "GSM6443154: MT 26HPF scRNAseq; Danio rerio; RNA Seq", "GSM6443154 r1", "GSM6443154", "1", "Wild type miR 128\u0394/\u0394 csnk1a1 and jag1b gthree primeUTR mutants Tgkdrl:GFP zn1 trunk tissue containing the AGM were dissected at 26 hpf. Dissected trunk tissues were dissociated into single cell suspensions and subjected to FACS. GFP+ cells which had 85% cell viability were loaded onto the 10X Genomics Chromium instrument for a targeted recovery of 10 000 cells per sample 10X Genomics Chromium Next GEM Single Cell three prime Library Construction Kit V3.1 CG000204 was used to generate libraires according to manufacturer intructions", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina HiSeq 4000", null, "SRP390913", null, "loader:fastq load.py|options: readTypes=TBB read1PairFiles=MT DRT S2 L004 I1 001.fastq.gz read2PairFiles=MT DRT S2 L004 R1 001.fastq.gz read3PairFiles=MT DRT S2 L004 R2 001.fastq.gz", "MT_DRT_S2_L004_I1_001.fastq.gz MT_DRT_S2_L004_R1_001.fastq.gz MT_DRT_S2_L004_R2_001.fastq.gz", "fastq fastq fastq", 44640313691.0, 351498533.0, "GSM6443154 r1", "0:8 1:28 2:91", "A:11802470987;C:9130307392;G:9708029949;T:11186763112;N:753987", 8, 28, 91, null, 11802470987, 9130307392, 9708029949, 11186763112, 753987, "SRX17024127", "SRS14609020", "SRA1473366", "Nicoli Lab, Genetics/Internal Medicine, Yale University", "Nicoli Lab, Genetics/Internal Medicine, Yale University", 2, 0.01069, 0.92492, 0.00314, 0.17525, 0.98338, 0.79586, 0.42895, 0.5135, 28, 91, "T", "B", "sc-like readlen", "illumina", "hiseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2022-08-10", "Pharyngula", "Embryo", "Trunk", "Surface Structure"], [70972, "SRR21007400", "SRX17024126", "SRS14609019", "SRP390913", "PRJNA868351", "Hematopoietic stem and progenitor cell heterogeneity is inherited from the embryonic hemogenic endothelium [scRNA seq]", "GSE210941", "Transcriptome Analysis", "Investigate the role of miR128 in the EHT process and the formation of nHSPCs Overall design: Comparative gene expression analysis of RNA seq data for WT and MT samples for miRNA128 in Human and Fish", "parent bioproject:PRJNA868347", "pubmed:37460694", null, "WT 26HPF scRNAseq", "GSM6443153", null, "source name:trunk tissue containing the AGM|cell type:Endothelial Cells|tissue:trunk tissue containing the AGM|strain:Tgkdrl:GFP zn1|age:26HPF|geo loc name:missing|collection date:missing", "WT 26HPF scRNAseq", "The barcoded processing gene counting and aggregation were made using the Cell Ranger software Version 5.0.0 Downstream analysis were performed on R studio using Seurat Assembly: Lawson Annotation V4.3.2 Supplementary files format and content: Tab separated values files and matrix files", "trunk tissue containing the AGM", null, "Wild type miR 128\u0394/\u0394 csnk1a1 and jag1b g3\u2019UTR mutants Tgkdrl:GFP zn1 trunk tissue containing the AGM were dissected at 26 hpf. Dissected trunk tissues were dissociated into single cell suspensions and subjected to FACS. GFP+ cells which had 85% cell viability were loaded onto the 10X Genomics Chromium instrument for a targeted recovery of 10 000 cells per sample 10X Genomics Chromium Next GEM Single Cell 3\u2019 Library Construction Kit V3.1 CG000204 was used to generate libraires according to manufacturer intructions", null, "cell type:Endothelial Cells|tissue:trunk tissue containing the AGM|strain:Tgkdrl:GFP zn1|age:26HPF", "GSM6443153", "GSM6443153: WT 26HPF scRNAseq; Danio rerio; RNA Seq", "GSM6443153 r1", "GSM6443153", "1", "Wild type miR 128\u0394/\u0394 csnk1a1 and jag1b gthree primeUTR mutants Tgkdrl:GFP zn1 trunk tissue containing the AGM were dissected at 26 hpf. Dissected trunk tissues were dissociated into single cell suspensions and subjected to FACS. GFP+ cells which had 85% cell viability were loaded onto the 10X Genomics Chromium instrument for a targeted recovery of 10 000 cells per sample 10X Genomics Chromium Next GEM Single Cell three prime Library Construction Kit V3.1 CG000204 was used to generate libraires according to manufacturer intructions", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina HiSeq 4000", null, "SRP390913", null, "loader:fastq load.py|options: readTypes=TBB read1PairFiles=WT DRT S1 L004 I1 001.fastq.gz read2PairFiles=WT DRT S1 L004 R1 001.fastq.gz read3PairFiles=WT DRT S1 L004 R2 001.fastq.gz", "WT_DRT_S1_L004_I1_001.fastq.gz WT_DRT_S1_L004_R1_001.fastq.gz WT_DRT_S1_L004_R2_001.fastq.gz", "fastq fastq fastq", 63333837772.0, 498691636.0, "GSM6443153 r1", "0:8 1:28 2:91", "A:16776941902;C:12869180260;G:13716776874;T:15980339022;N:1066626", 8, 28, 91, null, 16776941902, 12869180260, 13716776874, 15980339022, 1066626, "SRX17024126", "SRS14609019", "SRA1473366", "Nicoli Lab, Genetics/Internal Medicine, Yale University", "Nicoli Lab, Genetics/Internal Medicine, Yale University", 2, 0.00896, 0.91613, 0.0026, 0.16276, 0.98466, 0.79279, 0.44896, 0.53257, 28, 91, "T", "B", "sc-like readlen", "illumina", "hiseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2022-08-10", "Pharyngula", "Embryo", "Trunk", "Surface Structure"], [74668, "SRR23928776", "SRX19738955", "SRS17105108", "SRP428413", "PRJNA947108", "Gene expression profile at single cell level of zebrafish trunk from WT or flt1 mutant 3dpf.", "GSE227806", "Transcriptome Analysis", "scRNA seq was used to investigate neurovascular cross talk in zebrafish trunk. Overall design: Zebrafish trunk of WT and flt1 mutant were dissected dissociated and processed for single cell RNA Seq using 10X Genomics Chromium droplet based system", "parent bioproject:PRJNA947103", "pubmed:38600061", null, "flt1mut replicate 2 scRNAseq trunk", "GSM7108419", null, "source name:Trunk|tissue:Trunk|genotype:flt1ka604|age:3dpf|geo loc name:missing|collection date:missing", "flt1mut replicate 2 scRNAseq trunk", "The demultiplexing barcoded processing gene counting and aggregation were made using the Cell Ranger software https://support.10xgenomics.com/single cell gene expression/software/pipelines/latest/what is cell ranger Assembly: GRCZ11 v107 Supplementary files format and content: matrix files", "Trunk", null, "Zebrafish embryos 3dpf were anesthethised with Tricain prior the dissection of the trunk. Dissected trunks were dissociated using a mix of 0.25% Trypsin and collagenase 