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
31525,SRR28419473,SRX24023800,SRS20818155,SRP497235,PRJNA1090867,Single cell RNA seq of zebrafish endothelial cells,GSE262232,Transcriptome Analysis,We performed single cell RNA sequencing scRNA seq for isolated endothelial cells Overall design: Tgkdrl:EGFP zebrafish embryos were digested into single cell suspension  EGFP positive cells were isolated using FACS and subjected to 10X Genomics Chromium scRNAseq.,,pubmed:39977018,,Zebrafish endothelial cells 3 dpf 2,GSM8160887,,source name:Whole body|tissue:Whole body|age:embryo|geo loc name:missing|collection date:missing,Zebrafish endothelial cells 3 dpf 2,Cell Ranger v2.1 was used to de multiplex raw base call BCL files generated by Illumina sequencers into FASTQ files  perform the alignment  barcode counting  and UMI counting. Assembly: GRCz11 Supplementary files format and content: Tab seprated values files,Whole body,,Whole Tgkdrl:EGFP zebrafish embryos were digested into single cell suspensions  EGFP positive cells were isolated using FACS Single cell suspension was loaded into the 10X Chromium system and cDNA libraries were constructed using Chromium Next GEM Single Cell 3′ GEM  Library and Gel Bead Kit v2 10X Genomics according to manufacturer’s protocol.,,tissue:Whole body|age:embryo,GSM8160887,GSM8160887: Zebrafish endothelial cells 3 dpf 2; Danio rerio; RNA Seq,GSM8160887 r1,GSM8160887,1,Whole Tgkdrl:EGFP zebrafish embryos were digested into single cell suspensions  EGFP positive cells were isolated using FACS Single cell suspension was loaded into the 10X Chromium system and cDNA libraries were constructed using Chromium Next GEM Single Cell 3′ GEM  Library and Gel Bead Kit v2 10X Genomics according to manufacturer's protocol.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina HiSeq 1500,,SRP497235,,assembly:GRCz11|intentional duplicate|dangling references:treat as unmapped|dangling references:skip reference resolution,3dpf_2_possorted_genome_bam.bam,10X Genomics bam file,8478190406.0,86512147.0,GSM8160887 r1,0:98,A:2448546566;C:1819820402;G:2005413327;T:2187171703;N:17238408,98,,,,2448546566,1819820402,2005413327,2187171703,17238408,SRX24023800,SRS20818155,SRA1835509,Uppsala University,Uppsala University,1,0.91631,,0.11199,,0.82106,,0.54746,,98,,B,,usable mapping rate,illumina,hiseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,Sweden,2024-03-22,Larval,Larval,Trunk,Surface Structure
31526,SRR28419474,SRX24023799,SRS20818156,SRP497235,PRJNA1090867,Single cell RNA seq of zebrafish endothelial cells,GSE262232,Transcriptome Analysis,We performed single cell RNA sequencing scRNA seq for isolated endothelial cells Overall design: Tgkdrl:EGFP zebrafish embryos were digested into single cell suspension  EGFP positive cells were isolated using FACS and subjected to 10X Genomics Chromium scRNAseq.,,pubmed:39977018,,Zebrafish endothelial cells 3 dpf 1,GSM8160886,,source name:Whole body|tissue:Whole body|age:embryo|geo loc name:missing|collection date:missing,Zebrafish endothelial cells 3 dpf 1,Cell Ranger v2.1 was used to de multiplex raw base call BCL files generated by Illumina sequencers into FASTQ files  perform the alignment  barcode counting  and UMI counting. Assembly: GRCz11 Supplementary files format and content: Tab seprated values files,Whole body,,Whole Tgkdrl:EGFP zebrafish embryos were digested into single cell suspensions  EGFP positive cells were isolated using FACS Single cell suspension was loaded into the 10X Chromium system and cDNA libraries were constructed using Chromium Next GEM Single Cell 3′ GEM  Library and Gel Bead Kit v2 10X Genomics according to manufacturer’s protocol.,,tissue:Whole body|age:embryo,GSM8160886,GSM8160886: Zebrafish endothelial cells 3 dpf 1; Danio rerio; RNA Seq,GSM8160886 r1,GSM8160886,1,Whole Tgkdrl:EGFP zebrafish embryos were digested into single cell suspensions  EGFP positive cells were isolated using FACS Single cell suspension was loaded into the 10X Chromium system and cDNA libraries were constructed using Chromium Next GEM Single Cell 3′ GEM  Library and Gel Bead Kit v2 10X Genomics according to manufacturer's protocol.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina HiSeq 1500,,SRP497235,,assembly:GRCz11|intentional duplicate|dangling references:treat as unmapped|dangling references:skip reference resolution,3dpf_1_possorted_genome_bam.bam,10X Genomics bam file,2842123088.0,29001256.0,GSM8160886 r1,0:98,A:821846800;C:603425858;G:657525459;T:720690292;N:38634679,98,,,,821846800,603425858,657525459,720690292,38634679,SRX24023799,SRS20818156,SRA1835509,Uppsala University,Uppsala University,1,0.86292,,0.0954,,0.82844,,0.52761,,98,,B,,usable mapping rate,illumina,hiseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,Sweden,2024-03-22,Larval,Larval,Trunk,Surface Structure
31527,SRR28419475,SRX24023798,SRS20818154,SRP497235,PRJNA1090867,Single cell RNA seq of zebrafish endothelial cells,GSE262232,Transcriptome Analysis,We performed single cell RNA sequencing scRNA seq for isolated endothelial cells Overall design: Tgkdrl:EGFP zebrafish embryos were digested into single cell suspension  EGFP positive cells were isolated using FACS and subjected to 10X Genomics Chromium scRNAseq.,,pubmed:39977018,,Zebrafish endothelial cells 34 hpf,GSM8160885,,source name:Whole body|tissue:Whole body|age:embryo|geo loc name:missing|collection date:missing,Zebrafish endothelial cells 34 hpf,Cell Ranger v2.1 was used to de multiplex raw base call BCL files generated by Illumina sequencers into FASTQ files  perform the alignment  barcode counting  and UMI counting. Assembly: GRCz11 Supplementary files format and content: Tab seprated values files,Whole body,,Whole Tgkdrl:EGFP zebrafish embryos were digested into single cell suspensions  EGFP positive cells were isolated using FACS Single cell suspension was loaded into the 10X Chromium system and cDNA libraries were constructed using Chromium Next GEM Single Cell 3′ GEM  Library and Gel Bead Kit v2 10X Genomics according to manufacturer’s protocol.,,tissue:Whole body|age:embryo,GSM8160885,GSM8160885: Zebrafish endothelial cells 34 hpf; Danio rerio; RNA Seq,GSM8160885 r1,GSM8160885,1,Whole Tgkdrl:EGFP zebrafish embryos were digested into single cell suspensions  EGFP positive cells were isolated using FACS Single cell suspension was loaded into the 10X Chromium system and cDNA libraries were constructed using Chromium Next GEM Single Cell 3′ GEM  Library and Gel Bead Kit v2 10X Genomics according to manufacturer's protocol.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina HiSeq 1500,,SRP497235,,assembly:GRCz11|intentional duplicate|dangling references:treat as unmapped|dangling references:skip reference resolution,34hpf_possorted_genome_bam.bam,10X Genomics bam file,8518745844.0,86925978.0,GSM8160885 r1,0:98,A:2440648674;C:1828442217;G:2000096456;T:2232243146;N:17315351,98,,,,2440648674,1828442217,2000096456,2232243146,17315351,SRX24023798,SRS20818154,SRA1835509,Uppsala University,Uppsala University,1,0.92268,,0.1011,,0.82235,,0.50276,,98,,B,,usable mapping rate,illumina,hiseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,Sweden,2024-03-22,Pharyngula,Embryo,Trunk,Surface Structure
34500,SRR31853995,SRX27213775,SRS23662882,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.,,,,Control 10hr,GSM8703960,,source name:Body|tissue:Body|genotype:AB|age:6 dpf|treatment:control|geo loc name:missing|collection date:missing,Control 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,,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.,,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. 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.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP554457,,loader:fastq load.py,Control_S12_L001_I1_001.fastq.gz Control_S12_L001_R1_001.fastq.gz Control_S12_L001_R2_001.fastq.gz,fastq fastq fastq,54727297835.0,430923605.0,GSM8703960 r1,0:8 1:28 2:91,A:11073804966;C:8703587106;G:9746134722;T:9686959402;N:3561859,8,28,91,,11073804966,8703587106,9746134722,9686959402,3561859,SRX27213775,SRS23662882,SRA2042619,"Jerison, Physics, University of Chicago","Jerison, Physics, University of Chicago",,,,,,,,,,,,B,,usable mapping rate,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,United States,2024-12-30,Larval,Larval,Trunk,Surface Structure
34501,SRR31853996,SRX27213775,SRS23662882,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.,,,,Control 10hr,GSM8703960,,source name:Body|tissue:Body|genotype:AB|age:6 dpf|treatment:control|geo loc name:missing|collection date:missing,Control 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,,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.,,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. 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.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP554457,,loader:fastq load.py,Control_S12_L002_I1_001.fastq.gz Control_S12_L002_R1_001.fastq.gz Control_S12_L002_R2_001.fastq.gz,fastq fastq fastq,55269352123.0,435191749.0,GSM8703960 r2,0:8 1:28 2:91,A:11174489058;C:8794319355;G:9857401155;T:9771712847;N:4526744,8,28,91,,11174489058,8794319355,9857401155,9771712847,4526744,SRX27213775,SRS23662882,SRA2042619,"Jerison, Physics, University of Chicago","Jerison, Physics, University of Chicago",,,,,,,,,,,,B,,usable mapping rate,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,United States,2024-12-30,Larval,Larval,Trunk,Surface Structure
34502,SRR31853997,SRX27213775,SRS23662882,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.,,,,Control 10hr,GSM8703960,,source name:Body|tissue:Body|genotype:AB|age:6 dpf|treatment:control|geo loc name:missing|collection date:missing,Control 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,,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.,,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. 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.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP554457,,loader:fastq load.py,Control_S12_L003_I1_001.fastq.gz Control_S12_L003_R1_001.fastq.gz Control_S12_L003_R2_001.fastq.gz,fastq fastq fastq,56713746491.0,446564933.0,GSM8703960 r3,0:8 1:28 2:91,A:11445709349;C:9041805308;G:10134400820;T:10010485583;N:5007843,8,28,91,,11445709349,9041805308,10134400820,10010485583,5007843,SRX27213775,SRS23662882,SRA2042619,"Jerison, Physics, University of Chicago","Jerison, Physics, University of Chicago",,,,,,,,,,,,B,,usable mapping rate,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,United States,2024-12-30,Larval,Larval,Trunk,Surface Structure
