{"database": "metadata", "table": "run_metadata", "rows": [[47849, "SRR6890850", "SRX3841319", "SRS3087479", "SRP136369", "PRJNA445487", "Systematic mapping of cell state trajectories  cell lineage  and perturbations in the zebrafish embryo using single cell transcriptomics", "GSE112294", "Transcriptome Analysis", "High throughput mapping of cellular differentiation hierarchies from single cell data promises to empower systematic interrogations of vertebrate development and disease.  Here  we applied single cell RNA sequencing to >92 000 cells from zebrafish embryos during the first day of development. Using a graph based approach  we mapped a cell state landscape that describes axis patterning  germ layer formation  and organogenesis.  We tested how clonally related cells traverse this landscape by developing a transposon based barcoding approach \u201cTracerSeq\u201d for reconstructing single cell lineage histories. Clonally related cells were often restricted by the state landscape  including a case in which two independent lineages converge on similar fates. Cell fates remained restricted to this landscape in chordin deficient embryos. We provide web based resources for further analysis of the single cell data. Overall design: Single cell mRNA sequencing of zebrafish embryonic cells. Samples1 7: Single cell libraries from untreated embryos 4 hpf 24 hpf Samples8 12: Single cell libraries from embryos injected with TracerSeq lineage cassette at the 1 cell stage. Samples13 18: Single cell libraries from embryos injected with sgRNA + Cas9 at the 1 cell stage.", null, "pubmed:29700229", null, "Zebrafish Embryos  6hpf", "GSM3067190", null, "tissue:Zebrafish Embryo Dissociated Cells|strain:TU|developmental stage:06hpf|treatment:untreated embryos|genotype:wild type", "Zebrafish Embryos  6hpf", "inDrops FASTQ files were demultiplexed using a custom python pipeline as previously described see Zilionis et al.  Nature Protocols 2017 and https://github.com/indrops/.  Each sequencing spot is associated with a single biological read and 1 3 technical reads  depending on the specific inDrops library preparation chemistry used.  FASTQs DEW001 DEW003 used V1 chemistry in which read2 is the biological read and read1 is the metadata read.  DEW010 DEW057 used V2 chemistry in which read1 is the biological read and read2 is the metadata read.  DEW101 208 used V3 chemistry in which read1 is the biological read  read2 carries the first half of the cell barcode  read3 carries the library index  and read4 carries the second half of the cell barcode and the UMI. Sequencing reads were first sorted according to sample of origin; Individual samples were then formatted as a single demultiplexed FASTQ in which single cell and UMI barcodes for each read are listed in the header. These FASTQ files are deposited in NCBI SRA and can be used to resume the inDrops.py read processing pipeline at step 2 \"Identify abundant barcodes\"  see https://github.com/indrops/. Each cDNA read was trimmed using Trimomatic version 0.32; parameters: LEADING:28 SLIDINGWINDOW:4:20 MINLEN:16. Cell specific barcodes for each cDNA read were then matched against a set of pre determined barcodes. Up to two nucleotide mismatch errors were corrected; other reads were discarded. cDNA reads were then aligned to a zebrafish transcriptome using Bowtie version 1.1.1  parameters:  n 1  l 15  e 200  m 200  best  strata  a. The reference transcriptome was built from the zebrafish GRCz10 genome assembly Accesion: GCF 000002035.5.Mapped reads were then processed into counts of UMI filtered transcripts per gene. UMI counts matrices were filtered to exclude cell barcodes associated with low numbers of reads.  This determination was made by manually inspecting a weighted histogram of UMI counts for each cell barcode  and thresholding only the top 95% of the largest and often the only mode of the distribution. UMI counts matrices originating from the same biological sample were combined into a single table.  UMI counts were adjusted by a total counts normalization. For TracerSeq embryos  inDrops FASTQ files generated from GFP targeted sequencing libraries were demultiplexed as described above.  These FASTQ files were then parsed to generate TracerVSCellBarcodes tables using custom Matlab scripts see: https://github.com/wagnerde/TracerSeq. Genome build: GRCz10 Supplementary files format and content: Raw UMI filtered counts csv. Matrix rows are transcripts  columns are single cells.  Column headers are in the following format: LibraryName CellBarcodePart1 CellBarcodePart2 Normalized UMI filtered counts csv. Matrix rows are transcripts  columns are single cells.  Column headers are in the following format: LibraryName CellBarcodePart1 CellBarcodePart2 ClusterIDs txt.  An array of clusterID assignments for each cell column in the associated CSV tables ClusterNames csv.  A table of annotations for each ClusterID. Convert DEW to SRR csv.  A table for converting between DEW and NCBI library names. CellTracerCounts csv.  