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Identification of transcription factors responsible for dysregulated networks in human osteoarthritis cartilage by global gene expression analysis

GSE114007 Homo sapiens (human) RNA-seq (gene expression) 38 samples Submitted 2018/05/04 Platform GPL11154Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 38 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
38 samples
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Summary (written by the submitters)
Objective:Osteoarthritis (OA) is the most prevalent joint disease. As disease-modifying therapies are not available, novel therapeutic targets need to be discovered and prioritized for their importance in mediating the abnormal phenotype of cells in OA-affected joints. Here, we generated a genome-wide molecular profile of OA to elucidate regulatory mechanisms of OA pathogenesis and to identify possible therapeutic targets using integrative analysis of mRNA-sequencing data obtained from human knee cartilage.
Read the full summary ↓
Methods:RNA-sequencing (RNA-seq) was performed on 18 normal and 20 OA human knee cartilage tissues. RNA-seq datasets were analysed to identify genes, pathways and regulatory networks that were dysregulated in OA. Results:RNA-seq data analysis revealed 1332 differentially expressed (DE) genes between OA and non-OA samples, including known and novel transcription factors (TFs). Pathway analysis identified 15 significantly perturbed pathways in OA with ECM-related, PI3K-Akt, HIF-1, FoxO and circadian rhythm pathways being the most significantly dysregulated. We selected differentially expressed TFs that are enriched for regulating DE genes in OA and prioritized these transcription factors by creating a cartilage-specific interaction subnetwork. This analysis revealed 8 TFs, including JUN, EGR1, JUND, FOSL2, MYC, KLF4, RELA, and FOS that both target large numbers of dysregulated genes in OA and are themselves suppressed in OA. Conclusion:We identified a novel subnetwork of dysregulated TFs that represent new mediators of abnormal gene expression and promising therapeutic targets in OA.
This dataset
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE114007_RAW.tar (it can run to tens of gigabytes).

3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA454873 and SRA study SRP144491. Searching any of these in the dataset finder brings you back here.

Samples in this study

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