4mg/mL centrifuged to collect the cells resuspended into DMEM + 10% Fetal Bovine Serum and filtered to remove the debris. Cells were washed and resuspend in PBS prior 10X genomic experiment Library was performed according to the manufacter\u2019s instructions single cell 3\u2019 v2 protocol 10x Genomics", null, "tissue:Trunk|genotype:flt1ka604|age:3dpf", "GSM7108419", "GSM7108419: flt1mut replicate 2 scRNAseq trunk; Danio rerio; RNA Seq", "GSM7108419 r1", "GSM7108419", "1", "Zebrafish embryos 3dpf were anesthethised with Tricain prior the dissection of the trunk. Dissected trunks were dissociated using a mix of 0.25% Trypsin and collagenase 4mg/mL centrifuged to collect the cells resuspended into DMEM + 10% Fetal Bovine Serum and filtered to remove the debris. Cells were washed and resuspend in PBS prior 10X genomic experiment Library was performed according to the manufacter's instructions single cell three prime v2 protocol 10x Genomics", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "NextSeq 2000", null, "SRP428413", null, "loader:fastq load.py", "AAAVLTHHV_trunk_flt1_pool_22s004695-1-1_PREAU_lane1MUT2_1_sequence.txt AAAVLTHHV_trunk_flt1_pool_22s004695-1-1_PREAU_lane1MUT2_2_sequence.txt", "fastq fastq", 35418985138.0, 300160891.0, "GSM7108419 r1", "0:28 1:90", "A:9637251760;C:8083980683;G:8336318307;T:9349259129;N:12175259", 28, 90, null, null, 9637251760, 8083980683, 8336318307, 9349259129, 12175259, "SRX19738955", "SRS17105108", "SRA1608738", "Karlsruhe Institute of Technology (KIT)", "Karlsruhe Institute of Technology (KIT)", 2, 0.00564, 0.94991, 0.00167, 0.10681, 0.99088, 0.78904, 0.41428, 0.4583, 28, 90, "T", "B", "sc-like readlen", "illumina", "nextseq_v2", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2023-03-21", "Larval", "Larval", "Trunk", "Surface Structure"], [74669, "SRR23928777", "SRX19738954", "SRS17105107", "SRP428413", "PRJNA947108", "Gene expression profile at single cell level of zebrafish trunk from WT or flt1 mutant 3dpf.", "GSE227806", "Transcriptome Analysis", "scRNA seq was used to investigate neurovascular cross talk in zebrafish trunk. Overall design: Zebrafish trunk of WT and flt1 mutant were dissected dissociated and processed for single cell RNA Seq using 10X Genomics Chromium droplet based system", "parent bioproject:PRJNA947103", "pubmed:38600061", null, "WT replicate 2 scRNAseq trunk", "GSM7108418", null, "source name:Trunk|tissue:Trunk|genotype:WT|age:3dpf|geo loc name:missing|collection date:missing", "WT replicate 2 scRNAseq trunk", "The demultiplexing barcoded processing gene counting and aggregation were made using the Cell Ranger software https://support.10xgenomics.com/single cell gene expression/software/pipelines/latest/what is cell ranger Assembly: GRCZ11 v107 Supplementary files format and content: matrix files", "Trunk", null, "Zebrafish embryos 3dpf were anesthethised with Tricain prior the dissection of the trunk. Dissected trunks were dissociated using a mix of 0.25% Trypsin and collagenase 4mg/mL centrifuged to collect the cells resuspended into DMEM + 10% Fetal Bovine Serum and filtered to remove the debris. Cells were washed and resuspend in PBS prior 10X genomic experiment Library was performed according to the manufacter\u2019s instructions single cell 3\u2019 v2 protocol 10x Genomics", null, "tissue:Trunk|genotype:WT|age:3dpf", "GSM7108418", "GSM7108418: WT replicate 2 scRNAseq trunk; Danio rerio; RNA Seq", "GSM7108418 r1", "GSM7108418", "1", "Zebrafish embryos 3dpf were anesthethised with Tricain prior the dissection of the trunk. Dissected trunks were dissociated using a mix of 0.25% Trypsin and collagenase 4mg/mL centrifuged to collect the cells resuspended into DMEM + 10% Fetal Bovine Serum and filtered to remove the debris. Cells were washed and resuspend in PBS prior 10X genomic experiment Library was performed according to the manufacter's instructions single cell three prime v2 protocol 10x Genomics", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "NextSeq 2000", null, "SRP428413", null, "loader:fastq load.py", "AAAVLTHHV_trunk_flt1_pool_22s004695-1-1_PREAU_lane1WT2_1_sequence.txt AAAVLTHHV_trunk_flt1_pool_22s004695-1-1_PREAU_lane1WT2_2_sequence.txt", "fastq fastq", 41802904672.0, 354261904.0, "GSM7108418 r1", "0:28 1:90", "A:11394356103;C:9573831647;G:9783049319;T:11037144706;N:14522897", 28, 90, null, null, 11394356103, 9573831647, 9783049319, 11037144706, 14522897, "SRX19738954", "SRS17105107", "SRA1608738", "Karlsruhe Institute of Technology (KIT)", "Karlsruhe Institute of Technology (KIT)", 2, 0.00624, 0.94184, 0.00181, 0.10196, 0.99003, 0.79407, 0.40186, 0.46338, 28, 90, "T", "B", "sc-like readlen", "illumina", "nextseq_v2", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2023-03-21", "Larval", "Larval", "Trunk", "Surface Structure"], [74670, "SRR23928778", "SRX19738953", "SRS17105385", "SRP428413", "PRJNA947108", "Gene expression profile at single cell level of zebrafish trunk from WT or flt1 mutant 3dpf.", "GSE227806", "Transcriptome Analysis", "scRNA seq was used to investigate neurovascular cross talk in zebrafish trunk. Overall design: Zebrafish trunk of WT and flt1 mutant were dissected dissociated and processed for single cell RNA Seq using 10X Genomics Chromium droplet based system", "parent bioproject:PRJNA947103", "pubmed:38600061", null, "flt1mut replicate 1 scRNAseq trunk", "GSM7108417", null, "source name:Trunk|tissue:Trunk|genotype:flt1ka604|age:3dpf|geo loc name:missing|collection date:missing", "flt1mut replicate 1 scRNAseq trunk", "The demultiplexing barcoded processing gene counting and aggregation were made using the Cell Ranger software https://support.10xgenomics.com/single cell gene expression/software/pipelines/latest/what is cell ranger Assembly: GRCZ11 v107 Supplementary files format and content: matrix files", "Trunk", null, "Zebrafish embryos 3dpf were anesthethised with Tricain prior the dissection of the trunk. Dissected trunks were dissociated using a mix of 0.25% Trypsin and collagenase 4mg/mL centrifuged to collect the cells resuspended into DMEM + 10% Fetal Bovine Serum and filtered to remove the debris. Cells were washed and resuspend in PBS prior 10X genomic experiment Library was performed according to the manufacter\u2019s