34503,SRR31853998,SRX27213775,SRS23662882,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.,,,,Control 10hr,GSM8703960,,source name:Body|tissue:Body|genotype:AB|age:6 dpf|treatment:control|geo loc name:missing|collection date:missing,Control 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,,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.,,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. 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.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP554457,,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,,11203472019,8826429348,9895249162,9793520783,4749425,SRX27213775,SRS23662882,SRA2042619,"Jerison, Physics, University of Chicago","Jerison, Physics, University of Chicago",,,,,,,,,,,,B,,usable mapping rate,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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.,,,,LPS 10hr,GSM8703959,,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,,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.,,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.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP554457,,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,,5353386805,4418850048,5242873068,4476300884,1645414,SRX27213774,SRS23662881,SRA2042619,"Jerison, Physics, University of Chicago","Jerison, Physics, University of Chicago",,,,,,,,,,,,B,,usable mapping rate,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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.,,,,LPS 10hr,GSM8703959,,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,,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.,,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.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP554457,,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,,5407507765,4472892263,5312032344,4520956753,2044522,SRX27213774,SRS23662881,SRA2042619,"Jerison, Physics, University of Chicago","Jerison, Physics, University of Chicago",,,,,,,,,,,,B,,usable mapping rate,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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.,,,,LPS 10hr,GSM8703959,,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,,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.,,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.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP554457,,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,,5590192273,4644899622,5516199030,4676442556,2367665,SRX27213774,SRS23662881,SRA2042619,"Jerison, Physics, University of Chicago","Jerison, Physics, University of Chicago",,,,,,,,,,,,B,,usable mapping rate,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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.,,,,LPS 10hr,GSM8703959,,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,,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.,,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.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP554457,,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,,5383218071,4459553243,5297438054,4498601355,2212861,SRX27213774,SRS23662881,SRA2042619,"Jerison, Physics, University of Chicago","Jerison, Physics, University of Chicago",,,,,,,,,,,,B,,usable mapping rate,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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.,,,,larval trunk  2dpi Needle Stick,GSM9034433,,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 “cellranger mkref” 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 “cellranger count” 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 “cellranger count” 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 “SCTransform” 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 “SelectIntegrationFeatures” function nfeatures = 6000  which was used as input for the“anchor.features” argument of the “FindIntegrationAnchors” 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 “FindNeighbors” and “FindClusters” 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 “FindClusters” function. The resolution parameter res = 0.3 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 “RunUMAP” function Becht et al.  2018. Data was graphed using different plot functions  such as “DimPlot”  “VlnPlot”  “FeaturePlot”  “Dotplot” and “DoHeatmap”  to view the cell cluster identity and marker gene expression. Cell proportions were extracted using the “table” and “prop.table” functions. Differential gene expression for individual clusters was identified using Wilcoxon rank sum test in the “FindAllMarkers” 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 “subset” function for subcluster analysis. The muscle subset was again normalized and scaled using the “SCTransform” 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 “DE Marker Scoring” 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 “phyper” 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. −log10 of probability values were obtained for plotting the heatmap Table S2  sheet:−log10P. 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 −log10 p score obtained in the heatmap. The top DE markers of clusters with ambiguous scores were manually annotated using the “ident genes” 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 “RenameIdents” 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 “createCellChat” 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 “netAnalysis computeCentrality” function was used to calculate network centrality scores at each time point. Functions such as “netVisual circle”  “netAnalysis contribution”  “netVisual aggregate”  “netVisual bubble”  “netAnalysis signalingRole heatmap”  and “netAnalysis signalingRole scatter” 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  500μL 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 °C 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°C  the supernatant was discarded  and the pellet was resuspended in 100μL of resuspension buffer 1% FBS  2mM CaCl2  1X Penicillin/Streptomycin  in DMEM. The suspension was strained through 20μm cell strainer Pluriselect USA  43 10020  40  centrifuged once 500rcf  1 min  4°C to pass cells through the strainer  and centrifuged a second time 750rcf  7 min  4°C to pellet the cells. The cells were resuspended in 100μL of resuspension buffer  centrifugated 750rcf  7min  4°C  and the pellet was resuspended in 50μL 0.04% BSA in PBS. 5μl of cells were then combined with 5μl of Hoechst Invitrogen  H3570  incubated for 10min  and transferred to a hemocytometer Bulldogbio  NC1731934 to determine cell concentration. An additional 5μl 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 µl of isolated nuclei at a concentration of 1000 nuclei/µl 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’ 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’ 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.,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  500μL 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 °C 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°C  the supernatant was discarded  and the pellet was resuspended in 100μL of resuspension buffer 1% FBS  2mM CaCl2  1X Penicillin/Streptomycin  in DMEM. The suspension was strained through 20μm cell strainer Pluriselect USA  43 10020  40  centrifuged once 500rcf  1 min  4°C to pass cells through the strainer  and centrifuged a second time 750rcf  7 min  4°C to pellet the cells. The cells were resuspended in 100μL of resuspension buffer  centrifugated 750rcf  7min  4°C  and the pellet was resuspended in 50μL 0.04% BSA in PBS. 5μl of cells were then combined with 5μl of Hoechst Invitrogen  H3570  incubated for 10min  and transferred to a hemocytometer Bulldogbio  NC1731934 to determine cell concentration. An additional 5μl 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 µl of isolated nuclei at a concentration of 1000 nuclei/µl 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.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP590547,,,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,,,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",,,,,,,,,,,,T,B,sc-like readlen,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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.,,,,larval trunk  4dpi mcherry MTZ,GSM9034432,,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 “cellranger mkref” 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 “cellranger count” 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 “cellranger count” 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 “SCTransform” 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 “SelectIntegrationFeatures” function nfeatures = 6000  which was used as input for the“anchor.features” argument of the “FindIntegrationAnchors” 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 “FindNeighbors” and “FindClusters” 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 “FindClusters” function. The resolution parameter res = 0.3 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 “RunUMAP” function Becht et al.  2018. Data was graphed using different plot functions  such as “DimPlot”  “VlnPlot”  “FeaturePlot”  “Dotplot” and “DoHeatmap”  to view the cell cluster identity and marker gene expression. Cell proportions were extracted using the “table” and “prop.table” functions. Differential gene expression for individual clusters was identified using Wilcoxon rank sum test in the “FindAllMarkers” 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 “subset” function for subcluster analysis. The muscle subset was again normalized and scaled using the “SCTransform” 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 “DE Marker Scoring” 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 “phyper” 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. −log10 of probability values were obtained for plotting the heatmap Table S2  sheet:−log10P. 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 −log10 p score obtained in the heatmap. The top DE markers of clusters with ambiguous scores were manually annotated using the “ident genes” 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 “RenameIdents” 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 “createCellChat” 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 “netAnalysis computeCentrality” function was used to calculate network centrality scores at each time point. Functions such as “netVisual circle”  “netAnalysis contribution”  “netVisual aggregate”  “netVisual bubble”  “netAnalysis signalingRole heatmap”  and “netAnalysis signalingRole scatter” 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  500μL 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 °C 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°C  the supernatant was discarded  and the pellet was resuspended in 100μL of resuspension buffer 1% FBS  2mM CaCl2  1X Penicillin/Streptomycin  in DMEM. The suspension was strained through 20μm cell strainer Pluriselect USA  43 10020  40  centrifuged once 500rcf  1 min  4°C to pass cells through the strainer  and centrifuged a second time 750rcf  7 min  4°C to pellet the cells. The cells were resuspended in 100μL of resuspension buffer  centrifugated 750rcf  7min  4°C  and the pellet was resuspended in 50μL 0.04% BSA in PBS. 5μl of cells were then combined with 5μl of Hoechst Invitrogen  H3570  incubated for 10min  and transferred to a hemocytometer Bulldogbio  NC1731934 to determine cell concentration. An additional 5μl 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 µl of isolated nuclei at a concentration of 1000 nuclei/µl 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’ 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’ 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.,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  500μL 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 °C 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°C  the supernatant was discarded  and the pellet was resuspended in 100μL of resuspension buffer 1% FBS  2mM CaCl2  1X Penicillin/Streptomycin  in DMEM. The suspension was strained through 20μm cell strainer Pluriselect USA  43 10020  40  centrifuged once 500rcf  1 min  4°C to pass cells through the strainer  and centrifuged a second time 750rcf  7 min  4°C to pellet the cells. The cells were resuspended in 100μL of resuspension buffer  centrifugated 750rcf  7min  4°C  and the pellet was resuspended in 50μL 0.04% BSA in PBS. 5μl of cells were then combined with 5μl of Hoechst Invitrogen  H3570  incubated for 10min  and transferred to a hemocytometer Bulldogbio  NC1731934 to determine cell concentration. An additional 5μl 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 µl of isolated nuclei at a concentration of 1000 nuclei/µl 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.