{"database": "metadata", "table": "run_metadata", "rows": [[65790, "SRR15626590", "SRX11923653", "SRS9937163", "SRP334274", "PRJNA758087", "Next Generation Sequencing of zebrafish intraspinal serotonergic neurons in the injury segment and distal segments post spinal cord injury", "GSE182869", "Transcriptome Analysis", "The goals of this study is to compare transcriptome profiles RNA seq of zebrafish intraspinal serotonergic neurons in the injury segment and distal segments post spinal cord injury. Bulk RNA Seq samples of ISNs from the injury area and residual segments respectively were FAC sorted from Tgtph2:GFP line. Total RNA was isolated using SMART SeqTM v4 UltraTM Low Input RNA Kit for Sequencing Clontech. Sequencing libraries N=5 6 were generated using NEBNext UltraTM RNA Library Prep Kit for Illumina following the manufacturer's instructions NEB. We mapped about 50 60 million sequence reads per sample to the zebrafish genome and identified 39 714 transcripts in the zebrafish intraspinal serotonergic neurons. Our study represents the detailed analysis of transcriptomes of zebrafish intraspinal serotonergic neurons in the injury segment and distal segments post spinal cord injury. Overall design: Bulk RNA Seq samples of intraspinal serotonergic neurons from the injury area and residual segments respectively were FAC sorted from Tgtph2:GFP line. Total RNA was extracted and cDNA libraries N=5 6 were subjected to Illumina sequencing according to the manufacturer's protocol.", "parent bioproject:PRJNA758278", "pubmed:34876587", null, "SP 6W 3", "GSM5538907", null, "source name:spinal cord|strain:Tgtph2:GFP|tissue:spinal cord segment in the injury site|cell type:serot1rgic neuron|disease state:6 8 xxx post injury", "SP 6W 3", "Raw data raw reads of fastq format were firstly processed through in house perl scripts. In this step  clean data clean reads were obtained by removing reads containing adapter  reads containing ploy N and low quality reads from raw data. At the same time  Q20  Q30 and GC content the clean data were calculated. All the downstream analyses were based on the clean data with high quality. Reference genome and gene model annotation files were downloaded from genome website directly. Index of the reference genome was built using Hisat2 v2.0.5 and paired end clean reads were aligned to the reference genome using Hisat2 v2.0.5. HTSeq v0.9.1 was used to count the reads numbers mapped to each gene. And then FPKM of each gene was calculated based on the length of the gene and reads count mapped to this gene. FPKM  expected number of Fragments Per Kilobase of transcript sequence per Millions base pairs sequenced  considers the effect of sequencing depth and gene length for the reads count at the same time  and is currently the most commonly used method for estimating gene expression levels. Genome build: danRer11 Supplementary files format and content: tab delimited text files include FPKM values for each Sample.", "spinal cord", null, "Spinal cord tissue of the injury area and residual segments were dissected out. Intraspinal serotonin neurons were isolated from Tgtph2:GFP line by FAC sorting  flash frozen on dry ice. Total RNA was isolated using SMART SeqTM v4 UltraTM Low Input RNA Kit for Sequencing Clontech. A total amount of 1 \u00b5g RNA per sample was used as input material for the RNA sample preparations. Sequencing libraries were generated using NEBNext\u00ae UltraTM RNA Library Prep Kit for Illumina\u00ae NEB  USA following manufacturer\u2019s recommendations and index codes were added to attribute sequences to each sample. RNA libraries were prepared for sequencing using standard Illumina protocols", null, "strain:Tgtph2:GFP|tissue:spinal cord segment in the injury site|cell type:serot1rgic neuron|disease state:6 8 xxx post injury", "GSM5538907", "GSM5538907: SP 6W 3; Danio rerio; RNA Seq", "GSM5538907", null, "1", "Spinal cord tissue of the injury area and residual segments were dissected out. Intraspinal serotonin neurons were isolated from Tgtph2:GFP line by FAC sorting  flash frozen on dry ice. Total RNA was isolated using SMART SeqTM v4 UltraTM Low Input RNA Kit for Sequencing Clontech. A total amount of 1 \u00b5g RNA per sample was used as input material for the RNA sample preparations. Sequencing libraries were generated using NEBNext\u00ae UltraTM RNA Library Prep Kit for Illumina\u00ae NEB  USA following manufacturer's recommendations and index codes were added to attribute sequences to each sample. RNA libraries were prepared for sequencing using standard Illumina protocols", "GEO Accession:GSM5538907", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina HiSeq 2000", null, "SRP334274", null, "loader:fastq load.py", "SP_6W_3_1.fq.gz SP_6W_3_2.fq.gz", "fastq fastq", 22917868200.0, 76392894.0, "GSM5538907 r1", "0:150 1:150", "A:6801610029;C:4223124283;G:4702480567;T:7190055774;N:597547", 150, 150, null, null, 6801610029, 4223124283, 4702480567, 7190055774, 597547, "SRX11923653", "SRS9937163", "SRA1284222", "GEO", "Neuroscience, School of Medcine, Tongji University, 42508444-9", 2, 0.57129, 0.57016, 0.16002, 0.16225, 0.91634, 0.91729, 0.59641, 0.5943, 150, 150, "B", "B", "biological fallback assumption", "illumina", "hiseq_era", "unknown", "cdna_unspecified", "nebnext", "sc", "single_cell_plate", "smartseq", null, "China", "2021-08-26", "Undetermined", "Undetermined", "Spinal Cord", "Nervous 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": ["65790"], "units": {}, "query_ms": 12.322511989623308}