{"database": "metadata", "table": "run_metadata", "rows": [[32781, "SRR29411985", "SRX24925451", "SRS21630866", "SRP513930", "PRJNA1124008", "Cell state transitions are decoupled from cell division during early embryo development [II]", "GSE269848", "Other", "Paper abstract: As tissues develop  cells divide and differentiate concurrently. Conflicting evidence shows that cell division is either dispensable or required for formation of cell types. To determine the role of cell division in differentiation  we arrested the cell cycle in zebrafish embryos using two independent approaches and profiled them at single cell resolution. We show that cell division is dispensable for differentiation of all embryonic tissues during initial cell type differentiation from early gastrulation to the end of segmentation. However  in the absence of cell division  differentiation slows down in some cell types  and cells exhibit global stress responses. While differentiation is robust to blocking cell division  the proportions of cells across cell states are not but show evidence of partial compensation. This work clarifies our understanding of the role of cell division in development and showcases the utility of combining embryo wide perturbations with single cell RNA sequencing to uncover the role of common biological processes across multiple tissues. Overall design: Design of experiment for this particular dataset: Forty tails from zebrafish embryos at 24  38 hpf and 48 hpf were collected. Cells were dissociated from these tails and multi seq tags were added to the cells for each time point. Cells from all time points were pooled and single cell sequencing was performed using Indrops. Four gene expression GEX libraries were prepared for transcriptomic information and four multiseq tag libraries TAG were prepared for reading out the multiseq tags. We provide the raw data .fastq files  processed data   both raw counts.tsv.gz and filtered by total UMI counts filtered.h5ad files and the entire filtered data post removing doublets as all data.h5ad. We also provide counts for multi seq tags example  TAG 1.counts.csv. Information about pooling libraries and library indices is provided in Pooling Samples.xlsx. Only 24 hpf data was used for Kukreja et. al. 2024 and hence the cell state information we provide in the all data.h5ad is only for 24 hpf.", null, "pubmed:37546736", null, "24  38 hpf and 48 hpf tails", "GSM8328864", null, "source name:embryo tail|tissue:embryo tail|geo loc name:missing|collection date:missing", "24  38 hpf and 48 hpf tails", "Reads were mapped onto the Zebrafish genome as described in Kukreja et al. 2024 manuscript. Multi seq barcodes for each sample were identified using a custom pipeline available here: https://github.com/AllonKleinLab/klunctions/. Barcode abundance was used to manually remove multiplet populations as well as assign cells to their appropriate sample. Data from only 24 hpf tails were used for the manuscript. We provide 8 FASTQ files 2 lanes x 4 reads per lane. The read files from an inDrops run have the following content: * R1 001.fastq.gz : contains the three prime UTR cDNA read * R2 001.fastq.gz : contains the first half of the cell barcode * R3 001.fastq.gz : contains the library index for demultiplexing libraries * R4 001.fastq.gz : contains the second half of the barcode and the UMI.  All subsequent processing steps from FASTQ files to count matrixes were performed using the custom pipeline for inDrops data analysis github.com/indrops. Single cell transcriptomes were barcoded using inDrops Klein et al  Cell 2015. Standard transcriptome RNA seq libraries were processed as reported in Zilionis et al. Nature Protocol 2016 using inDrops v3 protocol. The transcriptome libraries were sequenced on reads Illumina NextSeq 500. Libraries used standard Illumina sequencing primers and 61 cycles for Read1  14 cycles for Read2  8 cycles each for IndexRead1 and IndexRead2. Raw fastq files was processed using inDrops.py pipeline github.com/indrops/indrops. Sequenced reads were mapped to a zebrafish reference transcriptome built from the zebrafish GRCz10 genome assembly Assembly Accession: GCF 000002035.5 using bowtie version 1.1.143. To obtain the final counts matrix used for data analysis  total count filters were applied as described in Kukreja et. al. 2024  method section \"Single cell RNA seq Data preprocessing\" Assembly: GRCz10 genome assembly Assembly Accession: GCF 000002035.5 Supplementary files format and content: Raw counts for transcriptome tsv.gz: cell barcode  gene names  and raw counts for all cells Supplementary files format and content: Raw counts for multi seq tags csv.gz: cell barcode  tag sequence  and raw counts for all cells Supplementary files format and content: Filtered barcodes filtered.h5ad: cell barcode  and associated metadata for all cells Library strategy: inDrops v3 scRNA seq", "embryo tail", null, "Forty zebrafish tail