{"database": "metadata", "table": "run_metadata", "rows": [[76725, "SRR25288287", "SRX21031898", "SRS18304344", "SRP449631", "PRJNA994919", "Diverse Epithelial Lymphocytes in Zebrafish Revealed Using a Novel Scale Biopsy Method", "GSE237417", "Transcriptome Analysis", "Zebrafish Danio rerio are a compelling model to study lymphocytes because zebrafish and humans have similar adaptive immune systems  including their lymphocytes. Antibodies that recognize zebrafish proteins are sparse  so many investigators utilize transgenic  lymphocyte specific fluorophore labeled lines. Human and zebrafish lymphocyte types are conserved  but many aspects of zebrafish lymphocyte biology remain uninvestigated  including lymphocytes in peripheral tissues  like epidermis. Here  we report the first study focused on zebrafish epidermal lymphocytes  using scales. Obtaining zebrafish blood via non lethal methods is difficult; scales represent a source to longitudinally sample live fish. We developed a novel biopsy technique  collecting scales to analyze epithelial lymphocytes from several fluorescently labeled lines. We imaged scales via confocal microscopy and demonstrated multiple lymphocyte types in scales/epidermis  quantifying them flow cytometrically. We profiled gene expression of scale  thymic  and marrow lymphocytes from the same animals  revealing B  and T lineage signatures. Single cell qRT PCR and RNA sequencing scRNA seq show not only canonical B and T cells  but also novel lymphocyte populations not described previously. To validate longitudinal scale biopsies  we serially sampled scales from fish treated with dexamethasone DXM  demonstrating epidermal lymphocyte responses. To analyze cells functionally  we employed a bead ingestion assay  showing thymic  marrow  and epidermal lymphocytes have phagocytic activity. In summary  we establish a novel  non lethal technique to obtain zebrafish lymphocytes  providing the first quantification  expression profiling  and functional data DXM responses and phagocytosis from epidermal lymphocytes in the zebrafish model. Overall design: This experimental study aimed to investigate the gene expression profiles of individual lymphocytes from the zebrafish lck:GFP transgenic line by using single cell RNA sequencing scRNA seq analysis. We performed scRNA seq on GFPhi thymocytes and GFPlo scale/marrow cells from lck:GFP fish which mark different lymphocyte populations. scRNA seq data reveal diverse thymic  scale  and marrow lymphocyte populations for subsequent transcriptomic analysis and isolation of specific cell types.", null, "pubmed:39503619", null, "Kidney Marrow S2", "GSM7611260", null, "source name:Kidney Marrow|tissue:Kidney Marrow|cell line:NA|cell type:Lymphocytes|genotype:lck:GFP|geo loc name:missing|collection date:missing", "Kidney Marrow S2", "post conversion to fastq files  reads for each sample were processed and aggregated using the 10x Genomics Cell Ranger v.6.0.0 pipeline no normalization  default settings and processed in the Seurat R package v.4.3.0. We obtained transcriptomes for 6 359 cells post Cell Ranger processing. SoupX v.1.6.2 was used to model and remove ambient RNA contamination per sample  and scDblFinder v.1.12.0 was used to detect potential multiplets default settings  per individual tissue type. Additional QC filtering was performed to remove potential dead or dying cells along with cells exhibiting abnormal read/gene counts and high levels of mitochondrial transcripts  resulting in 1 890 usable cells for our analysis. Using fastMNN  cells were normalized and integrated  and then clustered within Seurat Leiden algorithm. Clustering resolution was optimized using the clustree package v.0.5.0. Cluster boundaries were manually examined and fine tuned to optimize biological interpretation. Collective diagnostic gene signatures corresponding to published gene lists and our own sc qRT PCR results were explored using Seurat and UCell v.2.2.0. Preferential gene markers were determined for each distinct population using the FindAllMarkers function within Seurat  to aid in cell type assignment p.adj \u2264 0.05  min.pct = 0.25. Assembly: GRCz11 Supplementary files format and content: Tab delimited value files and matrices.", "Kidney Marrow", null, "For procedures  zebrafish subjects were anesthetized with 0.02% tricaine methanesulfonate. Thymus  kidney marrow and scale samples were dissected and placed in 500 ul cell media RPMI + 1% FBS + 1% Pen/Strep. Single cell suspensions were prepped by dissociating tissues using a pestle and passed through 35 um filters. Various fluorescent populations were sorted from the lymphoid and precursor gates using a BD FACSJazz Instrument analysis performed in FlowJo softare. Following creation of single cell emulsions  uniquely identifiable 1st strand template single cell cDNA libraries were generated from each cell by emulsion PCR. 2nd strand cDNA was generated and ligated to compatible Illumina adapters. Libraries were loaded onto single NovaSeq 6000 lanes and sequenced  using read lengths of 28 bp for the first read  120 bp for the second read  and 8 base index reads.", null, "tissue:Kidney Marrow|cell line:NA|cell type:Lymphocytes|genotype:lck:GFP", "GSM7611260", "GSM7611260: Kidney Marrow S2; Danio rerio; RNA Seq", "GSM7611260 r1", "GSM7611260", "1", "For procedures  zebrafish subjects were anesthetized with 0.02% tricaine methanesulfonate. Thymus  kidney marrow and scale samples were dissected and placed in 500 ul cell media RPMI + 1% FBS + 1% Pen/Strep. Single cell suspensions were prepped by dissociating tissues using a pestle and passed through 35 um filters. Various fluorescent populations were sorted from the lymphoid and precursor gates using a BD FACSJazz Instrument analysis performed in FlowJo softare. Following creation of single cell emulsions  uniquely identifiable 1st strand template single cell cDNA libraries were generated from each cell by emulsion PCR. 2nd strand cDNA was generated and ligated to compatible Illumina adapters. Libraries were loaded onto single NovaSeq 6000 lanes and sequenced  using read lengths of 28 bp for the first read  120 bp for the second read  and 8 base index reads.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP449631", null, "loader:fastq load.py", "3_Mo_1ck_KM_S2_L001_I1_001.fastq.gz 3_Mo_1ck_KM_S2_L001_R1_001.fastq.gz 3_Mo_1ck_KM_S2_L001_R2_001.fastq.gz", "fastq fastq fastq", 14406058368.0, 92346528.0, "GSM7611260 r1", "0:8 1:28 2:120", "A:3212551102;C:2439333260;G:2665663309;T:2763896751;N:138938", 8, 28, 120, null, 3212551102, 2439333260, 2665663309, 2763896751, 138938, "SRX21031898", "SRS18304344", "SRA1673435", "Pediatrics, University of Oklahoma Health Sciences Center", "Pediatrics, University of Oklahoma Health Sciences Center", 1, 0.92665, null, 0.1896, null, 0.8268, null, 0.56354, null, 120, null, "B", null, "usable mapping rate", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2023-07-14", "Undetermined", "Undetermined", "Multi-tissue", "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": ["76725"], "units": {}, "query_ms": 6.8656439980259165}