instructions single cell 3\u2019 v2 protocol 10x Genomics", null, "tissue:Trunk|genotype:flt1ka604|age:3dpf", "GSM7108417", "GSM7108417: flt1mut replicate 1 scRNAseq trunk; Danio rerio; RNA Seq", "GSM7108417 r1", "GSM7108417", "1", "Zebrafish embryos 3dpf were anesthethised with Tricain prior the dissection of the trunk. Dissected trunks were dissociated using a mix of 0.25% Trypsin and collagenase 4mg/mL centrifuged to collect the cells resuspended into DMEM + 10% Fetal Bovine Serum and filtered to remove the debris. Cells were washed and resuspend in PBS prior 10X genomic experiment Library was performed according to the manufacter's instructions single cell three prime v2 protocol 10x Genomics", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "NextSeq 2000", null, "SRP428413", null, "loader:fastq load.py", "AAAVLTHHV_trunk_flt1_pool_22s004695-1-1_PREAU_lane1MUT1_1_sequence.txt AAAVLTHHV_trunk_flt1_pool_22s004695-1-1_PREAU_lane1MUT1_2_sequence.txt", "fastq fastq", 37702754542.0, 319514869.0, "GSM7108417 r1", "0:28 1:90", "A:10209528305;C:8624230061;G:8827524184;T:10028556038;N:12915954", 28, 90, null, null, 10209528305, 8624230061, 8827524184, 10028556038, 12915954, "SRX19738953", "SRS17105385", "SRA1608738", "Karlsruhe Institute of Technology (KIT)", "Karlsruhe Institute of Technology (KIT)", 2, 0.00594, 0.95138, 0.00188, 0.10717, 0.9919, 0.79058, 0.38343, 0.46223, 28, 90, "T", "B", "sc-like readlen", "illumina", "nextseq_v2", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2023-03-21", "Larval", "Larval", "Trunk", "Surface Structure"], [74671, "SRR23928779", "SRX19738952", "SRS17105106", "SRP428413", "PRJNA947108", "Gene expression profile at single cell level of zebrafish trunk from WT or flt1 mutant 3dpf.", "GSE227806", "Transcriptome Analysis", "scRNA seq was used to investigate neurovascular cross talk in zebrafish trunk. Overall design: Zebrafish trunk of WT and flt1 mutant were dissected dissociated and processed for single cell RNA Seq using 10X Genomics Chromium droplet based system", "parent bioproject:PRJNA947103", "pubmed:38600061", null, "WT replicate 1 scRNAseq trunk", "GSM7108416", null, "source name:Trunk|tissue:Trunk|genotype:WT|age:3dpf|geo loc name:missing|collection date:missing", "WT replicate 1 scRNAseq trunk", "The demultiplexing barcoded processing gene counting and aggregation were made using the Cell Ranger software https://support.10xgenomics.com/single cell gene expression/software/pipelines/latest/what is cell ranger Assembly: GRCZ11 v107 Supplementary files format and content: matrix files", "Trunk", null, "Zebrafish embryos 3dpf were anesthethised with Tricain prior the dissection of the trunk. Dissected trunks were dissociated using a mix of 0.25% Trypsin and collagenase 4mg/mL centrifuged to collect the cells resuspended into DMEM + 10% Fetal Bovine Serum and filtered to remove the debris. Cells were washed and resuspend in PBS prior 10X genomic experiment Library was performed according to the manufacter\u2019s instructions single cell 3\u2019 v2 protocol 10x Genomics", null, "tissue:Trunk|genotype:WT|age:3dpf", "GSM7108416", "GSM7108416: WT replicate 1 scRNAseq trunk; Danio rerio; RNA Seq", "GSM7108416 r1", "GSM7108416", "1", "Zebrafish embryos 3dpf were anesthethised with Tricain prior the dissection of the trunk. Dissected trunks were dissociated using a mix of 0.25% Trypsin and collagenase 4mg/mL centrifuged to collect the cells resuspended into DMEM + 10% Fetal Bovine Serum and filtered to remove the debris. Cells were washed and resuspend in PBS prior 10X genomic experiment Library was performed according to the manufacter's instructions single cell three prime v2 protocol 10x Genomics", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "NextSeq 2000", null, "SRP428413", null, "loader:fastq load.py", "AAAVLTHHV_trunk_flt1_pool_22s004695-1-1_PREAU_lane1WT1_1_sequence.txt AAAVLTHHV_trunk_flt1_pool_22s004695-1-1_PREAU_lane1WT1_2_sequence.txt", "fastq fastq", 30416957822.0, 257770829.0, "GSM7108416 r1", "0:28 1:90", "A:8231697522;C:6992122503;G:7225363090;T:7957278327;N:10496380", 28, 90, null, null, 8231697522, 6992122503, 7225363090, 7957278327, 10496380, "SRX19738952", "SRS17105106", "SRA1608738", "Karlsruhe Institute of Technology (KIT)", "Karlsruhe Institute of Technology (KIT)", 2, 0.00623, 0.94345, 0.00214, 0.11682, 0.99105, 0.78033, 0.36317, 0.48249, 28, 90, "T", "B", "sc-like readlen", "illumina", "nextseq_v2", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2023-03-21", "Larval", "Larval", "Trunk", "Surface Structure"], [74951, "SRR24203796", "SRX20000418", "SRS17345141", "SRP433186", "PRJNA956844", "Gene expression profile at single cell level of sclerotome derived fibroblasts from 52 hpf transgenic zebrafish trunks.", "GSE229939", "Other", "The sclerotome region of the somite labelled by nkx3.1:Gal4 VP16; UAS:NTR mCherry gives rise to numerous fibroblasts populations in the zebrafish trunk. We performed single cell RNA sequencing scRNA seq on sclerotome derived fibroblasts from 52 hpf embryos to determine population heterogeneity and plasticity. Overall design: scRNA seq was performed on mCherry positive cells from trunk regions of 52 hpf Tg BACnkx3.1:Gal4 VP16ca101; TgUAS:NTR mCherryca264 zebrafish isolated by Fluorescence activated cell sorting FACS. The single cell library was prepared using 10X Genomics three prime gene expression profiling droplet based scRNA seq technology v3.1 chemistry according to manufacturer's protocols. Sequencing was performed on the using the Illumina NovaSeq S2 flow cell.", null, "pubmed:37967180", null, "52 hpf mCherry positive", "GSM7181573", null, "source name:zebrafish trunks dissected at the beginning of the yolk extension|cell type:Sclerotome derived cells|tissue:zebrafish trunks dissected at the beginning of the yolk extension|strain:Tg BACnkx3.1:Gal4 VP16ca101; TgUAS:NTR mCherryca264|age:52 hpf", "52 hpf mCherry positive", "A custom zebrafish transcriptome was prepared using V4.3.2 GTFs Lawson et al. 2021 and the GRCz11 Danio rerio reference genome with appended mCherry sequence using standard CellRanger mkgtf and mkref pipelines. FASTQs were then filtered and aligned to the reference using Cellranger count. All pipelines used 10X GEnomics