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Sample GSM3359727

Query DataSets for GSM3359727

Status

Public on Aug 29, 2018

Title

shFAKctr

Sample type

SRA

Source name

Myc-CaP prostate cancer cell line

Organism

Mus musculus

Characteristics

strain: FVB; Hi-Myc transgenic
treatment: vehicle
transfection: shRNAs targeting FAK

Treatment protocol

Myc-CaP cells stably transfected with shRNAs targeting FAK or negative control were treated with 10μM norepinephrine or vehicle for 24 hours.

Growth protocol

Myc-CaP cells stably transfected with shRNAs targeting FAK or negative control were cultured in DMEM (Biological Industries, Israel) supplemented with 10% heat-inactivated fetal bovine serum (Biological Industries, Israel), 0.1mM nonessential amino acids (Gibico) and 1% Penicillin-Streptomycin (Gibico) at 37 °C in a humidified 5% CO2 incubator.

Extracted molecule

total RNA

Extraction protocol

RNA was harvested using Trizol reagent. RNA purity was checked using the NanoPhotomete spectrophotometer (IMPLEN, CA, USA). RNA concentration was measured using Qubit RNA Assay Kit in Qubit 2.0 Flurometer (Life Technologies, CA, USA). RNA integrity was assessed using the RNA Nano 6000 Assay Kit of the Bioanalyzer 2100 system (Agilent Technologies, CA, USA).
A total amount of 3 μg RNA per sample was used as input material for the RNA sample preparations. Sequencing libraries were generated using NEBNext UltraTM RNA Library Prep Kit for Illumina (NEB, USA) following manufacturer's recommendations and index codes were added to attribute sequences to each sample.

Library strategy

RNA-Seq

Library source

transcriptomic

Library selection

cDNA

Instrument model

Illumina NovaSeq 6000

Data processing

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 v2.0.5 and paired-end clean reads were aligned to the reference genome using Hisat2 v2.0.5. 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.
FeatureCounts v1.5.0-p3 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.
Genome_build: mm10
Supplementary_files_format_and_content: tab-delimited excel files include readcount values for each sample

Submission date

Aug 28, 2018

Last update date

Aug 29, 2018

Contact name

Yan Cheng

E-mail(s)

chengyan_cpu@hotmail.com

Organization name

University of Arkansas for Medical Sciences

Department

Internal Medicine