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP590547,,,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,,,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",,,,,,,,,,,,T,B,sc-like readlen,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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.,,,,larval trunk  4dpi Negative Control,GSM9034431,,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 “cellranger mkref” 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 “cellranger count” 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 “cellranger count” 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 “SCTransform” 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 “SelectIntegrationFeatures” function nfeatures = 6000  which was used as input for the“anchor.features” argument of the “FindIntegrationAnchors” 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 “FindNeighbors” and “FindClusters” 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 “FindClusters” function. The resolution parameter res = 0.3 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 “RunUMAP” function Becht et al.  2018. Data was graphed using different plot functions  such as “DimPlot”  “VlnPlot”  “FeaturePlot”  “Dotplot” and “DoHeatmap”  to view the cell cluster identity and marker gene expression. Cell proportions were extracted using the “table” and “prop.table” functions. Differential gene expression for individual clusters was identified using Wilcoxon rank sum test in the “FindAllMarkers” 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 “subset” function for subcluster analysis. The muscle subset was again normalized and scaled using the “SCTransform” 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 “DE Marker Scoring” 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 “phyper” 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. −log10 of probability values were obtained for plotting the heatmap Table S2  sheet:−log10P. 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 −log10 p score obtained in the heatmap. The top DE markers of clusters with ambiguous scores were manually annotated using the “ident genes” 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 “RenameIdents” 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 “createCellChat” 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 “netAnalysis computeCentrality” function was used to calculate network centrality scores at each time point. Functions such as “netVisual circle”  “netAnalysis contribution”  “netVisual aggregate”  “netVisual bubble”  “netAnalysis signalingRole heatmap”  and “netAnalysis signalingRole scatter” 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  500μL 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 °C 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°C  the supernatant was discarded  and the pellet was resuspended in 100μL of resuspension buffer 1% FBS  2mM CaCl2  1X Penicillin/Streptomycin  in DMEM. The suspension was strained through 20μm cell strainer Pluriselect USA  43 10020  40  centrifuged once 500rcf  1 min  4°C to pass cells through the strainer  and centrifuged a second time 750rcf  7 min  4°C to pellet the cells. The cells were resuspended in 100μL of resuspension buffer  centrifugated 750rcf  7min  4°C  and the pellet was resuspended in 50μL 0.04% BSA in PBS. 5μl of cells were then combined with 5μl of Hoechst Invitrogen  H3570  incubated for 10min  and transferred to a hemocytometer Bulldogbio  NC1731934 to determine cell concentration. An additional 5μl 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 µl of isolated nuclei at a concentration of 1000 nuclei/µl 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’ 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’ 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.,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  500μL 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 °C 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°C  the supernatant was discarded  and the pellet was resuspended in 100μL of resuspension buffer 1% FBS  2mM CaCl2  1X Penicillin/Streptomycin  in DMEM. The suspension was strained through 20μm cell strainer Pluriselect USA  43 10020  40  centrifuged once 500rcf  1 min  4°C to pass cells through the strainer  and centrifuged a second time 750rcf  7 min  4°C to pellet the cells. The cells were resuspended in 100μL of resuspension buffer  centrifugated 750rcf  7min  4°C  and the pellet was resuspended in 50μL 0.04% BSA in PBS. 5μl of cells were then combined with 5μl of Hoechst Invitrogen  H3570  incubated for 10min  and transferred to a hemocytometer Bulldogbio  NC1731934 to determine cell concentration. An additional 5μl 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 µl of isolated nuclei at a concentration of 1000 nuclei/µl 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.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP590547,,,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,,,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",,,,,,,,,,,,T,B,sc-like readlen,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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.,,,,larval trunk  2dpi mcherry MTZ,GSM9034430,,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 “cellranger mkref” 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 “cellranger count” 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 “cellranger count” 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 “SCTransform” 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 “SelectIntegrationFeatures” function nfeatures = 6000  which was used as input for the“anchor.features” argument of the “FindIntegrationAnchors” 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 “FindNeighbors” and “FindClusters” 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 “FindClusters” function. The resolution parameter res = 0.3 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 “RunUMAP” function Becht et al.  2018. Data was graphed using different plot functions  such as “DimPlot”  “VlnPlot”  “FeaturePlot”  “Dotplot” and “DoHeatmap”  to view the cell cluster identity and marker gene expression. Cell proportions were extracted using the “table” and “prop.table” functions. Differential gene expression for individual clusters was identified using Wilcoxon rank sum test in the “FindAllMarkers” 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 “subset” function for subcluster analysis. The muscle subset was again normalized and scaled using the “SCTransform” 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 “DE Marker Scoring” 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 “phyper” 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. −log10 of probability values were obtained for plotting the heatmap Table S2  sheet:−log10P. 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 −log10 p score obtained in the heatmap. The top DE markers of clusters with ambiguous scores were manually annotated using the “ident genes” 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 “RenameIdents” 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 “createCellChat” 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 “netAnalysis computeCentrality” function was used to calculate network centrality scores at each time point. Functions such as “netVisual circle”  “netAnalysis contribution”  “netVisual aggregate”  “netVisual bubble”  “netAnalysis signalingRole heatmap”  and “netAnalysis signalingRole scatter” 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  500μL 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 °C 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°C  the supernatant was discarded  and the pellet was resuspended in 100μL of resuspension buffer 1% FBS  2mM CaCl2  1X Penicillin/Streptomycin  in DMEM. The suspension was strained through 20μm cell strainer Pluriselect USA  43 10020  40  centrifuged once 500rcf  1 min  4°C to pass cells through the strainer  and centrifuged a second time 750rcf  7 min  4°C to pellet the cells. The cells were resuspended in 100μL of resuspension buffer  centrifugated 750rcf  7min  4°C  and the pellet was resuspended in 50μL 0.04% BSA in PBS. 5μl of cells were then combined with 5μl of Hoechst Invitrogen  H3570  incubated for 10min  and transferred to a hemocytometer Bulldogbio  NC1731934 to determine cell concentration. An additional 5μl 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 µl of isolated nuclei at a concentration of 1000 nuclei/µl 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’ 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’ 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.,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  500μL 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 °C 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°C  the supernatant was discarded  and the pellet was resuspended in 100μL of resuspension buffer 1% FBS  2mM CaCl2  1X Penicillin/Streptomycin  in DMEM. The suspension was strained through 20μm cell strainer Pluriselect USA  43 10020  40  centrifuged once 500rcf  1 min  4°C to pass cells through the strainer  and centrifuged a second time 750rcf  7 min  4°C to pellet the cells. The cells were resuspended in 100μL of resuspension buffer  centrifugated 750rcf  7min  4°C  and the pellet was resuspended in 50μL 0.04% BSA in PBS. 5μl of cells were then combined with 5μl of Hoechst Invitrogen  H3570  incubated for 10min  and transferred to a hemocytometer Bulldogbio  NC1731934 to determine cell concentration. An additional 5μl 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 µl of isolated nuclei at a concentration of 1000 nuclei/µl 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.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP590547,,,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,,,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,,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.,,,,larval trunk  2dpi Negative Control,GSM9034429,,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 “cellranger mkref” 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 “cellranger count” 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 “cellranger count” 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 “SCTransform” 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 “SelectIntegrationFeatures” function nfeatures = 6000  which was used as input for the“anchor.features” argument of the “FindIntegrationAnchors” 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 “FindNeighbors” and “FindClusters” 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 “FindClusters” function. The resolution parameter res = 0.3 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 “RunUMAP” function Becht et al.  2018. Data was graphed using different plot functions  such as “DimPlot”  “VlnPlot”  “FeaturePlot”  “Dotplot” and “DoHeatmap”  to view the cell cluster identity and marker gene expression. Cell proportions were extracted using the “table” and “prop.table” functions. Differential gene expression for individual clusters was identified using Wilcoxon rank sum test in the “FindAllMarkers” 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 “subset” function for subcluster analysis. The muscle subset was again normalized and scaled using the “SCTransform” 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 “DE Marker Scoring” 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 “phyper” 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. −log10 of probability values were obtained for plotting the heatmap Table S2  sheet:−log10P. 