CellRanger v5.0.0 software. Downstream quality control normalization dimension reduction clustering and analysis was performed in R using Seurat v4.0.0. Assembly: GRCz11 Supplementary files format and content: 10x Genomics output files: barcodes.tsv.gz features.tsv.gz matrix.mtx.gz", "zebrafish trunks dissected at the beginning of the yolk extension", null, "About 140 hpf 52 hpf nkx3.1NTR mCherry embryos were anesthetized in fish water with 0.4% tricaine and maintained over ice during dissection. Trunks were dissected at the beginning of the yolk extension using a surgical scalpel. Dissected trunk tissues were then 0.25% Trypsin + 1 mM EDTA solution at 28.5\u00b0C for 20 minutes with gentle shaking at 300 rpm. Dissociated was then stopped and dissolved tissue was washed with 1% FBS solution in 1x DPBS Dulbecco\u2019s phosphate buffered saline ThermoFisher Scientific and strained. Live mCherry+ cells were collected by fluorescence activated cell sorting FACS. Sorted cells were resuspended in 50 \u03bcl HBSS Hank\u2019s Balanced Salt Solution + 2% BSA Bovine Serum Albumin. 15 000 live mCherry+ cells were loaded into the 10X Genomics Chromium Controller for droplet based cell separation. cDNA libraries were generated using the 10X Genomics 3\u2019 gene expression profiling droplet based scRNA seq kit v3.1 chemistry according to manufacturer\u2019s protocol. cDNA was amplified for 12 cycles and an index primer was added for sequencing using 14 PCR cycles", "Zebrafish embryos were raised at 28.5 \u00b0C. Embryos older than 24 hours were grown in fish water with added 1 phenyl 2 thiourea PTU to prevent pigmentation.", "cell type:Sclerotome derived cells|tissue:zebrafish trunks dissected at the beginning of the yolk extension|strain:Tg BACnkx3.1:Gal4 VP16ca101; TgUAS:NTR mCherryca264|age:52 hpf", "GSM7181573", "GSM7181573: 52 hpf mCherry positive; Danio rerio; RNA Seq", "GSM7181573 r1", "GSM7181573", "1", "About 140 hpf 52 hpf nkx3.1NTR mCherry embryos were anesthetized in fish water with 0.4% tricaine and maintained over ice during dissection. Trunks were dissected at the beginning of the yolk extension using a surgical scalpel. Dissected trunk tissues were then 0.25% Trypsin + 1 mM EDTA solution at 28.5\u00b0C for 20 minutes with gentle shaking at 300 rpm. Dissociated was then stopped and dissolved tissue was washed with 1% FBS solution in 1x DPBS Dulbecco's phosphate buffered saline ThermoFisher Scientific and strained. Live mCherry+ cells were collected by fluorescence activated cell sorting FACS. Sorted cells were resuspended in 50 \u03bcl HBSS Hank's Balanced Salt Solution + 2% BSA Bovine Serum Albumin. 15 000 live mCherry+ cells were loaded into the 10X Genomics Chromium Controller for droplet based cell separation. cDNA libraries were generated using the 10X Genomics three prime gene expression profiling droplet based scRNA seq kit v3.1 chemistry according to manufacturer's protocol. cDNA was amplified for 12 cycles and an index primer was added for sequencing using 14 PCR cycles", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP433186", null, "loader:fastq load.py", "AR_2_S5_L002_I1_001.fastq.gz AR_2_S5_L002_R1_001.fastq.gz AR_2_S5_L002_R2_001.fastq.gz", "fastq fastq fastq", 12097924750.0, 95259250.0, "GSM7181573 r1", "0:8 1:28 2:91", "A:2458401542;C:1953802815;G:2304998485;T:1951185638;N:203270", 8, 28, 91, null, 2458401542, 1953802815, 2304998485, 1951185638, 203270, "SRX20000418", "SRS17345141", "SRA1623336", "Department of Biochemistry and Molecular Biology, University of Calgary", "Department of Biochemistry and Molecular Biology, University of Calgary", 1, 0.85356, null, 0.24065, null, 0.84705, null, 0.64618, null, 91, null, "B", null, "usable mapping rate", "illumina", "novaseq_era", "3prime", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "Canada", "2023-04-18", "Hatching", "Embryo", "Trunk", "Surface Structure"], [74952, "SRR24203797", "SRX20000418", "SRS17345141", "SRP433186", "PRJNA956844", "Gene expression profile at single cell level of sclerotome derived fibroblasts from 52 hpf transgenic zebrafish trunks.", "GSE229939", "Other", "The sclerotome region of the somite labelled by nkx3.1:Gal4 VP16; UAS:NTR mCherry gives rise to numerous fibroblasts populations in the zebrafish trunk. We performed single cell RNA sequencing scRNA seq on sclerotome derived fibroblasts from 52 hpf embryos to determine population heterogeneity and plasticity. Overall design: scRNA seq was performed on mCherry positive cells from trunk regions of 52 hpf Tg BACnkx3.1:Gal4 VP16ca101; TgUAS:NTR mCherryca264 zebrafish isolated by Fluorescence activated cell sorting FACS. The single cell library was prepared using 10X Genomics three prime gene expression profiling droplet based scRNA seq technology v3.1 chemistry according to manufacturer's protocols. Sequencing was performed on the using the Illumina NovaSeq S2 flow cell.", null, "pubmed:37967180", null, "52 hpf mCherry positive", "GSM7181573", null, "source name:zebrafish trunks dissected at the beginning of the yolk extension|cell type:Sclerotome derived cells|tissue:zebrafish trunks dissected at the beginning of the yolk extension|strain:Tg BACnkx3.1:Gal4 VP16ca101; TgUAS:NTR mCherryca264|age:52 hpf", "52 hpf mCherry positive", "A custom zebrafish transcriptome was prepared using V4.3.2 GTFs Lawson et al. 2021 and the GRCz11 Danio rerio reference genome with appended mCherry sequence using standard CellRanger mkgtf and mkref pipelines. FASTQs were then filtered and aligned to the reference using Cellranger count. All pipelines used 10X GEnomics CellRanger v5.0.0 software. Downstream quality control normalization dimension reduction clustering and analysis was performed in R using Seurat v4.0.0. Assembly: GRCz11 Supplementary files format and content: 10x Genomics output files: barcodes.tsv.gz features.tsv.gz matrix.mtx.gz", "zebrafish trunks dissected at the beginning of the yolk extension", null, "About 140 hpf 52 hpf nkx3.1NTR mCherry embryos were anesthetized in fish water with 0.4% tricaine and maintained over ice during dissection. Trunks were dissected at the beginning of the yolk extension using a surgical scalpel. Dissected trunk tissues were then 0.25% Trypsin + 1 mM EDTA solution at 28.5\u00b0C for 20 minutes with gentle shaking at 300 rpm. Dissociated was then stopped and dissolved tissue was washed with 1% FBS solution in 1x DPBS Dulbecco\u2019s phosphate buffered saline ThermoFisher Scientific and strained. Live mCherry+ cells were collected by fluorescence activated cell sorting FACS. Sorted cells were resuspended in 50 \u03bcl HBSS Hank\u2019s Balanced Salt Solution + 2% BSA Bovine Serum Albumin. 