{"database": "metadata", "table": "run_metadata", "rows": [[34930, "SRR32424870", "SRX27754015", "SRS24139546", "SRP565442", "PRJNA1226487", "Separate brainstem circuits for fast steering and slow exploratory turns", "GSE290157", "Transcriptome Analysis", "During locomotion  trajectory changes necessitate precise tuning of descending commands to scale turning movements according to specific tasks or objectives  resulting in either rapid steering turns during prey pursuit or routine shallow turns associated with exploration. We show that these two types of turning are controlled by separate brainstem circuits that encode rapid steering turning versus slow exploratory turns. The circuit for rapid steering is widely distributed across different brainstem nuclei  involving specific excitatory V2a and inhibitory commissural V0d neurons. The steering V2a and V0d neurons are furthermore coupled via gap junctions and simultaneously recruited to ensure rapid steering through an asymmetrical recruitment of spinal motor neurons. The recruitment of these steering neurons is primarily associated with the degree of the direction change  rather than the locomotor frequency. The brainstem steering neurons are  in turn  controlled by a subset of V2a neurons in the pretectum activated by salient visual input. Conversely  the circuit controlling swim related slow exploratory turns comprises a different set of V2a neurons localized in fewer brainstem nuclei. These findings demonstrate a modular organization of the brainstem circuits that control rapid steering and slow exploratory turning during locomotion. Overall design: CaD neurons were taken fromTg  gly2: GFP zebrafish brain stem  one cell from each fish  a total of eight fish", null, null, null, "Glycinergic neurons m5", "GSM8807150", null, "tissue:Glycinergic neurons|cell type:Glycinergic neurons|genotype:Tg gly2: GFP|geo loc name:missing|collection date:missing", "Glycinergic neurons m5", "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  Q30and 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 v2.0.4 and paired end clean reads were aligned to the reference genome using Hisat2 v2.0.4. We selected Hisat2 as the mapping tool for that Hisat2 can generate a database of splice junctions based on the gene model annotation file and thus a better mapping result than other non splice mapping tools. 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. Assembly: danio rerio Ensembl 97 Supplementary files format and content: FPKM values for each samples.", "Glycinergic neurons", null, "RNA was harvested using SMART Seq v4 Ultra Low Input RNA Kit Takara Bio USA  Inc. Sequencing libraries were generated using NEBNext\u00ae Ultra\u2122 RNA Library Prep Kit for Illumina\u00ae NEB  USA following manufacturer\u2019s recommendations and index codes were added to attribute sequences to each sample.", null, "cell type:Glycinergic neurons|genotype:Tg gly2: GFP", "GSM8807150", "GSM8807150: Glycinergic neurons m5; Danio rerio; RNA Seq", "GSM8807150 r1", "GSM8807150", "1", "RNA was harvested using SMART Seq v4 Ultra Low Input RNA Kit Takara Bio USA  Inc. Sequencing libraries were generated using NEBNext\u00ae Ultra\u2122 RNA Library Prep Kit for Illumina\u00ae NEB  USA following manufacturer's recommendations and index codes were added to attribute sequences to each sample.", null, "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP565442", null, null, "M5_1.fq.gz M5_2.fq.gz", "fastq fastq", 8381104622.0, 30664708.0, "GSM8807150 r1", null, "A:2289409726;C:1427540731;G:1492945660;T:3168884923;N:2323582", null, null, null, null, 2289409726, 1427540731, 1492945660, 3168884923, 2323582, "SRX27754015", "SRS24139546", "SRA2081247", "TongJi university", "TongJi university", null, null, null, null, null, null, null, null, null, null, null, "B", "B", "biological fallback assumption", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "nebnext", "sc", "single_cell_plate", "smartseq", null, "China", "2025-02-21", "Undetermined", "Undetermined", "Brain", "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": ["34930"], "units": {}, "query_ms": 10.71308999962639}