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 −log10 p score obtained in the heatmap. The top DE markers of clusters with ambiguous scores were manually annotated using the “ident genes” 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 “RenameIdents” 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 “createCellChat” 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 “netAnalysis computeCentrality” function was used to calculate network centrality scores at each time point. Functions such as “netVisual circle”  “netAnalysis contribution”  “netVisual aggregate”  “netVisual bubble”  “netAnalysis signalingRole heatmap”  and “netAnalysis signalingRole scatter” 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  500μL 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 °C 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°C  the supernatant was discarded  and the pellet was resuspended in 100μL of resuspension buffer 1% FBS  2mM CaCl2  1X Penicillin/Streptomycin  in DMEM. The suspension was strained through 20μm cell strainer Pluriselect USA  43 10020  40  centrifuged once 500rcf  1 min  4°C to pass cells through the strainer  and centrifuged a second time 750rcf  7 min  4°C to pellet the cells. The cells were resuspended in 100μL of resuspension buffer  centrifugated 750rcf  7min  4°C  and the pellet was resuspended in 50μL 0.04% BSA in PBS. 5μl of cells were then combined with 5μl of Hoechst Invitrogen  H3570  incubated for 10min  and transferred to a hemocytometer Bulldogbio  NC1731934 to determine cell concentration. An additional 5μl 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 µl of isolated nuclei at a concentration of 1000 nuclei/µl 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’ 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’ 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.,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  500μL 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 °C 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°C  the supernatant was discarded  and the pellet was resuspended in 100μL of resuspension buffer 1% FBS  2mM CaCl2  1X Penicillin/Streptomycin  in DMEM. The suspension was strained through 20μm cell strainer Pluriselect USA  43 10020  40  centrifuged once 500rcf  1 min  4°C to pass cells through the strainer  and centrifuged a second time 750rcf  7 min  4°C to pellet the cells. The cells were resuspended in 100μL of resuspension buffer  centrifugated 750rcf  7min  4°C  and the pellet was resuspended in 50μL 0.04% BSA in PBS. 5μl of cells were then combined with 5μl of Hoechst Invitrogen  H3570  incubated for 10min  and transferred to a hemocytometer Bulldogbio  NC1731934 to determine cell concentration. An additional 5μl 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 µl of isolated nuclei at a concentration of 1000 nuclei/µl 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.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP590547,,,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,,,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,,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.,,,,larval trunk  1dpi mcherry MTZ,GSM9034428,,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 “cellranger mkref” 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 “cellranger count” 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 “cellranger count” 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 “SCTransform” 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 “SelectIntegrationFeatures” function nfeatures = 6000  which was used as input for the“anchor.features” argument of the “FindIntegrationAnchors” 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 “FindNeighbors” and “FindClusters” 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 “FindClusters” function. The resolution parameter res = 0.3 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 “RunUMAP” function Becht et al.  2018. Data was graphed using different plot functions  such as “DimPlot”  “VlnPlot”  “FeaturePlot”  “Dotplot” and “DoHeatmap”  to view the cell cluster identity and marker gene expression. Cell proportions were extracted using the “table” and “prop.table” functions. Differential gene expression for individual clusters was identified using Wilcoxon rank sum test in the “FindAllMarkers” 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 “subset” function for subcluster analysis. The muscle subset was again normalized and scaled using the “SCTransform” 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 “DE Marker Scoring” 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 “phyper” 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. −log10 of probability values were obtained for plotting the heatmap Table S2  sheet:−log10P. 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 −log10 p score obtained in the heatmap. The top DE markers of clusters with ambiguous scores were manually annotated using the “ident genes” 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 “RenameIdents” 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 “createCellChat” 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 “netAnalysis computeCentrality” function was used to calculate network centrality scores at each time point. Functions such as “netVisual circle”  “netAnalysis contribution”  “netVisual aggregate”  “netVisual bubble”  “netAnalysis signalingRole heatmap”  and “netAnalysis signalingRole scatter” 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  500μL 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 °C 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°C  the supernatant was discarded  and the pellet was resuspended in 100μL of resuspension buffer 1% FBS  2mM CaCl2  1X Penicillin/Streptomycin  in DMEM. The suspension was strained through 20μm cell strainer Pluriselect USA  43 10020  40  centrifuged once 500rcf  1 min  4°C to pass cells through the strainer  and centrifuged a second time 750rcf  7 min  4°C to pellet the cells. The cells were resuspended in 100μL of resuspension buffer  centrifugated 750rcf  7min  4°C  and the pellet was resuspended in 50μL 0.04% BSA in PBS. 5μl of cells were then combined with 5μl of Hoechst Invitrogen  H3570  incubated for 10min  and transferred to a hemocytometer Bulldogbio  NC1731934 to determine cell concentration. An additional 5μl 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 µl of isolated nuclei at a concentration of 1000 nuclei/µl 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’ 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’ 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.,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  500μL 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 °C 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°C  the supernatant was discarded  and the pellet was resuspended in 100μL of resuspension buffer 1% FBS  2mM CaCl2  1X Penicillin/Streptomycin  in DMEM. The suspension was strained through 20μm cell strainer Pluriselect USA  43 10020  40  centrifuged once 500rcf  1 min  4°C to pass cells through the strainer  and centrifuged a second time 750rcf  7 min  4°C to pellet the cells. The cells were resuspended in 100μL of resuspension buffer  centrifugated 750rcf  7min  4°C  and the pellet was resuspended in 50μL 0.04% BSA in PBS. 5μl of cells were then combined with 5μl of Hoechst Invitrogen  H3570  incubated for 10min  and transferred to a hemocytometer Bulldogbio  NC1731934 to determine cell concentration. An additional 5μl 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 µl of isolated nuclei at a concentration of 1000 nuclei/µl 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.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP590547,,,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,,,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,,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.,,,,larval trunk  1dpi Negative Control,GSM9034427,,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 “cellranger mkref” 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 “cellranger count” 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 “cellranger count” 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 “SCTransform” 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 “SelectIntegrationFeatures” function nfeatures = 6000  which was used as input for the“anchor.features” argument of the “FindIntegrationAnchors” 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 “FindNeighbors” and “FindClusters” 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 “FindClusters” function. The resolution parameter res = 0.3 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 “RunUMAP” function Becht et al.  2018. Data was graphed using different plot functions  such as “DimPlot”  “VlnPlot”  “FeaturePlot”  “Dotplot” and “DoHeatmap”  to view the cell cluster identity and marker gene expression. Cell proportions were extracted using the “table” and “prop.table” functions. Differential gene expression for individual clusters was identified using Wilcoxon rank sum test in the “FindAllMarkers” 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 “subset” function for subcluster analysis. The muscle subset was again normalized and scaled using the “SCTransform” 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 “DE Marker Scoring” 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 “phyper” 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. −log10 of probability values were obtained for plotting the heatmap Table S2  sheet:−log10P. 