15 000 live mCherry+ cells were loaded into the 10X Genomics Chromium Controller for droplet based cell separation. cDNA libraries were generated using the 10X Genomics 3\u2019 gene expression profiling droplet based scRNA seq kit v3.1 chemistry according to manufacturer\u2019s protocol. cDNA was amplified for 12 cycles and an index primer was added for sequencing using 14 PCR cycles", "Zebrafish embryos were raised at 28.5 \u00b0C. Embryos older than 24 hours were grown in fish water with added 1 phenyl 2 thiourea PTU to prevent pigmentation.", "cell type:Sclerotome derived cells|tissue:zebrafish trunks dissected at the beginning of the yolk extension|strain:Tg BACnkx3.1:Gal4 VP16ca101; TgUAS:NTR mCherryca264|age:52 hpf", "GSM7181573", "GSM7181573: 52 hpf mCherry positive; Danio rerio; RNA Seq", "GSM7181573 r1", "GSM7181573", "1", "About 140 hpf 52 hpf nkx3.1NTR mCherry embryos were anesthetized in fish water with 0.4% tricaine and maintained over ice during dissection. Trunks were dissected at the beginning of the yolk extension using a surgical scalpel. Dissected trunk tissues were then 0.25% Trypsin + 1 mM EDTA solution at 28.5\u00b0C for 20 minutes with gentle shaking at 300 rpm. Dissociated was then stopped and dissolved tissue was washed with 1% FBS solution in 1x DPBS Dulbecco's phosphate buffered saline ThermoFisher Scientific and strained. Live mCherry+ cells were collected by fluorescence activated cell sorting FACS. Sorted cells were resuspended in 50 \u03bcl HBSS Hank's Balanced Salt Solution + 2% BSA Bovine Serum Albumin. 15 000 live mCherry+ cells were loaded into the 10X Genomics Chromium Controller for droplet based cell separation. cDNA libraries were generated using the 10X Genomics three prime gene expression profiling droplet based scRNA seq kit v3.1 chemistry according to manufacturer's protocol. cDNA was amplified for 12 cycles and an index primer was added for sequencing using 14 PCR cycles", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP433186", null, "loader:fastq load.py", "AR_2_S5_L001_I1_001.fastq.gz AR_2_S5_L001_R1_001.fastq.gz AR_2_S5_L001_R2_001.fastq.gz", "fastq fastq fastq", 11926942872.0, 93912936.0, "GSM7181573 r2", "0:8 1:28 2:91", "A:2430702466;C:1919825027;G:2264443130;T:1930929426;N:177127", 8, 28, 91, null, 2430702466, 1919825027, 2264443130, 1930929426, 177127, "SRX20000418", "SRS17345141", "SRA1623336", "Department of Biochemistry and Molecular Biology, University of Calgary", "Department of Biochemistry and Molecular Biology, University of Calgary", 1, 0.85561, null, 0.24037, null, 0.84678, null, 0.66835, null, 91, null, "B", null, "usable mapping rate", "illumina", "novaseq_era", "3prime", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "Canada", "2023-04-18", "Hatching", "Embryo", "Trunk", "Surface Structure"], [74953, "SRR24203798", "SRX20000418", "SRS17345141", "SRP433186", "PRJNA956844", "Gene expression profile at single cell level of sclerotome derived fibroblasts from 52 hpf transgenic zebrafish trunks.", "GSE229939", "Other", "The sclerotome region of the somite labelled by nkx3.1:Gal4 VP16; UAS:NTR mCherry gives rise to numerous fibroblasts populations in the zebrafish trunk. We performed single cell RNA sequencing scRNA seq on sclerotome derived fibroblasts from 52 hpf embryos to determine population heterogeneity and plasticity. Overall design: scRNA seq was performed on mCherry positive cells from trunk regions of 52 hpf Tg BACnkx3.1:Gal4 VP16ca101; TgUAS:NTR mCherryca264 zebrafish isolated by Fluorescence activated cell sorting FACS. The single cell library was prepared using 10X Genomics three prime gene expression profiling droplet based scRNA seq technology v3.1 chemistry according to manufacturer's protocols. Sequencing was performed on the using the Illumina NovaSeq S2 flow cell.", null, "pubmed:37967180", null, "52 hpf mCherry positive", "GSM7181573", null, "source name:zebrafish trunks dissected at the beginning of the yolk extension|cell type:Sclerotome derived cells|tissue:zebrafish trunks dissected at the beginning of the yolk extension|strain:Tg BACnkx3.1:Gal4 VP16ca101; TgUAS:NTR mCherryca264|age:52 hpf", "52 hpf mCherry positive", "A custom zebrafish transcriptome was prepared using V4.3.2 GTFs Lawson et al. 2021 and the GRCz11 Danio rerio reference genome with appended mCherry sequence using standard CellRanger mkgtf and mkref pipelines. FASTQs were then filtered and aligned to the reference using Cellranger count. All pipelines used 10X GEnomics CellRanger v5.0.0 software. Downstream quality control normalization dimension reduction clustering and analysis was performed in R using Seurat v4.0.0. Assembly: GRCz11 Supplementary files format and content: 10x Genomics output files: barcodes.tsv.gz features.tsv.gz matrix.mtx.gz", "zebrafish trunks dissected at the beginning of the yolk extension", null, "About 140 hpf 52 hpf nkx3.1NTR mCherry embryos were anesthetized in fish water with 0.4% tricaine and maintained over ice during dissection. Trunks were dissected at the beginning of the yolk extension using a surgical scalpel. Dissected trunk tissues were then 0.25% Trypsin + 1 mM EDTA solution at 28.5\u00b0C for 20 minutes with gentle shaking at 300 rpm. Dissociated was then stopped and dissolved tissue was washed with 1% FBS solution in 1x DPBS Dulbecco\u2019s phosphate buffered saline ThermoFisher Scientific and strained. Live mCherry+ cells were collected by fluorescence activated cell sorting FACS. Sorted cells were resuspended in 50 \u03bcl HBSS Hank\u2019s Balanced Salt Solution + 2% BSA Bovine Serum Albumin. 