{"database": "metadata", "table": "run_metadata", "rows": [[64414, "SRR14702158", "SRX11040181", "SRS9109179", "SRP322166", "PRJNA734313", "Single cell profiling of photoreceptor cells in adult zebrafish", "GSE175929", "Other", "Vertebrate vision is mediated by two kinds of photoreceptors  rods and cones  responsible for dim  and bright light vision  respectively. Gene expression differences among cone subtypes remain poorly understood compared with rods. We generated single cell transcriptome data using a droplet based approach to reveal the extent of gene expression diversity among adult zebrafish photoreceptor subtypes. Populations of photoreceptor cells were enriched by using the transgenic zebrafish lines  Tgrho:EGFPja2Tg and Tggnat2:EGFPja23Tg  which express GFP in rods and all cone subtypes  respectively. By analyzing the single cell transcriptomes  we found that in addition to the four canonical zebrafish cone types ultraviolet  blue  green and red  there exist subpopulations of green and red cones in the ventral retina that express red shifted opsin paralogs opn1mw4 and opn1lw1. This work lays a foundation for future studies aimed at understanding how molecular differences among cone subtypes affect photoreceptor function. Overall design: GFP positive cells collected from two transgenic zebrafish  Tgrho:EGFPja2Tg and Tggnat2:EGFPja23Tg were combined into one sample. A small percentage of GFP negative cells was also included in the sample.", null, "pubmed:34462505", null, "retinal cells", "GSM5351368", null, "tissue:retinal cells|age:adult|transgene:Tgrho:egfpja2Tg|transgene:Tggnat2:egfpja23Tg", "retinal cells", "FASTQ files were generated from the raw BCL files using Illumina\u2019s bcl2fastq conversion program. Sample demultiplexing with the mkfastq function from Cell Ranger softwareversion 3.1.0  10X Genomics. Sample alignment with the count function from Cell Ranger software version 6.0.0  10X Genomics. Paired end reads were mapped to the zebrafish genome GRCz11 using Cell Ranger software version 6.0.0  10X Genomics. Mapped reads were quantified using the Cell Ranger software with a custom annotation v432 dr adult eye.gtf  included as processed file. The GFP transcript sequence was added manually to the reference assembly as an extra chromosome. Data were analyzed using the Seurat R package v4.0.0. We retained all cells that expressed >500 genes  and we considered all genes expressed in at least five cells.  Cells with greater than 30% mitochondrial gene content or >40 000 unique molecular identifiers were removed from the analysis. For the remaining cells  a gene expression matrix was normalized to total cellular read counts using the Seurat SCTransform function. The 3 000 most variable genes  identified by the SCTransform function  were used for Principal Component Analysis. The top 30 principal components were selected for subsequent analysis. Graph based clustering was performed to obtain a set of transcriptionally distinct clusters. At this point in the analysis  we deliberately set parameters to \"over cluster\" the data  to avoid combining distinct cell types and to identify sub populations of low quality cells for removal. To retain high quality photoreceptors and bipolar cells only  we subjected our data to multiple rounds of clustering  filtering  and selection. In the first round  we retained those clusters characterized either by the presence of one or more of the following opsin genes or phototransduction genes rho  opn1sw1  opn1sw2  opn1mw1  opn1mw2  opn1mw3  opn1mw4  opn1lw1  opn1lw2  gnat1  or gnat2 or bipolar specific genes e.g.  gnao1b   vsx1   cabp2a  cabp5a and cabp5b among the top 20 most differentially expressed genes as identified by the FindAllMarkers function in Seurat. We also removed clusters consisting of low quality cells with low total gene counts 500 1 000 genes/cell compared with high quality photoreceptor clusters 1 000 3 000 genes/cell for rods and 1 000 4 000 genes/cell for cones. In the second round of clustering and selection  we removed clusters that showed co expression of photoreceptor genes and M\u00fcller glial genes icn  fxyd6l  mt2  rlbp1a  and glula. We also removed one cluster showing co expression of photoreceptor and bipolar genes and with low total gene counts. In the final round of clustering and selection  