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 −log10 p score obtained in the heatmap. The top DE markers of clusters with ambiguous scores were manually annotated using the “ident genes” 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 “RenameIdents” 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 “createCellChat” 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 “netAnalysis computeCentrality” function was used to calculate network centrality scores at each time point. Functions such as “netVisual circle”  “netAnalysis contribution”  “netVisual aggregate”  “netVisual bubble”  “netAnalysis signalingRole heatmap”  and “netAnalysis signalingRole scatter” 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  500μL 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 °C 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°C  the supernatant was discarded  and the pellet was resuspended in 100μL of resuspension buffer 1% FBS  2mM CaCl2  1X Penicillin/Streptomycin  in DMEM. The suspension was strained through 20μm cell strainer Pluriselect USA  43 10020  40  centrifuged once 500rcf  1 min  4°C to pass cells through the strainer  and centrifuged a second time 750rcf  7 min  4°C to pellet the cells. The cells were resuspended in 100μL of resuspension buffer  centrifugated 750rcf  7min  4°C  and the pellet was resuspended in 50μL 0.04% BSA in PBS. 5μl of cells were then combined with 5μl of Hoechst Invitrogen  H3570  incubated for 10min  and transferred to a hemocytometer Bulldogbio  NC1731934 to determine cell concentration. An additional 5μl 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 µl of isolated nuclei at a concentration of 1000 nuclei/µl 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’ 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’ 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.,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  500μL 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 °C 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°C  the supernatant was discarded  and the pellet was resuspended in 100μL of resuspension buffer 1% FBS  2mM CaCl2  1X Penicillin/Streptomycin  in DMEM. The suspension was strained through 20μm cell strainer Pluriselect USA  43 10020  40  centrifuged once 500rcf  1 min  4°C to pass cells through the strainer  and centrifuged a second time 750rcf  7 min  4°C to pellet the cells. The cells were resuspended in 100μL of resuspension buffer  centrifugated 750rcf  7min  4°C  and the pellet was resuspended in 50μL 0.04% BSA in PBS. 5μl of cells were then combined with 5μl of Hoechst Invitrogen  H3570  incubated for 10min  and transferred to a hemocytometer Bulldogbio  NC1731934 to determine cell concentration. An additional 5μl 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 µl of isolated nuclei at a concentration of 1000 nuclei/µl 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.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP590547,,,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,,,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,,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.,,pubmed:29644996,,Larva F1 2 scar,GSM3032175,,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,,Single cell dissociation. 10X Genomics Chromium,,strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva,GSM3032175,GSM3032175: Larva F1 2 scar; Danio rerio; OTHER,GSM3032175,,1,Single cell dissociation. 10X Genomics Chromium,GEO Accession:GSM3032175,OTHER,TRANSCRIPTOMIC,other,PAIRED,ILLUMINA,Illumina HiSeq 2500,,SRP121343,,,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,,,2682085389,3008788535,2093169318,1516220703,1664627,SRX3768872,SRS3023386,SRA623333,GEO,Max Delbrück 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,,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.,,pubmed:29644996,,Larva F1 1 scar,GSM3032174,,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,,Single cell dissociation. 10X Genomics Chromium,,strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva,GSM3032174,GSM3032174: Larva F1 1 scar; Danio rerio; OTHER,GSM3032174,,1,Single cell dissociation. 10X Genomics Chromium,GEO Accession:GSM3032174,OTHER,TRANSCRIPTOMIC,other,PAIRED,ILLUMINA,Illumina HiSeq 2500,,SRP121343,,,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,,,2222016153,2555237987,1722216404,1271855931,1387101,SRX3768871,SRS3023388,SRA623333,GEO,Max Delbrück 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,,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.,,pubmed:29644996,,Larva F1 2 mRNA,GSM3032173,,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,,Single cell dissociation. 10X Genomics Chromium,,strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva,GSM3032173,GSM3032173: Larva F1 2 mRNA; Danio rerio; RNA Seq,GSM3032173,,1,Single cell dissociation. 10X Genomics Chromium,GEO Accession:GSM3032173,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina HiSeq 2500,,SRP121343,,,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,,,8264355452,6830431714,7093261338,7804053400,5378804,SRX3768870,SRS3023387,SRA623333,GEO,Max Delbrück 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,,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.,,pubmed:29644996,,Larva F1 1 mRNA,GSM3032172,,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,,Single cell dissociation. 10X Genomics Chromium,,strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva,GSM3032172,GSM3032172: Larva F1 1 mRNA; Danio rerio; RNA Seq,GSM3032172,,1,Single cell dissociation. 10X Genomics Chromium,GEO Accession:GSM3032172,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina HiSeq 2500,,SRP121343,,,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,,,7365353958,6068313931,6251004125,6996410946,4793112,SRX3768869,SRS3023385,SRA623333,GEO,Max Delbrück 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,,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.,,pubmed:29644996,,Larva 5 scar,GSM3032167,,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,,Single cell dissociation. 10X Genomics Chromium,,strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva,GSM3032167,GSM3032167: Larva 5 scar; Danio rerio; OTHER,GSM3032167,,1,Single cell dissociation. 10X Genomics Chromium,GEO Accession:GSM3032167,OTHER,TRANSCRIPTOMIC,other,PAIRED,ILLUMINA,Illumina HiSeq 2500,,SRP121343,,,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,,,2173948352,2439410929,1714624642,1343296377,1365400,SRX3768864,SRS3023381,SRA623333,GEO,Max Delbrück 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,,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.,,pubmed:29644996,,Larva 4 scar,GSM3032166,,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,,Single cell dissociation. 10X Genomics Chromium,,strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva,GSM3032166,GSM3032166: Larva 4 scar; Danio rerio; OTHER,GSM3032166,,1,Single cell dissociation. 10X Genomics Chromium,GEO Accession:GSM3032166,OTHER,TRANSCRIPTOMIC,other,PAIRED,ILLUMINA,Illumina HiSeq 2500,,SRP121343,,,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,,,2080254513,2296727471,1625115068,1232786300,1300452,SRX3768863,SRS3023380,SRA623333,GEO,Max Delbrück 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,,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.,,pubmed:29644996,,Larva 5 mRNA,GSM3032161,,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,,Single cell dissociation. 10X Genomics Chromium,,strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva,GSM3032161,GSM3032161: Larva 5 mRNA; Danio rerio; RNA Seq,GSM3032161,,1,Single cell dissociation. 10X Genomics Chromium,GEO Accession:GSM3032161,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina HiSeq 2500,,SRP121343,,,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,,,7637677199,6210942203,6438364980,7117667800,4904630,SRX3768858,SRS3023376,SRA623333,GEO,Max Delbrück 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,,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.,,pubmed:29644996,,Larva 4 mRNA,GSM3032160,,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,,Single cell dissociation. 10X Genomics Chromium,,strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva,GSM3032160,GSM3032160: Larva 4 mRNA; Danio rerio; RNA Seq,GSM3032160,,1,Single cell dissociation. 10X Genomics Chromium,GEO Accession:GSM3032160,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina HiSeq 2500,,SRP121343,,,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,,,5483727144,4548396363,4737957565,5002119078,3511306,SRX3768857,SRS3023374,SRA623333,GEO,Max Delbrück 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,,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.,,pubmed:29644996,,Larva 3 mRNA,GSM3032159,,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,,Single cell dissociation. 10X Genomics Chromium,,strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva,GSM3032159,GSM3032159: Larva 3 mRNA; Danio rerio; RNA Seq,GSM3032159,,1,Single cell dissociation. 10X Genomics Chromium,GEO Accession:GSM3032159,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina HiSeq 2500,,SRP121343,,,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,,2047850756,1318672327,1403772432,1743394108,52287,SRX3768856,SRS3023373,SRA623333,GEO,Max Delbrück Center,1,0.87661,,0.06466,,0.86614,,0.53364,,130,,B,,usable mapping rate,illumina,hiseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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.,,pubmed:29644996,,Larva 2 mRNA,GSM2830057,,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 Grün 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 – 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,,Single cell dissociation. 10X Genomics Chromium,,strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva,GSM2830057,GSM2830057: Larva 2 mRNA; Danio rerio; RNA Seq,GSM2830057,,1,Single cell dissociation. 10X Genomics Chromium,GEO Accession:GSM2830057,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina HiSeq 2500,,SRP121343,,,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,,6582076349,4985163175,5131319282,6085835988,3297756,SRX3320762,SRS2626335,SRA623333,GEO,Max Delbrück Center,1,0.9378,,0.05825,,0.79687,,0.50342,,98,,B,,usable mapping rate,illumina,hiseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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.,,pubmed:29644996,,Larva 1 mRNA,GSM2830056,,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 Grün 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 – 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,,Single cell dissociation. 10X Genomics Chromium,,strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva,GSM2830056,GSM2830056: Larva 1 mRNA; Danio rerio; RNA Seq,GSM2830056,,1,Single cell dissociation. 10X Genomics Chromium,GEO Accession:GSM2830056,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina HiSeq 2500,,SRP121343,,,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,,9121762570,5889322717,6251660049,8039869338,228116,SRX3320760,SRS2626333,SRA623333,GEO,Max Delbrück Center,1,0.88569,,0.08353,,0.86016,,0.53379,,130,,B,,usable mapping rate,illumina,hiseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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.,,pubmed:29644996,,Larva 1 mRNA,GSM2830056,,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 Grün 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 – 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,,Single cell dissociation. 10X Genomics Chromium,,strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva,GSM2830056,GSM2830056: Larva 1 mRNA; Danio rerio; RNA Seq,GSM2830056,,1,Single cell dissociation. 10X Genomics Chromium,GEO Accession:GSM2830056,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina HiSeq 2500,,SRP121343,,,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,,1890861891,1307860042,1403340071,1654667424,45902,SRX3320760,SRS2626333,SRA623333,GEO,Max Delbrück Center,1,0.89198,,0.07477,,0.87288,,0.49519,,130,,B,,usable mapping rate,illumina,hiseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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.,,pubmed:29644996,,Larva 1 scar,GSM2830049,,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,,Single cell dissociation. 