15 000 live mCherry+ cells were loaded into the 10X Genomics Chromium Controller for droplet based cell separation. cDNA libraries were generated using the 10X Genomics 3\u2019 gene expression profiling droplet based scRNA seq kit v3.1 chemistry according to manufacturer\u2019s protocol. cDNA was amplified for 12 cycles and an index primer was added for sequencing using 14 PCR cycles", "Zebrafish embryos were raised at 28.5 \u00b0C. Embryos older than 24 hours were grown in fish water with added 1 phenyl 2 thiourea PTU to prevent pigmentation.", "cell type:Sclerotome derived cells|tissue:zebrafish trunks dissected at the beginning of the yolk extension|strain:Tg BACnkx3.1:Gal4 VP16ca101; TgUAS:NTR mCherryca264|age:52 hpf", "GSM7181573", "GSM7181573: 52 hpf mCherry positive; Danio rerio; RNA Seq", "GSM7181573 r1", "GSM7181573", "1", "About 140 hpf 52 hpf nkx3.1NTR mCherry embryos were anesthetized in fish water with 0.4% tricaine and maintained over ice during dissection. Trunks were dissected at the beginning of the yolk extension using a surgical scalpel. Dissected trunk tissues were then 0.25% Trypsin + 1 mM EDTA solution at 28.5\u00b0C for 20 minutes with gentle shaking at 300 rpm. Dissociated was then stopped and dissolved tissue was washed with 1% FBS solution in 1x DPBS Dulbecco's phosphate buffered saline ThermoFisher Scientific and strained. Live mCherry+ cells were collected by fluorescence activated cell sorting FACS. Sorted cells were resuspended in 50 \u03bcl HBSS Hank's Balanced Salt Solution + 2% BSA Bovine Serum Albumin. 15 000 live mCherry+ cells were loaded into the 10X Genomics Chromium Controller for droplet based cell separation. cDNA libraries were generated using the 10X Genomics three prime gene expression profiling droplet based scRNA seq kit v3.1 chemistry according to manufacturer's protocol. cDNA was amplified for 12 cycles and an index primer was added for sequencing using 14 PCR cycles", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP433186", null, "loader:fastq load.py", "AR_2_S4_L002_I1_001.fastq.gz AR_2_S4_L002_R1_001.fastq.gz AR_2_S4_L002_R2_001.fastq.gz", "fastq fastq fastq", 6129613598.0, 48264674.0, "GSM7181573 r3", "0:8 1:28 2:91", "A:1248940274;C:989811597;G:1170220249;T:982937378;N:175836", 8, 28, 91, null, 1248940274, 989811597, 1170220249, 982937378, 175836, "SRX20000418", "SRS17345141", "SRA1623336", "Department of Biochemistry and Molecular Biology, University of Calgary", "Department of Biochemistry and Molecular Biology, University of Calgary", 1, 0.85545, null, 0.24212, null, 0.84816, null, 0.65892, null, 91, null, "B", null, "usable mapping rate", "illumina", "novaseq_era", "3prime", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "Canada", "2023-04-18", "Hatching", "Embryo", "Trunk", "Surface Structure"], [74954, "SRR24203799", "SRX20000418", "SRS17345141", "SRP433186", "PRJNA956844", "Gene expression profile at single cell level of sclerotome derived fibroblasts from 52 hpf transgenic zebrafish trunks.", "GSE229939", "Other", "The sclerotome region of the somite labelled by nkx3.1:Gal4 VP16; UAS:NTR mCherry gives rise to numerous fibroblasts populations in the zebrafish trunk. We performed single cell RNA sequencing scRNA seq on sclerotome derived fibroblasts from 52 hpf embryos to determine population heterogeneity and plasticity. Overall design: scRNA seq was performed on mCherry positive cells from trunk regions of 52 hpf Tg BACnkx3.1:Gal4 VP16ca101; TgUAS:NTR mCherryca264 zebrafish isolated by Fluorescence activated cell sorting FACS. The single cell library was prepared using 10X Genomics three prime gene expression profiling droplet based scRNA seq technology v3.1 chemistry according to manufacturer's protocols. Sequencing was performed on the using the Illumina NovaSeq S2 flow cell.", null, "pubmed:37967180", null, "52 hpf mCherry positive", "GSM7181573", null, "source name:zebrafish trunks dissected at the beginning of the yolk extension|cell type:Sclerotome derived cells|tissue:zebrafish trunks dissected at the beginning of the yolk extension|strain:Tg BACnkx3.1:Gal4 VP16ca101; TgUAS:NTR mCherryca264|age:52 hpf", "52 hpf mCherry positive", "A custom zebrafish transcriptome was prepared using V4.3.2 GTFs Lawson et al. 2021 and the GRCz11 Danio rerio reference genome with appended mCherry sequence using standard CellRanger mkgtf and mkref pipelines. FASTQs were then filtered and aligned to the reference using Cellranger count. All pipelines used 10X GEnomics CellRanger v5.0.0 software. Downstream quality control normalization dimension reduction clustering and analysis was performed in R using Seurat v4.0.0. Assembly: GRCz11 Supplementary files format and content: 10x Genomics output files: barcodes.tsv.gz features.tsv.gz matrix.mtx.gz", "zebrafish trunks dissected at the beginning of the yolk extension", null, "About 140 hpf 52 hpf nkx3.1NTR mCherry embryos were anesthetized in fish water with 0.4% tricaine and maintained over ice during dissection. Trunks were dissected at the beginning of the yolk extension using a surgical scalpel. Dissected trunk tissues were then 0.25% Trypsin + 1 mM EDTA solution at 28.5\u00b0C for 20 minutes with gentle shaking at 300 rpm. Dissociated was then stopped and dissolved tissue was washed with 1% FBS solution in 1x DPBS Dulbecco\u2019s phosphate buffered saline ThermoFisher Scientific and strained. Live mCherry+ cells were collected by fluorescence activated cell sorting FACS. Sorted cells were resuspended in 50 \u03bcl HBSS Hank\u2019s Balanced Salt Solution + 2% BSA Bovine Serum Albumin. 15 000 live mCherry+ cells were loaded into the 10X Genomics Chromium Controller for droplet based cell separation. cDNA libraries were generated using the 10X Genomics 3\u2019 gene expression profiling droplet based scRNA seq kit v3.1 chemistry according to manufacturer\u2019s protocol. cDNA was amplified for 12 cycles and an index primer was added for sequencing using 14 PCR cycles", "Zebrafish embryos were raised at 28.5 \u00b0C. Embryos older than 24 hours were grown in fish water with added 1 phenyl 2 thiourea PTU to prevent pigmentation.", "cell type:Sclerotome derived cells|tissue:zebrafish trunks dissected at the beginning of the yolk extension|strain:Tg BACnkx3.1:Gal4 VP16ca101; TgUAS:NTR mCherryca264|age:52 hpf", "GSM7181573", "GSM7181573: 52 hpf mCherry positive; Danio rerio; RNA Seq", "GSM7181573 r1", "GSM7181573", "1", "About 140 hpf 52 hpf nkx3.1NTR mCherry embryos were anesthetized in fish water with 0.4% tricaine and maintained over ice during dissection. Trunks were dissected at the beginning of the yolk extension using a surgical scalpel. Dissected trunk tissues were then 0.25% Trypsin + 1 mM EDTA solution at 28.5\u00b0C for 20 minutes with gentle shaking at 300 rpm. Dissociated was then stopped and dissolved tissue was washed with 1% FBS solution in 1x DPBS Dulbecco's phosphate buffered saline ThermoFisher Scientific and strained. Live mCherry+ cells were collected by fluorescence activated cell sorting FACS. Sorted cells were resuspended in 50 \u03bcl HBSS Hank's Balanced Salt Solution + 2% BSA Bovine Serum Albumin. 