GEO Accession viewer

NCBI > GEO > Accession Display

Not logged in | Login

GEO help: Mouse over screen elements for information.

Sample GSM3330450

Query DataSets for GSM3330450

Status

Public on Jan 09, 2019

Title

D18-3362 : Pro BR2 (TCCGCGAATAATCTTA)

Sample type

SRA

Source name

Brain

Organism

Xenopus laevis

Characteristics

tissue: Brain
treatment: Progesterone treatment

Extracted molecule

total RNA

Extraction protocol

Total RNA for each sample was isolated by using TRIzolTM Reagent (Ambion, Invitrogen #15596018) –chloroform, following standard manufacturer’s protocol.
NGS analyses were performed by The MIT BioMicro Center (Boston, MA). Samples were quality controlled on a Fragment Analyzer (Advanced Analytical) to determine DV200 scores. The mRNA from 1 μg of total RNA was isolated using Illumina human/mouse/rat RiboZero Gold and prepared into Illumina libraries using the Kapa RNA HyperPrep kit and 10 cycles of amplification. Final libraries were pooled and quality controlled using qPCR (Roche LC480II) as well as the Fragment Analyzer and sequenced on HiSeq2000 for 40 nucleotides. Following sequencing, data processing was performed using the standard Illumina pipeline. Fastq files were generated for data processing and assembly.

Library strategy

RNA-Seq

Library source

transcriptomic

Library selection

cDNA

Instrument model

Illumina HiSeq 2000

Data processing

The quality of the RNA-Seq sequence data was first evaluated using FastQC prior to further downstream analysis. Low quality sequences were trimmed and poor quality reads were removed using Trimmomatic.
Differential gene (DE) expression analysis was conducted using The Star Aligner to map high quality single end reads to the genome, X. laevis v9.2 and the gene annotation was downloaded from Xenbase. Gene expression was obtained using RSEM
The expected read counts and Fragments Per Kilobase of transcript per Million mapped reads (FPKM), were extracted for further analysis. The estimated read counts were used as input for edgeR to perform DE analysis
A generalize linear regression model was developed to identify DE genes and the thresholds were set at FDR 0.05 and fold change of greater than 2 or less than 0.5. Three comparisons were performed (comparing Control, Sham, and Prog-Device amongst each other).
Genome_build: X. laevis v9.2
Supplementary_files_format_and_content: Excel sheet with normalized counts for each sample, log2 fold change, p-value, gene identifier.

Submission date

Aug 13, 2018

Last update date

Jan 09, 2019

Contact name

Christopher Joseph Martyniuk

E-mail(s)

CMARTYN@UFL.EDU

Organization name

Department

Physiological Sciences

Street address