GEO Accession viewer

NCBI > GEO > Accession Display

Not logged in | Login

GEO help: Mouse over screen elements for information.

Sample GSM4487280

Query DataSets for GSM4487280

Status

Public on Jul 01, 2021

Title

Resp18 mutant 3

Sample type

SRA

Source name

Resp18 mutant 3

Organism

Rattus norvegicus

Characteristics

genotype/variation: Resp18 mutant
tissue: Kidney
gender: Male
age: 7 Weeks

Extracted molecule

total RNA

Extraction protocol

At the age of 6 weeks, both control and Resp18mutant rats diet was switched to det containing 2% high salt diet. Rats were euthanized after one week exposure to 2% high salt diet and kidneys were removed, flash frozen on liquid nitrogen, and total RNA was isolated using PureLink RNA Mini Kit. NEBNext® Ultra™ RNA Library Prep Kit for Illumina® (NEB, USA) following manufacturer’s recommendations was used with 3 ug of total RNA for the construction of sequencing libraries.
RNA libraries were prepared for sequencing using Illumina protocols

Library strategy

RNA-Seq

Library source

transcriptomic

Library selection

cDNA

Instrument model

Illumina HiSeq 4000

Description

M2_38

Data processing

Base Quality and Phred score relationship with the Illumina CASAVA v1.8 software:
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 2.1.0 and paired- end clean reads were aligned to the reference genome using HISAT2.
HTSeq v0.6.1 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 C, Williams BA, Pertea G, Mortazavi A, Kwan G, van Baren MJ, Salzberg SL, Wold BJ, Pachter L. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol. 2010 May;28(5):511-5.).
Genome_build: Rnor_5.0
Supplementary_files_format_and_content: fpkm.stat: gene count table of different expression levels, calculation of gene numbers in different expression levels and the expression levels of each single gene.
Supplementary_files_format_and_content: fpkm, expression quantification table, calculation of all genes' RPKM.
Supplementary_files_format_and_content: readcount: gene expression quantification table, calculation of all genes' readcount.

Submission date

Apr 21, 2020

Last update date

Jul 01, 2021

Contact name

Sivarajan Kumarasamy

E-mail(s)

Sivarajan.Kumarasamy@utoledo.edu

Organization name

University of Toledo College of Medicine and Life Sciences

Department

Physiology Pharmacology