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Diverse Targets of the Transcription Factor STAT3 Contribute to T Cell Pathogenicity and Homeostasis

GSE21671 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 19 samples Submitted 2010/05/30 Platform GPL9185Platform GPL1261
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 19 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Mus musculus (mouse)
Samples
19 samples
Data you can get
A processed expression table (series matrix) and the array files, from NCBI.
Summary (written by the submitters)
STAT3, an essential transcription factor with pleiotropic functions, plays critical roles in the pathogenesis of autoimmunity. Despite recent data linking STAT3 with inflammatory bowel disease, exactly how it contributes to chronic intestinal inflammation is not known. Using a T cell transfer model of colitis we found that STAT3 expression in T cells was essential for the induction of both colitis and systemic inflammation.
Read the full summary ↓
STAT3 was critical in modulating the balance of T helper 17 (Th17) and regulatory T (Treg) cells, as well as in promoting CD4+ T cell proliferation. We used chromatin immunoprecipitation and massive parallel sequencing (ChIP-Seq) to define the genome-wide targets of STAT3 in CD4+ T cells. We found that STAT3 bound to multiple genes involved in Th17 cell differentiation, cell activation, proliferation and survival, regulating both expression and epigenetic modifications. Thus, STAT3 orchestrates multiple critical aspects of T cell function in inflammation and homeostasis. This SuperSeries is composed of the SubSeries listed below.
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 GSE21671_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA125911 and SRA study SRP002451. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 19 more — browse all 19 samples with per-sample file links →

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