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Sample GSM5623994

Query DataSets for GSM5623994

Status

Public on Oct 16, 2021

Title

Sample type

SRA

Source name

MCROGLIA

Organism

Rattus norvegicus

Characteristics

cell type: Primary cell
treatment: treated with CYP11A1 gene containing adenovirus
strain: Sprague Dawley

Treatment protocol

Rats' mother was treatmented with control vehicle adenovirus or CYP11A1 gene containing adenovirus

Growth protocol

Rats were grow up to 3 mouths

Extracted molecule

total RNA

Extraction protocol

then small RNA library was constructed and
Sequencing libraries were generated using NEBNext® Multiplex Small RNA Library Prep Set for Illumina® (NEB, USA.)

Library strategy

RNA-Seq

Library source

transcriptomic

Library selection

cDNA

Instrument model

Illumina HiSeq 2500

Data processing

Sequencing libraries were generated using NEBNext® Ultra™ RNA Library Prep Kit for Illumina® (NEB, USA) following manufacturer’s recommendations and index codes were added to attribute sequences to each sample.
The clustering of the index-coded samples was performed on a cBot Cluster Generation System using TruSeq PE Cluster Kit v3-cBot-HS (Illumia) according to the manufacturer’s instructions. After cluster generation, the library preparations were sequenced on an Illumina Hiseq platform and 125 bp/150 bp paired-end reads were generated.
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 v2.0.4 and paired_x0002_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 (Trapnell, Cole, et al., 2010).
Genome_build: Gene Ontology (GO) enrichment analysis of differentially expressed genes was implemented by the GOseq R package, in which gene length bias wascorrected. GO terms with corrected Pvalue less than 0.05 were considered significantly enriched by differential expressed genes.
Supplementary_files_format_and_content: raw counts

Submission date

Oct 13, 2021

Last update date

Oct 16, 2021

Contact name

li tongtong

E-mail(s)

tongtongli@nwafu.edu.cn

Phone

15596828981

Organization name

xinong