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Sample GSM6108280

Query DataSets for GSM6108280

Status

Public on Jun 30, 2022

Title

4T1, serum free medium control, 24h, biol rep 2 [SK3R8_Tdctrl3]

Sample type

SRA

Source name

4T1

Organism

Mus musculus

Characteristics

cell line: 4T1
cell type: murine breast cancer
time: 24h
treatment: serum free medium control

Treatment protocol

Cells were washed two times with PBS. Then 1 mL of serum-free Opti-MEM medium with or without 100 ng/mL of IL-22 was added to each of the three biological replicates, followed by an incubation for 24 h in a humidified atmosphere at 37°C and 5% CO2.

Growth protocol

0.3 × 10^5 4T1 cells were seeded into six-well plates and were grown in RPMI medium, supplemented with 10 % fetal bovine serum, 100 μg/ml streptomycin, 1 IU/ml penicillin, and 2 mM L-glutamine, and grown for 24 h in a humidified atmosphere at 37°C and 5% CO2.

Extracted molecule

total RNA

Extraction protocol

Extraction was performed at room temperature using TRIzol reagent (Invitrogen) according to the manufacturers instructions. RNA quality was asessed using a Bioanalyzer (Agilent Technologies) with the Agilent RNA 6000 Nano Kit (Agilent Technologies) according to the manufacturers instructions.
Up to 500ng of RNA were used with the 3’ mRNA-Seq Library Prep Kit Protocol for Ion Torrent (QuantSeq-LEXOGEN™ Vienna, Austria), following the manufacturer’s instructions. Library quality and quantity was analyzed with the DNA High Sensitivity Kit (Agilent Technologies) in Bioanalyzer (Agilent Technologies). After pooling, templating and enrichment of the libraries was performed on an Ion Proton One Touch system. The pools were templated using the Ion PI™ Hi-Q™ OT2 200 Kit (ThermoFisher Scientific) and then sequenced with the Ion PI™ Hi-Q™ Sequencing 200 Kit on Ion Proton PI™ V2 chips (ThermoFisher Scientific), following commercially available protocols.

Library strategy

RNA-Seq

Library source

transcriptomic

Library selection

cDNA

Instrument model

Ion Torrent Proton

Data processing

Differential gene expression analysis was performed with the Bioconductor package metaseqR. A 3'UTR read counts table was created from the BAM files resulting the short-read mapping with the Bioconductor GenomicRanges. The Bioconductor package DESeq was used to normalize for inherent systematic or experimental biases (e.g. GC-content bias, sequencing depht, gene lenght, etc.), after removal of genes with zero counts over all samples.
Genes with any of the following features were filtered out before further analysis: i) total gene length less than 500, ii) average reads per 100 bp less than the 25th quantile of the total normalized distribution of average reads per 100 bp, iii) genes with read counts below the median read counts of the total normalized count distribution, iv) Ensembl biotype matching the following: rRNA, TR_V_pseudogene, TR_J_pseudogene, IG_C_pseudogene, IG_J_pseudogene, IG_V_pseudogene, v) genes where 50% of samples did not present more than five normalized counts across all samples.
Differential gene expression analysis for the contrast of the control versus the treated samples was performed utilizing Bioconductor packages DESeq, edgeR, limma, NBPSeq, and NOISeq.
PANDORA weighted p-value was calculated and applied to combine the statistical significance of the aforementioned algorithms.
Assembly: hg19
Supplementary files format and content: metaseqr_sig_out_Tdctrl_vs_Tdil22.txt: Tab-delimited text file containing log2 and rpgm normalized 3’UTR read counts of significantly differentially expressed genes for each sample.
Supplementary files format and content: metaseqr_all_out_Tdctrl_vs_Tdil22.txt: Tab-delimited text file containing log2 and rpgm normalized 3’UTR read counts of all differentially expressed genes for each sample.

Submission date

May 05, 2022

Last update date

Jun 30, 2022

Contact name

Daria Briukhovetska

Organization name

Klinikum der Universität München

Department

Division of Clinical Pharmacology

Street address

Lindwurmstraße 2a