we removed a rod subpopulation with low total gene counts and retained 2 186 high quality cells. Genome build: GRCz11 Supplementary files format and content: The Gene transfer format GTF containing information about gene structure used for counting the transcripts in the data Supplementary files format and content: Seurat object for scRNA seq data", "retinal cells", null, "Retinas of five mpf adult zebrafish were were harvested at around zeitgeber time 3 ZT 3. The dissected retinas were dissociated with a papain dissociation solution  followed by further incubation with 10% FBS in DMEM and DNaseI. post the trituration  the samples were resuspended in sorting buffer 20 mM HEPES and 0.04% bovine serum albumin in Calcium  and magnesium free HBSS  pH 7.4. Four retinas from two individuals were combined for Tgrho:EGFP fish  while six retinas from three individuals were combined for Tggnat2:EGFP fish. The filtered samples were incubated in a solution of propidium iodide and Hoechst 33342. GFP positive cells were isolated via fluorescence activated cell sorting FACS. Dead cells were then removed based on propidium iodide positivity. Intact rods and cones were then selected based on the presence of both blue Hoechst 33342 and green fluorescence GFP. About 35 000 viable  intact GFP positive cells PI   GFP+  Hoechst+ and 1 500 GFP negative cells PI   GFP   Hoechst+ were collected from Tggnat2:EGFP fish  while 10 000 GFP viable  intact GFP positive cells and 1 500 GFP negative cells were collected from Tgrho:EGFP fish. These isolated cells were collected into the sorting buffer in one tube. Approximately 6 000 single cells were loaded into a 10X Chromium Single Cell Chip. Single cell libraries were made with Chromium 3\u2019 v3 platform following the manufacturer\u2019s protocol. RNA libraries were prepared for sequencing using standard Illumina protocols.", null, "age:adult|transgene:Tgrho:egfpja2Tg|transgene:Tggnat2:egfpja23Tg", "GSM5351368", "GSM5351368: retinal cells; Danio rerio; RNA Seq", "GSM5351368", null, "1", "Retinas of five mpf adult zebrafish were were harvested at around zeitgeber time 3 ZT 3. The dissected retinas were dissociated with a papain dissociation solution  followed by further incubation with 10% FBS in DMEM and DNaseI. post the trituration  the samples were resuspended in sorting buffer 20 mM HEPES and 0.04% bovine serum albumin in Calcium  and magnesium free HBSS  pH 7.4. Four retinas from two individuals were combined for Tgrho:EGFP fish  while six retinas from three individuals were combined for Tggnat2:EGFP fish. The filtered samples were incubated in a solution of propidium iodide and Hoechst 33342. GFP positive cells were isolated via fluorescence activated cell sorting FACS. Dead cells were then removed based on propidium iodide positivity. Intact rods and cones were then selected based on the presence of both blue Hoechst 33342 and green fluorescence GFP. About 35 000 viable  intact GFP positive cells PI   GFP+  Hoechst+ and 1 500 GFP negative cells PI   GFP   Hoechst+ were collected from Tggnat2:EGFP fish  while 10 000 GFP viable  intact GFP positive cells and 1 500 GFP negative cells were collected from Tgrho:EGFP fish. These isolated cells were collected into the sorting buffer in one tube. Approximately 6 000 single cells were loaded into a 10X Chromium Single Cell Chip. Single cell libraries were made with Chromium three prime v3 platform following the manufacturer's protocol. RNA libraries were prepared for sequencing using standard Illumina protocols.", "GEO Accession:GSM5351368", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP322166", null, null, "Cone_S5_L003_R1_001.fastq.gz Cone_S5_L003_R2_001.fastq.gz", "fastq fastq", 68659489710.0, 544916585.0, "GSM5351368 r1", "0:28 1:98", "A:19580055351;C:15466801940;G:15266233048;T:18341055919;N:5343452", 28, 98, null, null, 19580055351, 15466801940, 15266233048, 18341055919, 5343452, "SRX11040181", "SRS9109179", "SRA1239213", "GEO", "Pathology and Immunology, Washington University School of Medicine", 2, 0.0102, 0.85996, 0.00306, 0.14003, 0.98977, 0.84595, 0.44136, 0.62184, 28, 98, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2021-06-01", "Adult", "Adult", "Eye", "Sensory 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": ["64414"], "units": {}, "query_ms": 8.820721006486565}