10X Genomics Chromium,,strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva,GSM2830049,GSM2830049: Larva 1 scar; Danio rerio; OTHER,GSM2830049,,1,Single cell dissociation. 10X Genomics Chromium,GEO Accession:GSM2830049,OTHER,TRANSCRIPTOMIC,other,PAIRED,ILLUMINA,Illumina HiSeq 2500,,SRP121343,,,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,,286107087,390283378,268551180,159171790,5555,SRX3320753,SRS2626327,SRA623333,GEO,Max Delbrück Center,1,0.00515,,8e-05,,0.99959,,0.24561,,130,,T,,under 1.2% mapping rate,illumina,hiseq_era,unknown,other,unknown,sc,single_cell_droplet,10x,,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.,,pubmed:29644996,,Larva 1 scar,GSM2830049,,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,,Single cell dissociation. 10X Genomics Chromium,,strain/background:Zebrabow M|tissue:Whole body|developmental stage:Larva,GSM2830049,GSM2830049: Larva 1 scar; Danio rerio; OTHER,GSM2830049,,1,Single cell dissociation. 10X Genomics Chromium,GEO Accession:GSM2830049,OTHER,TRANSCRIPTOMIC,other,PAIRED,ILLUMINA,Illumina HiSeq 2500,,SRP121343,,,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,,232542409,315925727,218437491,129610895,4168,SRX3320753,SRS2626327,SRA623333,GEO,Max Delbrück Center,1,0.00786,,0.0,,0.99922,,0.31764,,130,,T,,under 1.2% mapping rate,illumina,hiseq_era,unknown,other,unknown,sc,single_cell_droplet,10x,,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.,,pubmed:31140974;pubmed:33933422,,Neural crest derived cells from hypothyroid  post embryonic zebrafish trunks  biological replicate 7,GSM3764578,,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 °C 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,,1,10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,NextSeq 500,,SRP198298,,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,,,,1897524564,1180297377,1360942367,1732425907,3368643,SRX5827022,SRS4754836,SRA886020,GEO,"Biology, University of Virginia",1,0.91289,,0.25388,,0.82856,,0.50847,,57,,B,,usable mapping rate,illumina,nextseq,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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.,,pubmed:31140974;pubmed:33933422,,Neural crest derived cells from hypothyroid  post embryonic zebrafish trunks  biological replicate 6,GSM3764577,,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 °C 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,,1,10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,NextSeq 500,,SRP198298,,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,,,,1320513576,874241368,1044266437,1169033783,2222423,SRX5827021,SRS4754835,SRA886020,GEO,"Biology, University of Virginia",1,0.92536,,0.20155,,0.83473,,0.50983,,57,,B,,usable mapping rate,illumina,nextseq,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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.,,pubmed:31140974;pubmed:33933422,,Neural crest derived cells from hypothyroid  post embryonic zebrafish trunks  biological replicate 5,GSM3764576,,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 °C 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,,1,10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,NextSeq 500,,SRP198298,,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,,,,2380116568,1626615273,2248860789,2185343861,3296247,SRX5827020,SRS4754834,SRA886020,GEO,"Biology, University of Virginia",1,0.91177,,0.16393,,0.80509,,0.514,,57,,B,,usable mapping rate,illumina,nextseq,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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.,,pubmed:31140974;pubmed:33933422,,Neural crest derived cells from hypothyroid  post embryonic zebrafish trunks  biological replicate 4,GSM3764575,,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 °C 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,,1,10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,NextSeq 500,,SRP198298,,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,,,,2469579044,1654897730,2303443265,2280478208,3403207,SRX5827019,SRS4754833,SRA886020,GEO,"Biology, University of Virginia",1,0.90749,,0.17908,,0.8017,,0.5124,,57,,B,,usable mapping rate,illumina,nextseq,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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.,,pubmed:31140974;pubmed:33933422,,Neural crest derived cells from hypothyroid  post embryonic zebrafish trunks  biological replicate 3,GSM3764574,,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 °C 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,,1,10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,NextSeq 500,,SRP198298,,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,,,,4458931221,3243678800,3916155957,3908839406,3221381,SRX5827018,SRS4754832,SRA886020,GEO,"Biology, University of Virginia",1,0.94166,,0.13327,,0.79304,,0.49472,,57,,B,,usable mapping rate,illumina,nextseq,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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.,,pubmed:31140974;pubmed:33933422,,Neural crest derived cells from hypothyroid  juvenile zebrafish trunks  biological replicate 1,GSM3764572,,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 °C 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,,1,10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,NextSeq 500,,SRP198298,,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,,,,1526791201,989860604,1192544480,1366270035,2704663,SRX5827016,SRS4754830,SRA886020,GEO,"Biology, University of Virginia",1,0.92899,,0.25348,,0.83571,,0.48794,,57,,B,,usable mapping rate,illumina,nextseq,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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.,,pubmed:31140974;pubmed:33933422,,Neural crest derived cells from euthyroid  post embryonic zebrafish trunks  biological replicate 6,GSM3764571,,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 °C 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,,1,10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,NextSeq 500,,SRP198298,,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,,,,1638197208,1052881199,1241396499,1476057783,2883835,SRX5827015,SRS4754829,SRA886020,GEO,"Biology, University of Virginia",1,0.91678,,0.23274,,0.83435,,0.51765,,57,,B,,usable mapping rate,illumina,nextseq,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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.,,pubmed:31140974;pubmed:33933422,,Neural crest derived cells from euthyroid  post embryonic zebrafish trunks  biological replicate 5,GSM3764570,,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 °C 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,,1,10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,NextSeq 500,,SRP198298,,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,,,,2330538697,1602893033,2265568086,2124697512,3276777,SRX5827014,SRS4754828,SRA886020,GEO,"Biology, University of Virginia",1,0.91032,,0.14841,,0.81207,,0.52798,,57,,B,,usable mapping rate,illumina,nextseq,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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.,,pubmed:31140974;pubmed:33933422,,Neural crest derived cells from euthyroid  post embryonic zebrafish trunks  biological replicate 4,GSM3764569,,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 °C 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,,1,10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,NextSeq 500,,SRP198298,,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,,,,2659154932,1836434156,2596847773,2428811653,3737227,SRX5827013,SRS4754827,SRA886020,GEO,"Biology, University of Virginia",1,0.91042,,0.14492,,0.81148,,0.53287,,57,,B,,usable mapping rate,illumina,nextseq,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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.,,pubmed:31140974;pubmed:33933422,,Neural crest derived cells from euthyroid  post embryonic zebrafish trunks  biological replicate 3,GSM3764568,,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 °C 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,,1,10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,NextSeq 500,,SRP198298,,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,,,,4144426475,3024945467,3685756189,3690427238,3013937,SRX5827012,SRS4754826,SRA886020,GEO,"Biology, University of Virginia",1,0.94033,,0.12393,,0.79338,,0.50069,,57,,B,,usable mapping rate,illumina,nextseq,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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.,,pubmed:31140974;pubmed:33933422,,Neural crest derived cells from euthyroid  post embryonic zebrafish trunks  biological replicate 1,GSM3764566,,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 °C 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,,1,10X genomics single cell gene expression V2 protocol following manufacturer recommendations. 10X genomics single cell gene expression V2 protocol following manufacturer recommendations.,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,NextSeq 500,,SRP198298,,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,,,,1531421605,966957285,1151579626,1352667292,2608146,SRX5827010,SRS4754824,SRA886020,GEO,"Biology, University of Virginia",1,0.92288,,0.25231,,0.83479,,0.5014,,57,,B,,usable mapping rate,illumina,nextseq,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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.,,pubmed:34234366,,Zf 30h trunk,GSM4631066,,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,,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,,age:30 hpf|tissue:trunk|genotype:wildtype,GSM4631066,GSM4631066: Zf 30h trunk; Danio rerio; RNA Seq,GSM4631066,,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,,SRP268312,,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,,8739694698,6736998816,6903125001,8168427703,20277404,SRX8595501,SRS6886082,SRA1089692,GEO,University of South Florida,1,0.88066,,0.09296,,0.8506,,0.50586,,147,,B,,usable mapping rate,illumina,hiseq_era,3prime,cdna_unspecified,nextera,sc,single_cell_droplet,10x,,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.,,pubmed:34234366,,Zf 30h trunk,GSM4631066,,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,,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,,age:30 hpf|tissue:trunk|genotype:wildtype,GSM4631066,GSM4631066: Zf 30h trunk; Danio rerio; RNA Seq,GSM4631066,,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,,SRP268312,,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,,8978925123,6926043302,7091713953,8399543364,32147234,SRX8595501,SRS6886082,SRA1089692,GEO,University of South Florida,1,0.87666,,0.09235,,0.85277,,0.49776,,147,,B,,usable mapping rate,illumina,hiseq_era,3prime,cdna_unspecified,nextera,sc,single_cell_droplet,10x,,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,,pubmed:36063998,,olig2+ cells in zebrafish trunks,GSM5406686,,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 “expressed”. 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,,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’ Library and Gel Bead kit V3,,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,,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,,SRP325962,,,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,,,6848745621,5731974961,10959380121,7859959179,352118,SRX11248236,SRS9294118,SRA1251944,GEO,Nantong University,2,0.0,0.89636,0.0,0.20375,1.0,0.78575,,0.50155,150,150,T,B,mate1 technical by mapping diff,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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,,pubmed:36063998,,olig2+ cells in zebrafish trunks,GSM5406686,,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 “expressed”. 