samples collected at 24  38 hpf and 48 hpf  were dissected between the yolk ball and extension and dissociated according to a modified version of the protocol described by Bresciani et al. 2018. Briefly  the tails were dissociated with a mixture of DNaseI 20\u00b5g/mL  Collagenase/Dispase 8 mg/mL  and 0.25% Trypsin EDTA at 30.5\u00b0C for 15 minutes. The proteases were quenched with DMEM + 10% FBS. Samples were washed and resuspend in PBS. Cells from each timepoint were hashed with a unique lipid modified oligo using Multi seq. The barcoded samples were subsequently pooled  washed with 1% BSA + PBS  and resuspended in 0.1% BSA + 18% Optiprep in PBS at a final concentration of 300 000 cells/mL. Single cell transcriptomes were captured using inDrops. NGS libraries were prepared by the Single cell Core at Harvard Medical School and sequenced using an Illumina NovaSeq kit.", null, "tissue:embryo tail", "GSM8328864", "GSM8328864: 24  38 hpf and 48 hpf tails; Danio rerio; OTHER", "GSM8328864 r1", "GSM8328864", "1", "Forty zebrafish tail samples collected at 24  38 hpf and 48 hpf  were dissected between the yolk ball and extension and dissociated according to a modified version of the protocol described by Bresciani et al. 2018. Briefly  the tails were dissociated with a mixture of DNaseI 20\u00b5g/mL  Collagenase/Dispase 8 mg/mL  and 0.25% Trypsin EDTA at 30.5\u00b0C for 15 minutes. The proteases were quenched with DMEM + 10% FBS. Samples were washed and resuspend in PBS. Cells from each timepoint were hashed with a unique lipid modified oligo using Multi seq. The barcoded samples were subsequently pooled  washed with 1% BSA + PBS  and resuspended in 0.1% BSA + 18% Optiprep in PBS at a final concentration of 300 000 cells/mL. Single cell transcriptomes were captured using inDrops. NGS libraries were prepared by the Single cell Core at Harvard Medical School and sequenced using an Illumina NovaSeq kit.", null, "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP513930", null, null, "Undetermined_S0_L002_R1_001.fastq.gz Undetermined_S0_L002_R2_001.fastq.gz Undetermined_S0_L002_R3_001.fastq.gz Undetermined_S0_L002_R4_001.fastq.gz", "fastq fastq fastq fastq", 58603546956.0, 505202991.0, "GSM8328864 r1", "0:86 1:8 2:8 3:14", "A:13191204330;C:9162028793;G:9431065581;T:11662090182;N:1068340", 86, 8, 8, 14, 13191204330, 9162028793, 9431065581, 11662090182, 1068340, "SRX24925451", "SRS21630866", "SRA1899240", "Harvard University", "Harvard University", null, null, null, null, null, null, null, null, null, null, null, "B", null, "usable mapping rate", "illumina", "novaseq_era", "unknown", "other", "trueseq", "sc", "single_cell_droplet", "indrops", null, "United States", "2024-06-14", "Multi-stage", "Embryo", "Tail", "Multi-system"]], "columns": ["rowid", "run.accession", "experiment.accession", "sample.accession", "study.accession", "bioproject", "study.title", "study.alias", "study.type", "study.abstract", "study.attributes", "study.PMIDs", "sample.description", "sample.title", "sample.alias", "sample.centername", "sample.attributes", "GEOsample.title", "GEOsample.dataprocessing", "GEOsample.source", "GEOsample.treatmentprotocol", "GEOsample.extractprotocol", "GEOsample.growthprotocol", "GEOsample.characteristics", "GEOsample.accession", "experiment.title", "experiment.alias", "experiment.library_name", "experiment.design_description", "experiment.library_construction_protocol", "experiment.attributes", "experiment.library_strategy", "experiment.library_source", "experiment.library_selection", "experiment.library_layout", "experiment.platform", "experiment.instrument_model", "experiment.spot_descriptor", "experiment.study_ref", "run.title", "run.attributes", "run.filename", "run.semantic_name", "run.total_bases", "run.total_spots", "run.alias", "run.read_lengths", "run.base_counts", "run.r1_length", "run.r2_length", "run.r3_length", "run.r4_length", "run.Acount", "run.Ccount", "run.Gcount", "run.Tcount", "run.Ncount", "run.experiment", "run.pool_member", "submission.accession", "submission.srasource", "submission.bioprojectsource", "seqdetective.n_mates", "seqdetective.mapping_rate.mate1", "seqdetective.mapping_rate.mate2", "seqdetective.nofeature_rate.mate1", "seqdetective.nofeature_rate.mate2", "seqdetective.sparsity.mate1", "seqdetective.sparsity.mate2", "seqdetective.pos_strand_rate.mate1", "seqdetective.pos_strand_rate.mate2", "seqdetective.readlen.mate1", "seqdetective.readlen.mate2", "seqdetective.judgement.mate1", "seqdetective.judgement.mate2", "seqdetective.judgement.reason", "platform_family", "instrument_generation", "read_bias", "selection_class", "prep_kit", "sc_or_bulk", "tech_class", "technology", "tech_variant", "submission.bioprojectsource.country", "earliest_date", "devstage_curation", "devstage_curation_coarse", "tissue_curation", "tissue_curation_coarse"], "primary_keys": ["rowid"], "primary_key_values": ["32781"], "units": {}, "query_ms": 8.250386999861803}