run_metadata: 67824

This data as json

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
67824	SRR17335720	SRX13511114	SRS11405355	SRP352585	PRJNA792582	circRNA based biomarker candidates for acute cypermethrin and chlorpyrisfos toxication in the brain of Zebrafish Danio rerio	GSE192669	Transcriptome Analysis	Cypermethrin CYP and chlorpyrifos CPF are pesticides which are frequently used in agricultural areas around the world. These chemicals have been shown to cause serious toxicological damage in the brain of fish which is non target organisms. However circRNAs associated with acute brain toxicity caused by cypermethrin and chlorpyrifos have not been studied yet. In this study circRNAs were identified and characterized using RNA seq in Zebrafish brains exposed to acute cypermethrin and chlorpyrifos toxicity. A total of 10375 circRNAs were detected. It was determined that 6 circRNAs were up regulated 10 circRNAs were down regulated in CYP brain samples compared to controls . In addition it was found that 57 circRNAs are up regulated and 3 circRNAs down regulated in CPF brain samples compared to controls. Moreover 62 circRNAs were down regulated in the CYP samples when CYP and CPF samples were compared. However up regulated circRNA could not be detected. It was revealed that the detected circRNAs specifically regulated the MAPK signaling pathway endocytosis mechanism apoptosis and p53 signaling pathway. This study which was conducted for the first time in terms of the subject of the study could bring a different perspective especially to pesticide toxicity studies. Overall design: Examination of circRNA related to acute cypermethrin and chlopyrifos toxication in brain of zebrafish		pubmed:35304207		CPF2	GSM5754469		source name:Brain tissue\|tissue:Brain\|treatment:CPF toxication\|geo loc name:missing\|collection date:missing	CPF2	Raw data raw reads of FASTQ format were firstly processed through in house scripts. In this step clean data clean reads were obtained by removing reads containing adapter and poly N sequences and reads with low quality from raw data. At the same time Q20 Q30 and GC content of the clean data were calculated. All the downstream analyses were based on the clean data with high quality.An upgraded computational pipeline CIRCexplorer2 is applied to detect circRNAs and identify alternative back splicing in back spliced circular RNAs circRNAs The expression of circRNAs is usually represented by the fragments that are mapped to the back spliced exon–exon junction sites. In addition to the raw fragment numbers normalized RNA seq fragments that are mapped to a specific back spliced exon–exon junction by total mapped fragments is used to quantitate circRNA expression. With FPM Fragments mapped to back spliced junction Per Million mapped fragments circRNAs from different samples with distinct sequencing depths can be directly compared. The input data for differential gene expression analysis is read counts from gene expression level analysis. For DESeq2 with biological replicates Differential expression analysis between two conditions/groups three biological replicates per condition was performed using DESeq2 R package. DESeq2 provides statistical routines for determining differential expression in digital gene expression data using a model based on the negative binomial distribution. The resulting P values were adjusted using the Benjamini and Hochberg’s approach for controlling the False Discovery Rate FDR. Genes with an adjusted P value < 0.05 found by DESeq2 were assigned as differentially expressed. A common way for searching shared functions among genes is to incorporate the biological knowledge provided by biological ontologies. Gene Ontology GO annotates genes to biological processes molecular functions and cellular components in a directed acyclic graph structure and Kyoto Encyclopedia of Genes and Genomes KEGG annotates genes to pathways. KEGG is a database resource for understanding high level functions and utilities of the biological system such as the cell the organism and the ecosystem from molecular level information especially large scale molecular datasets generated by genome sequencing and other high throughput experimental technologies http://www.genome.jp/kegg/. We used KOBAS software to test the statistical enrichment of differential expression genes or circRNA host genes in KEGG pathways. circRNAs can act as miRNA sponge to inhibit the functioning of miRNAs. To further study the functions of circRNAs microRNA target site in exons of circRNA loci were identified using miRanda animal species or psRobot plant species. software could be used to construct the circRNA miRNA gene networks. Genome build: UMD3.1	Brain tissue		Total RNA was isolated with Trizol from brain tissues RNA libraries were prepared for sequencing using standard Illumina protocols		tissue:Brain\|treatment:CPF toxication	GSM5754469	GSM5754469: CPF2; Danio rerio; ncRNA Seq	GSM5754469 r1	GSM5754469	1	Total RNA was isolated with Trizol from brain tissues RNA libraries were prepared for sequencing using standard Illumina protocols		ncRNA-Seq	TRANSCRIPTOMIC	size fractionation	PAIRED	ILLUMINA	Illumina HiSeq 4000		SRP352585		loader:fastq load.py	CPF2_1.fq.gz CPF2_2.fq.gz	fastq fastq	14881715100.0	49605717.0	GSM5754469 r1	0:150 1:150	A:4214905088;C:3201163283;G:3225795074;T:4239665352;N:186303	150	150			4214905088	3201163283	3225795074	4239665352	186303	SRX13511114	SRS11405355	SRA1349262	Atatürk University	Atatürk University	2	0.87491	0.87638	0.40844	0.40479	0.67123	0.67018	0.49174	0.48952	150	150	B	B	biological fallback assumption	illumina	hiseq_era	unknown	size_fractionation	unknown	bulk	unknown	unknown		Turkey	2021-12-27	Undetermined	Undetermined	Brain	Nervous System