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,,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’ Library and Gel Bead kit V3,,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,,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,,SRP325962,,,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,,,5431710090,4568888734,8717963207,6239757593,280876,SRX11248236,SRS9294118,SRA1251944,GEO,Nantong University,2,0.0,0.89635,0.0,0.20299,1.0,0.78453,,0.50241,150,150,T,B,mate1 technical by mapping diff,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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,,pubmed:36063998,,olig2+ cells in zebrafish trunks,GSM5406686,,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 “expressed”. 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,,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’ Library and Gel Bead kit V3,,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,,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,,SRP325962,,,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,,,4513259900,3774781009,7221748955,5183345869,232767,SRX11248236,SRS9294118,SRA1251944,GEO,Nantong University,2,0.0,0.89637,0.0,0.20432,1.0,0.78439,,0.4973,150,150,T,B,mate1 technical by mapping diff,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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,,pubmed:36063998,,olig2+ cells in zebrafish trunks,GSM5406686,,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 “expressed”. 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,,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’ Library and Gel Bead kit V3,,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,,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,,SRP325962,,,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,,,4874539429,4084280591,7793747016,5594741104,249560,SRX11248236,SRS9294118,SRA1251944,GEO,Nantong University,2,0.0,0.89737,0.0,0.20476,1.0,0.78675,,0.5017,150,150,T,B,mate1 technical by mapping diff,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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.,,pubmed:35355015,,XBN,GSM5510265,,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,,Droplet based scRNA seq was performed using the Chromium Single Cell 3’ Library and Gel Bead Kit v3 10X Genomics and Chromium Single Cell 3’ 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,,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,,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,,SRP331755,,,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,,,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,,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.,,pubmed:35355015,,XBN,GSM5510265,,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,,Droplet based scRNA seq was performed using the Chromium Single Cell 3’ Library and Gel Bead Kit v3 10X Genomics and Chromium Single Cell 3’ 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,,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,,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,,SRP331755,,,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,,,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,,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.,,pubmed:35355015,,XBG,GSM5510264,,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,,Droplet based scRNA seq was performed using the Chromium Single Cell 3’ Library and Gel Bead Kit v3 10X Genomics and Chromium Single Cell 3’ 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,,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,,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,,SRP331755,,,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,,,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,,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.,,pubmed:35355015,,XBG,GSM5510264,,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,,Droplet based scRNA seq was performed using the Chromium Single Cell 3’ Library and Gel Bead Kit v3 10X Genomics and Chromium Single Cell 3’ 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,,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,,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,,SRP331755,,,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,,,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,,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,,pubmed:36063998,,olig2+ cells in zebrafish trunks   60hpf,GSM5639644,,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 “expressed”. 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,,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’ Library and Gel Bead kit V3,,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,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP342165,,,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,,,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,,0.51047,150,150,T,B,mate1 technical by mapping diff,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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,,pubmed:36063998,,olig2+ cells in zebrafish trunks   60hpf,GSM5639644,,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 “expressed”. 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,,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’ Library and Gel Bead kit V3,,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,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP342165,,,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,,,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,,0.50682,150,150,T,B,mate1 technical by mapping diff,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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,,pubmed:36063998,,olig2+ cells in zebrafish trunks   60hpf,GSM5639644,,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 “expressed”. 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,,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’ Library and Gel Bead kit V3,,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,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP342165,,,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,,,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,,0.50544,150,150,T,B,mate1 technical by mapping diff,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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,,pubmed:36063998,,olig2+ cells in zebrafish trunks   60hpf,GSM5639644,,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 “expressed”. 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,,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’ Library and Gel Bead kit V3,,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,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP342165,,,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,,,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,,0.51059,150,150,T,B,mate1 technical by mapping diff,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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,,pubmed:36063998,,olig2+ cells in zebrafish trunks   28hpf,GSM5639643,,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 “expressed”. 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,,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’ Library and Gel Bead kit V3,,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,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP342165,,,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,,,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,,0.49581,150,150,T,B,mate1 technical by mapping diff,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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,,pubmed:36063998,,olig2+ cells in zebrafish trunks   28hpf,GSM5639643,,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 “expressed”. 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,,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’ Library and Gel Bead kit V3,,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,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP342165,,,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,,,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,,0.50368,150,150,T,B,mate1 technical by mapping diff,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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,,pubmed:36063998,,olig2+ cells in zebrafish trunks   28hpf,GSM5639643,,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 “expressed”. 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,,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’ Library and Gel Bead kit V3,,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,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP342165,,,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,,,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,,0.50003,150,150,T,B,mate1 technical by mapping diff,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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,,pubmed:36063998,,olig2+ cells in zebrafish trunks   28hpf,GSM5639643,,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 “expressed”. 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,,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’ Library and Gel Bead kit V3,,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,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP342165,,,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,,,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,,0.4925,150,150,T,B,mate1 technical by mapping diff,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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,,DP1 36hpf,GSM7083138,,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，raw 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 ≥ 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,,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’ 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’ 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.,,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.,,OTHER,TRANSCRIPTOMIC,other,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP342737,,,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,,,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,,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,,DP2 36hpf,GSM7083139,,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，raw 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 ≥ 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,,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’ 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’ 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.,,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.,,OTHER,TRANSCRIPTOMIC,other,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP342737,,,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,,,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,,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,,SP 36hpf,GSM7083140,,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，raw 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 ≥ 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,,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’ 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’ 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.,,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.,,OTHER,TRANSCRIPTOMIC,other,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP342737,,,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,,,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,,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,,gRNA jag1  26HPF  scRNAseq,GSM6443156,,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,,Wild type  miR 128Δ/Δ  csnk1a1 and jag1b g3’UTR 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’ Library Construction Kit V3.1 CG000204 was used to generate libraires according to manufacturer intructions,,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 128Δ/Δ  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,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina HiSeq 4000,,SRP390913,,loader:fastq load.py|options:  readTypes=TBB   read1PairFiles=jag1b DRT S3 L003 I1 001.fastq.gz   read2PairFiles=jag1b DRT S3 L003 R1 001.fastq.gz   read3PairFiles=jag1b DRT S3 L003 R2 001.fastq.gz,jag1b_DRT_S3_L003_I1_001.fastq.gz jag1b_DRT_S3_L003_R1_001.fastq.gz jag1b_DRT_S3_L003_R2_001.fastq.gz,fastq fastq fastq,16114282986.0,126884118.0,GSM6443156 r1,0:8 1:28 2:91,A:4274223175;C:3328097087;G:3589117645;T:3907323607;N:448528,8,28,91,,4274223175,3328097087,3589117645,3907323607,448528,SRX17024129,SRS14609022,SRA1473366,"Nicoli Lab, Genetics/Internal Medicine, Yale University","Nicoli Lab, Genetics/Internal Medicine, Yale University",2,0.00772,0.88765,0.00298,0.21848,0.98776,0.7934,0.36184,0.53575,28,91,T,B,sc-like readlen,illumina,hiseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,United States,2022-08-10,Pharyngula,Embryo,Trunk,Surface Structure
70968,SRR21007396,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,,gRNA jag1  26HPF  scRNAseq,GSM6443156,,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,,Wild type  miR 128Δ/Δ  csnk1a1 and jag1b g3’UTR 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’ Library Construction Kit V3.1 CG000204 was used to generate libraires according to manufacturer intructions,,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 128Δ/Δ  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,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina HiSeq 4000,,SRP390913,,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,,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,,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,,gRNA csnk1  26HPF  scRNAseq,GSM6443155,,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,,Wild type  miR 128Δ/Δ  csnk1a1 and jag1b g3’UTR 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’ Library Construction Kit V3.1 CG000204 was used to generate libraires according to manufacturer intructions,,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 128Δ/Δ  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,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina HiSeq 4000,,SRP390913,,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,,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,,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,,gRNA csnk1  26HPF  scRNAseq,GSM6443155,,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,,Wild type  miR 128Δ/Δ  csnk1a1 and jag1b g3’UTR 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’ Library Construction Kit V3.1 CG000204 was used to generate libraires according to manufacturer intructions,,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 128Δ/Δ  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,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina HiSeq 4000,,SRP390913,,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,,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,,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,,MT  26HPF  scRNAseq,GSM6443154,,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,,Wild type  miR 128Δ/Δ  csnk1a1 and jag1b g3’UTR 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’ Library Construction Kit V3.1 CG000204 was used to generate libraires according to manufacturer intructions,,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 128Δ/Δ  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,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina HiSeq 4000,,SRP390913,,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,,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,,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,,WT  26HPF  scRNAseq,GSM6443153,,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,,Wild type  miR 128Δ/Δ  csnk1a1 and jag1b g3’UTR 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’ Library Construction Kit V3.1 CG000204 was used to generate libraires according to manufacturer intructions,,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 128Δ/Δ  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,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina HiSeq 4000,,SRP390913,,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,,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,,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,,flt1mut  replicate 2  scRNAseq trunk,GSM7108419,,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,,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 3’ v2 protocol  10x Genomics,,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,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,NextSeq 2000,,SRP428413,,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,,,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,,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,,WT  replicate 2  scRNAseq trunk,GSM7108418,,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,,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 3’ v2 protocol  10x Genomics,,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,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,NextSeq 2000,,SRP428413,,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,,,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,,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,,flt1mut  replicate 1  scRNAseq trunk,GSM7108417,,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,,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 3’ v2 protocol  10x Genomics,,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,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,NextSeq 2000,,SRP428413,,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,,,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,,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,,WT  replicate 1  scRNAseq trunk,GSM7108416,,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,,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 3’ v2 protocol  10x Genomics,,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,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,NextSeq 2000,,SRP428413,,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,,,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,,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.,,pubmed:37967180,,52 hpf mCherry positive,GSM7181573,,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,,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°C 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 μl 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 3’ 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,Zebrafish embryos were raised at 28.5 °C. 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°C 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 μl 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,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP433186,,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,,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,,0.24065,,0.84705,,0.64618,,91,,B,,usable mapping rate,illumina,novaseq_era,3prime,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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.,,pubmed:37967180,,52 hpf mCherry positive,GSM7181573,,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,,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°C 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 μl 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 3’ 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,Zebrafish embryos were raised at 28.5 °C. 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°C 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 μl 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,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP433186,,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,,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,,0.24037,,0.84678,,0.66835,,91,,B,,usable mapping rate,illumina,novaseq_era,3prime,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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.,,pubmed:37967180,,52 hpf mCherry positive,GSM7181573,,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,,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°C 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 μl 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 3’ 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,Zebrafish embryos were raised at 28.5 °C. 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°C 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 μl 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,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP433186,,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,,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,,0.24212,,0.84816,,0.65892,,91,,B,,usable mapping rate,illumina,novaseq_era,3prime,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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.,,pubmed:37967180,,52 hpf mCherry positive,GSM7181573,,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,,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°C 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 μl 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 3’ 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,Zebrafish embryos were raised at 28.5 °C. 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°C 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 μl 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,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP433186,,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,,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,,0.24209,,0.84934,,0.68035,,91,,B,,usable mapping rate,illumina,novaseq_era,3prime,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,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.,,,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,,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,,,,,,,,,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.,,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,SINGLE,ILLUMINA,Illumina NovaSeq 6000,,SRP444513,,,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,,,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,,0.51028,150,150,T,B,mate1 technical by mapping diff,illumina,novaseq_era,full_length,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,China,2023-06-17,Pharyngula,Embryo,Trunk,Surface Structure