15 000 live mCherry+ cells were loaded into the 10X Genomics Chromium Controller for droplet based cell separation. cDNA libraries were generated using the 10X Genomics three prime gene expression profiling droplet based scRNA seq kit v3.1 chemistry according to manufacturer's protocol. cDNA was amplified for 12 cycles and an index primer was added for sequencing using 14 PCR cycles", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP433186", null, "loader:fastq load.py", "AR_2_S4_L001_I1_001.fastq.gz AR_2_S4_L001_R1_001.fastq.gz AR_2_S4_L001_R2_001.fastq.gz", "fastq fastq fastq", 6325004622.0, 49803186.0, "GSM7181573 r4", "0:8 1:28 2:91", "A:1283864621;C:1025588666;G:1211968623;T:1010456763;N:211253", 8, 28, 91, null, 1283864621, 1025588666, 1211968623, 1010456763, 211253, "SRX20000418", "SRS17345141", "SRA1623336", "Department of Biochemistry and Molecular Biology, University of Calgary", "Department of Biochemistry and Molecular Biology, University of Calgary", 1, 0.85448, null, 0.24209, null, 0.84934, null, 0.68035, null, 91, null, "B", null, "usable mapping rate", "illumina", "novaseq_era", "3prime", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "Canada", "2023-04-18", "Hatching", "Embryo", "Trunk", "Surface Structure"], [76372, "SRR24954201", "SRX20712237", "SRS18004425", "SRP444513", "PRJNA981358", "Danio rerio Genome sequencing and assembly", "PRJNA981358", "Whole Genome Sequencing", "To explore the source of Csf1a and Csf1b in embryonic zebrafish we carried out a single cell RNA sequencing scRNA seq. We collected the trunks from 28 hpf embryos and performed 10X Genomics scRNA seq.", null, null, "This sample contained cells isolated from trunks of 40 zebrafish embryos at 28hpf.", "Cells isolated from trunks of wildtype danio rerio at 28hpf", "WT 1", null, "strain:ABSR|dev stage:28 hpf date:2019 11 18|geo loc name:China: Guangzhou|sex:not determined|tissue:Trunk|BioSampleModel:Model organism or animal", null, null, null, null, null, null, null, null, "scRNA seq of 28hpfWT trunk", "28hpfWT 1", "28hpfWT 1", "Cellular suspensions were loaded on a 10X Genomics GemCode Single cell instrument that generates single cell Gel Bead In EMlusion GEMs. Libraries were generated and sequenced from the cDNAs with Chromium Next GEM Single Cell 3 Reagent Kits v3.1. Upon dissolution of the Gel Bead in a GEM primers containing i an Illumina R1 sequence read 1 sequencing primer ii a 16nt 10x Barcode iii a 10nt Unique Molecular Identifier UMI and iv a poly dT primer sequence were released and mixed with cell lysate and Master Mix. Barcoded full length cDNAs were then reverse transcribed from poly adenylated mRNA. Silane magnetic beads were used to remove leftover biochemical reagents and primers from the post GEM reaction mixture. Full length barcoded cDNAs were then amplified by PCR to generate sufficient mass for library construction. R1 were added to the molecules during GEM incubation. P5 P7 a sample index and R2 were added during library construction via End Repair A tailing Adaptor Ligation and PCR. The final libraries contained the P5 and P7 primers used in Illumina bridge amplification.", null, null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "SINGLE", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP444513", null, null, "J1911072-ATGCTCCG_BKDL192544560-1a-AK949_2.fq.gz J1911072-CACTCGGA_BKDL192544560-1a-AK946_1.fq.gz J1911072-CACTCGGA_BKDL192544560-1a-AK946_2.fq.gz J1911072-GCTGAATT_BKDL192544560-1a-AK947_1.fq.gz J1911072-GCTGAATT_BKDL192544560-1a-AK947_2.fq.gz J1911072-TGAAGTAC_BKDL192544560-1a-AK948_1.fq.gz J1911072-TGAAGTAC_BKDL192544560-1a-AK948_2.fq.gz J1911072-ATGCTCCG_BKDL192544560-1a-AK949_1.fq.gz", "fastq fastq fastq fastq fastq fastq fastq fastq", 144260432400.0, 480868108.0, "J1911072 ATGCTCCG BKDL192544560 1a AK949 1.fq.gz", "0:150 1:150", "A:57113710706;C:25903289244;G:24836065109;T:36405707402;N:1659939", 150, 150, null, null, 57113710706, 25903289244, 24836065109, 36405707402, 1659939, "SRX20712237", "SRS18004425", "SRA1657728", "South China University of Technology|School of Medicine", "South China University of Technology", 2, 0.0, 0.92449, 0.0, 0.12055, 1.0, 0.77806, null, 0.51028, 150, 150, "T", "B", "mate1 technical by mapping diff", "illumina", "novaseq_era", "full_length", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "China", "2023-06-17", "Pharyngula", "Embryo", "Trunk", "Surface Structure"]], "truncated": false, "filtered_table_rows_count": 79, "expanded_columns": [], "expandable_columns": [], "columns": ["rowid", "run.accession", "experiment.accession", "sample.accession", "study.accession", "bioproject", "study.title", "study.alias", "study.type", "study.abstract", "study.attributes", "study.PMIDs", "sample.description", "sample.title", "sample.alias", "sample.centername", "sample.attributes", "GEOsample.title", "GEOsample.dataprocessing", "GEOsample.source", "GEOsample.treatmentprotocol", "GEOsample.extractprotocol", "GEOsample.growthprotocol", "GEOsample.characteristics", "GEOsample.accession", "experiment.title", "experiment.alias", "experiment.library_name", "experiment.design_description", "experiment.library_construction_protocol", "experiment.attributes", "experiment.library_strategy", "experiment.library_source", "experiment.library_selection", "experiment.library_layout", "experiment.platform", "experiment.instrument_model", "experiment.spot_descriptor", "experiment.study_ref", "run.title", "run.attributes", "run.filename", "run.semantic_name", "run.total_bases", "run.total_spots", "run.alias", "run.read_lengths", "run.base_counts", "run.r1_length