{"database": "metadata", "table": "run_metadata", "rows": [[74419, "SRR23929943", "SRX19740078", "SRS17106152", "SRP428435", "PRJNA941866", "Decoding pancreatic endocrine cell differentiation and beta cell regeneration in zebrafish", "GSE226841", "Transcriptome Analysis", "The aim of the study is to investigate the endocrinogenesis process in zebrafish pancreas during normal development and regenerative condition. Overall design: Using lineage tracing methodology TgKIkrt4 p2a mNeonGreen t2a iCre; ubb:loxp CFP stop loxp H2BmCherry  we used FACS to sort out mCherry positive cells in adult zebrafish pancreas  indicating cells in the krt4+ cell lineage", null, "pubmed:37595046", null, "10X 22 021  2 dy post single ablation", "GSM7085295", null, "source name:krt4 lineage traced cells in adult zebrafish pancreas|genotype:WT|tissue:pancreas|cell type:krt4 lineage traced cells|treatment:ablation|time:2 dy post single ablation", "10X 22 021  2 dy post single ablation", "The raw sequencing data was then processed with the \u2018count\u2019 command of the Cell Ranger software v5.0.1 10\u00d7 Genomics with the option \u2018  expect cells\u2019 set to 7000 all other options were used as per default. Assembly: danRer11 Supplementary files format and content: matrix files", "krt4 lineage traced cells in adult zebrafish pancreas", "We selected 6 mpf 9 mpf fish with 8 10 fish in each condition  We sacrificed the adult fish by putting each one into ice cold Hanks' Balanced Salt Solution HBSS  no calcium  no magnesium for 10 minutes. Next  we used blunt forceps to carefully remove the skin  kidney  eggs in females  liver and gallbladder to expose the pancreata. This step is critical for avoiding krt4 + cell contamination from other organs. We also removed adipose tissue as much as possible. Then  we cut at the anterior region of the intestinal bulb and hindgut  and transferred the intestine and pancreas together to a new dish. We used blunt dissection tools to carefully separate the pancreata from the intestine. Meanwhile  we also removed the spleen appearing in dark red  which is also attached to the intestine. We moved and immersed the whole pancreata into 5 mL HBSS kept on ice. For each condition  we pooled 4 8 samples together for an enzymatic digestion with 600 \u03bcL 1\u00d7TrypLE\u2122 Thermofisher supplemented with 60 \u03bcL 100\u00d7 Pluronic\u2122 F68 Thermofisher at 37 \u00b0C on a shaker at 125 rpm for 45 \u2013 60 minutes to prevent tissue adhesion. We also pipetted the tissue up and down every 5 minutes for better digestion. We added 6 mL precooled 2% BSA to end the digestion and centrifuged the sample at 500 g for 5 minutes. post removing the supernatant  we washed the pellets with 300 \u03bcL pre cooled solution containing 1% BSA  0.1% Pluronic F 68 and 0.1% DAPI  and used a Corning\u2122 Falcon\u2122 cell strainer Corning\u2122 352235 to filter out not fully digested tissues. During FACS  we selected single cell populations based on forward scatter and side scatter signals. Next  we performed negative selection with the DAPI channel to remove dead cells and cell debris. Lastly  we used the Cherry channel for the subsequent gating to collect all cells of the krt4 derived lineage in a new tube as the single cell suspension.", "Droplet based scRNA seq was performed using the Chromium Single Cell 3\u2032 Library and Gel Bead Kit v3 10\u00d7 Genomics and Chromium Single Cell 3\u2032 Chip G 10\u00d7 Genomics. Approximately 8 000 10 000 cells from each condition were loaded and encapsulated in a single v3 reaction. GEM generation and library preparation were performed according to manufacturer\u2019s instructions. Cells were partitioned into gel beads in emulsion in the controller for cell lysis and reverse transcription. The 10\u00d7 scRNA Seq libraries were PCR amplified 13 cycles  pooled  denatured  and diluted in prior to paired end sequencing on a NextSeq 500 according to manufacturer\u2019s recommendations. Sequencing data was aligned to the zebrafish reference genome GRCz11 with addition of the mCherry sequence using Cell Ranger v5.0.1 10\u00d7 Genomics to generate a gene by cell count matrix with default parameters.", null, "genotype:WT|tissue:pancreas|cell type:krt4 lineage traced cells|treatment:ablation|time:2 dy post single ablation", "GSM7085295", "GSM7085295: 10X 22 021  2 dy post single ablation; Danio rerio; RNA Seq", "GSM7085295 r1", "GSM7085295", "1", "Droplet based scRNA seq was performed using the Chromium Single Cell 3\u2032 Library and Gel Bead Kit v3 10\u00d7 Genomics and Chromium Single Cell 3\u2032 Chip G 10\u00d7 Genomics. Approximately 8 000 10 000 cells from each condition were loaded and encapsulated in a single v3 reaction. GEM generation and library preparation were performed according to manufacturer's instructions. Cells were partitioned into gel beads in emulsion in the controller for cell lysis and reverse transcription. The 10\u00d7 scRNA Seq libraries were PCR amplified 13 cycles  pooled  denatured  and diluted in prior to paired end sequencing on a NextSeq 500 according to manufacturer's recommendations. Sequencing data was aligned to the zebrafish reference genome GRCz11 with addition of the mCherry sequence using Cell Ranger v5.0.1 10\u00d7 Genomics to generate a gene by cell count matrix with default parameters.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP428435", null, "loader:fastq load.py", "P25452_2008_S8_L001_R1_001.fastq.gz P25452_2008_S8_L001_R2_001.fastq.gz", "fastq fastq", 10399611282.0, 88132299.0, "GSM7085295 r1", "0:28 1:90", "A:2977005008;C:2261455885;G:2402621333;T:2758168947;N:360109", 28, 90, null, null, 2977005008, 2261455885, 2402621333, 2758168947, 360109, "SRX19740078", "SRS17106152", "SRA1608504", "Karolinska Institute", "Karolinska Institute", 2, 0.00664, 0.91101, 0.00219, 0.14269, 0.9903, 0.71492, 0.31124, 0.52378, 28, 90, "T", "B", "sc-like readlen", "illumina", "nextseq", "unknown", "random_priming", "unknown", "sc", "single_cell_droplet", "10x", null, "Sweden", "2023-03-07", "Adult", "Adult", "Pancreas", "Endocrine 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": ["74419"], "units": {}, "query_ms": 9.739212000567932}