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Sample GSM2795209

Query DataSets for GSM2795209

Status

Public on Jun 28, 2018

Title

Flp8_NoDox_exp3_S202

Sample type

SRA

Source name

Flp-In™ T-Rex Hela cells with doxycycline-inducible EGFP transgene

Organism

Homo sapiens

Characteristics

cell line: Flp-In T-Rex Hela cells
genotype/variation: doxycycline-inducible EGFP transgene
passage: 8-9
treatment: none
experiment: 3

Treatment protocol

Cells were synchronized with a double thymidine arrest (18 hours 2mM thymidine, 9 hours release, 16 hours 2mM thymidine) and after 1 hour release harvested for mRNA isolation. The expression of PP1-NIPP1 wild-type or mutants was induced by the addition of 10 ng/ml Doxycycline to the medium of the cells for the last 13 hours before the cells were harvested.

Growth protocol

Cells were grown in low glucose-DMEM medium supplemented with 10% fetal bovine serum and penicilline/streptomycin

Extracted molecule

total RNA

Extraction protocol

RNA was extracted with the Mammalian Total RNA Miniprep kit (GenElute from SIGMA)
RNA concentration and purity were determined spectrophotometrically using the Nanodrop ND-1000 (Nanodrop Technologies) and RNA integrity was assessed using a Bioanalyzer 2100 (Agilent). Per sample, an amount of 1 microgram of total RNA was used as input. Using the Illumina TruSeq® Stranded mRNA Sample Prep Kit (protocol version: Part # 15031047 Rev. E - October 2013) poly-A containing mRNA molecules were purified from the total RNA input using poly-T oligo-attached magnetic beads. In a reverse transcription reaction using random primers, RNA was converted into first strand cDNA and subsequently converted into double-stranded cDNA in a second strand cDNA synthesis reaction using DNA PolymeraseI and RNAse H. The cDNA fragments were extended with a single ‘A’ base to the 3’ ends of the blunt-ended cDNA fragments after which multiple indexing adapters were ligated introducing different barcodes for each sample. Finally, enrichment PCR was carried out to enrich those DNA fragments that have adapter molecules on both ends and to amplify the amount of DNA in the library. Sequence-libraries of each sample were equimolarly pooled and sequenced on an Illumina NextSeq 500 instrument (High Output, 75 bp, Single Reads, v2) at the VIB Nucleomics core (www.nucleomics.be).

Library strategy

RNA-Seq

Library source

transcriptomic

Library selection

cDNA

Instrument model

Illumina NextSeq 500

Data processing

Read Preprocessing: Low quality ends and adapter sequences were trimmed off from the Illumina reads with FastX 0.0.14 and Cutadapt 1.7.1. Using FastX 0.0.14 and ShortRead 1.24.0, we filtered subsequently small reads (length < 35 bp), polyA-reads (more than 90% of the bases equal A), ambiguous reads (containing N) and low quality reads (more than 50% of the bases < Q25). With Bowtie2 v2.2.4 we identified and removed reads that mapped to the spiked-in PhiX. The number of processed reads per sample then varied between 16,086,947 and 20,042,939.
Alignment: Processed reads were aligned with STAR v2.4.1d to the reference genome of Homo sapiens (GRCh38), as downloaded from the Genome Reference Consortium. Default STAR parameter settings were used, except for ‘outSAMprimaryFlag=OneBestScore’, ‘twopassMode=Basic’, ‘alignIntronMin=50’, ‘alignIntronMax=500000’, ‘outSAMtype=BAM’, SortedByCoordinate. Using Samtools 1.1, reads with a mapping quality smaller than 20 were removed from the alignments.
Counting: Transcript coordinates were extracted from the GRC reference annotation with Gffread from the Cufflinks v2.1.1 suite and merged to gene coordinates with mergeBed from the Bedtools v2.17.0 toolkit. GC content and gene length were derived from the gene coordinates. The numbers of aligned reads per gene were summarized using featureCounts 1.4.6 with parameters ‘Q=0’, ‘s=2’, ’t=exon’ and ‘g=gene_id’. We removed 41,248 genes for which all samples had less than 1 count-per-million. As such, we continued with raw counts for 16,985 genes. Raw counts were further corrected within samples for GC-content and between samples using full quantile-normalization, as implemented in the EDASeq package from Bioconductor.
Identifying differential gene expression: With the EdgeR 3.16.5 package, a negative binomial generalized linear model (GLM) was fitted against the normalized counts. We did not use the normalized counts directly, but worked with offsets. Differential expression was tested for with a GLM likelihood ratio test, also implemented in the EdgeR package. The resulting p-values were corrected for multiple testing with Benjamini-Hochberg to control the false discovery rate.
Genome_build: GRCh38
Supplementary_files_format_and_content: One tab-delimited text file with raw read counts per gene and per sample. Gene IDs are Ensembl IDs.

Submission date

Sep 27, 2017

Last update date

May 15, 2019

Contact name

Rekin's Janky

E-mail(s)

Nucleomics.Bioinformatics@vib.be

Organization name

VIB

Department

Nucleomics Core