", "run.r2_length", "run.r3_length", "run.r4_length", "run.Acount", "run.Ccount", "run.Gcount", "run.Tcount", "run.Ncount", "run.experiment", "run.pool_member", "submission.accession", "submission.srasource", "submission.bioprojectsource", "seqdetective.n_mates", "seqdetective.mapping_rate.mate1", "seqdetective.mapping_rate.mate2", "seqdetective.nofeature_rate.mate1", "seqdetective.nofeature_rate.mate2", "seqdetective.sparsity.mate1", "seqdetective.sparsity.mate2", "seqdetective.pos_strand_rate.mate1", "seqdetective.pos_strand_rate.mate2", "seqdetective.readlen.mate1", "seqdetective.readlen.mate2", "seqdetective.judgement.mate1", "seqdetective.judgement.mate2", "seqdetective.judgement.reason", "platform_family", "instrument_generation", "read_bias", "selection_class", "prep_kit", "sc_or_bulk", "tech_class", "technology", "tech_variant", "submission.bioprojectsource.country", "earliest_date", "devstage_curation", "devstage_curation_coarse", "tissue_curation", "tissue_curation_coarse"], "primary_keys": [], "units": {}, "query": {"sql": "select rowid, [run.accession], [experiment.accession], [sample.accession], [study.accession], bioproject, [study.title], [study.alias], [study.type], [study.abstract], [study.attributes], [study.PMIDs], [sample.description], [sample.title], [sample.alias], [sample.centername], [sample.attributes], [GEOsample.title], [GEOsample.dataprocessing], [GEOsample.source], [GEOsample.treatmentprotocol], [GEOsample.extractprotocol], [GEOsample.growthprotocol], [GEOsample.characteristics], [GEOsample.accession], [experiment.title], [experiment.alias], [experiment.library_name], [experiment.design_description], [experiment.library_construction_protocol], [experiment.attributes], [experiment.library_strategy], [experiment.library_source], [experiment.library_selection], [experiment.library_layout], [experiment.platform], [experiment.instrument_model], [experiment.spot_descriptor], [experiment.study_ref], [run.title], [run.attributes], [run.filename], [run.semantic_name], [run.total_bases], [run.total_spots], [run.alias], [run.read_lengths], [run.base_counts], [run.r1_length], [run.r2_length], [run.r3_length], [run.r4_length], [run.Acount], [run.Ccount], [run.Gcount], [run.Tcount], [run.Ncount], [run.experiment], [run.pool_member], [submission.accession], [submission.srasource], [submission.bioprojectsource], [seqdetective.n_mates], [seqdetective.mapping_rate.mate1], [seqdetective.mapping_rate.mate2], [seqdetective.nofeature_rate.mate1], [seqdetective.nofeature_rate.mate2], [seqdetective.sparsity.mate1], [seqdetective.sparsity.mate2], [seqdetective.pos_strand_rate.mate1], [seqdetective.pos_strand_rate.mate2], [seqdetective.readlen.mate1], [seqdetective.readlen.mate2], [seqdetective.judgement.mate1], [seqdetective.judgement.mate2], [seqdetective.judgement.reason], platform_family, instrument_generation, read_bias, selection_class, prep_kit, sc_or_bulk, tech_class, technology, tech_variant, [submission.bioprojectsource.country], earliest_date, devstage_curation, devstage_curation_coarse, tissue_curation, tissue_curation_coarse from run_metadata where \"technology\" = :p0 and \"tissue_curation\" = :p1 order by rowid limit 101", "params": {"p0": "10x", "p1": "Trunk"}}, "facet_results": {"experiment.library_strategy": {"name": "experiment.library_strategy", "type": "column", "hideable": false, "toggle_url": "/metadata/run_metadata.json?technology=10x&tissue_curation=Trunk", "results": [{"value": "RNA-Seq", "label": "RNA-Seq", "count": 70, "toggle_url": "http://metadata.rnaquarium.org/metadata/run_metadata.json?technology=10x&tissue_curation=Trunk&experiment.library_strategy=RNA-Seq", "selected": false}, {"value": "OTHER", "label": "OTHER", "count": 9, "toggle_url": "http://metadata.rnaquarium.org/metadata/run_metadata.json?technology=10x&tissue_curation=Trunk&experiment.library_strategy=OTHER", "selected": false}], "truncated": false}, "experiment.library_source": {"name": "experiment.library_source", "type": "column", "hideable": false, "toggle_url": "/metadata/run_metadata.json?technology=10x&tissue_curation=Trunk", "results": [{"value": "TRANSCRIPTOMIC", "label": "TRANSCRIPTOMIC", "count": 46, "toggle_url": "http://metadata.rnaquarium.org/metadata/run_metadata.json?technology=10x&tissue_curation=Trunk&experiment.library_source=TRANSCRIPTOMIC", "selected": false}, {"value": 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"experiment.library_layout", "type": "column", "hideable": false, "toggle_url": "/metadata/run_metadata.json?technology=10x&tissue_curation=Trunk", "results": [{"value": "PAIRED", "label": "PAIRED", "count": 78, "toggle_url": "http://metadata.rnaquarium.org/metadata/run_metadata.json?technology=10x&tissue_curation=Trunk&experiment.library_layout=PAIRED", "selected": false}, {"value": "SINGLE", "label": "SINGLE", "count": 1, "toggle_url": "http://metadata.rnaquarium.org/metadata/run_metadata.json?technology=10x&tissue_curation=Trunk&experiment.library_layout=SINGLE", "selected": false}], "truncated": false}, "experiment.platform": {"name": "experiment.platform", "type": "column", "hideable": false, "toggle_url": "/metadata/run_metadata.json?technology=10x&tissue_curation=Trunk", "results": [{"value": "ILLUMINA", "label": "ILLUMINA", "count": 79, "toggle_url": "http://metadata.rnaquarium.org/metadata/run_metadata.json?technology=10x&tissue_curation=Trunk&experiment.platform=ILLUMINA", 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"column", "hideable": false, "toggle_url": "/metadata/run_metadata.json?technology=10x&tissue_curation=Trunk", "results": [{"value": "Trunk", "label": "Trunk", "count": 79, "toggle_url": "http://metadata.rnaquarium.org/metadata/run_metadata.json?technology=10x", "selected": true}], "truncated": false}, "technology": {"name": "technology", "type": "column", "hideable": false, "toggle_url": "/metadata/run_metadata.json?technology=10x&tissue_curation=Trunk", "results": [{"value": "10x", "label": "10x", "count": 79, "toggle_url": "http://metadata.rnaquarium.org/metadata/run_metadata.json?tissue_curation=Trunk", "selected": true}], "truncated": false}}, "suggested_facets": [], "next": null, "next_url": null, "private": false, "allow_execute_sql": true, "query_ms": 128.60261899913894}