A table where each row is a unique TracerSeq transcript barcode; column1: inDrops cell barcode; column2: TracerSeq clone # assignment; column3: corrected TracerSeq barcode sequence; column4: UMI counts.", "Zebrafish Embryo Dissociated Cells", null, "Zebrafish embryos were incubated to the indicated times post fertilization and chorions were removed by incubating in 1mg/mL Pronase Sigma P5147 1G for 3 4 min followed by washing in 0.3X Danieau Buffer. [10X Danieau Buffer = 174 mM NaCl  2.1 mM KCl 1.2 mM MgSO4  1.8 mM CaNO32  15 mM HEPES   pH 7.6].  Dissociation of embryonic tissues was performed similarly as previously described Manoli & Driever  Cold Spring Harbor Protocols 2012 with the following specifications. Wild type and CRISPR targeted samples were each prepared from 20 100 embryos. Embryo tissues were triturated to homogeneity in 1 5mL FACSmax cell dissociation solution Genlantis T200100 and incubated for 4 5 minutes at room temperature.  Cells were then filtered through a 40\u03bcm cell strainer mesh Fisher 352340  and centrifuged in a swinging bucket rotor at 310g for 5 minutes.  Cell pellets were resuspended in 1X DPBS no Ca/Mg  Life Technologies 14190 144 containing 1% BSA Sigma A3311 100G  and subjected to 2 3 additional rounds of centrifugation and resuspension.  post washing  cells were resuspended in 0.5% BSA / DPBS containing 18% optiprep density medium Sigma D1556 250ML.  Cell density was quantified manually using INCYTO\u2122 C Chip\u2122 Disposable Hemacytometers Fisher 22 600 100  and adjusted to 100 000 cells per mL.  For single embryo dissociations  all FACSmax and wash volumes were reduced to a volume 0.5 mL and were carried out in 0.5mL LoBind microcentrifuge tubes Eppendorf 022431005 that had been pre coated with 10% BSA/DPBS for 15 minutes at room temperature.  Single cell transcriptomes were then barcoded using the inDrops platform as previously described Zilionis et al.  Nature Protocols 2017. Following the within droplet reverse transcription step  emulsions were split into batches of approximately 1 000 2 000 cells  frozen at  80C  and subsequently processed as individual RNA seq libraries. Single cell RNA Seq libraries were prepared using a protocol customized for the inDrops platform see Zilionis et al.  Nature Protocols 2017", null, "strain:TU|developmental stage:06hpf|treatment:untreated embryos|genotype:wild type", "GSM3067190", "GSM3067190: Zebrafish Embryos  6hpf; Danio rerio; RNA Seq", "GSM3067190", null, "1", "Zebrafish embryos were incubated to the indicated times post fertilization and chorions were removed by incubating in 1mg/mL Pronase Sigma P5147 1G for 3 4 min followed by washing in 0.3X Danieau Buffer. [10X Danieau Buffer = 174 mM NaCl  2.1 mM KCl 1.2 mM MgSO4  1.8 mM CaNO32  15 mM HEPES   pH 7.6].  Dissociation of embryonic tissues was performed similarly as previously described Manoli & Driever  Cold Spring Harbor Protocols 2012 with the following specifications. Wild type and CRISPR targeted samples were each prepared from 20 100 embryos. Embryo tissues were triturated to homogeneity in 1 5mL FACSmax cell dissociation solution Genlantis T200100 and incubated for 4 5 minutes at room temperature.  Cells were then filtered through a 40\u03bcm cell strainer mesh Fisher 352340  and centrifuged in a swinging bucket rotor at 310g for 5 minutes.  Cell pellets were resuspended in 1X DPBS no Ca/Mg  Life Technologies 14190 144 containing 1% BSA Sigma A3311 100G  and subjected to 2 3 additional rounds of centrifugation and resuspension.  post washing  cells were resuspended in 0.5% BSA / DPBS containing 18% optiprep density medium Sigma D1556 250ML.  Cell density was quantified manually using INCYTO\u2122 C Chip\u2122 Disposable Hemacytometers Fisher 22 600 100  and adjusted to 100 000 cells per mL.  For single embryo dissociations  all FACSmax and wash volumes were reduced to a volume 0.5 mL and were carried out in 0.5mL LoBind microcentrifuge tubes Eppendorf 022431005 that had been pre coated with 10% BSA/DPBS for 15 minutes at room temperature.  Single cell transcriptomes were then barcoded using the inDrops platform as previously described Zilionis et al.  Nature Protocols 2017. Following the within droplet reverse transcription step  emulsions were split into batches of approximately 1 000 2 000 cells  frozen at  80C  and subsequently processed as individual RNA seq libraries. Single cell RNA Seq libraries were prepared using a protocol customized for the inDrops platform see Zilionis et al.  Nature Protocols 2017", "GEO Accession:GSM3067190", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "SINGLE", "ILLUMINA", "NextSeq 500", null, "SRP136369", null, "loader:fastq load.py|options:  appendBCtoName   platform=Illumina", "DEW045.fastq.gz", "fastq", 2495609024.0, 74858057.0, "GSM3067190 r4", "0:33.34", "A:622971438;C:464022853;G:480774815;T:927835940;N:3978", 33, null, null, null, 622971438, 464022853, 480774815, 927835940, 3978, "SRX3841319", "SRS3087479", "SRA672434", "GEO", "Systems Biology, Harvard Medical School", 1, 0.82948, null, 0.1439, null, 0.81132, null, 0.55832, null, 34, null, "B", null, "usable mapping rate", "illumina", "nextseq", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "indrops", null, "United States", "2018-03-23", "Gastrula", "Embryo", "Embryo Imprecise", "All anatomical structures"]], "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": ["47849"], "units": {}, "query_ms": 10.161190002691}