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Identification of a transcription factor network that regulates anti-TNF mediated IL-10 expression in human CD4+ T-cells

GSE216688 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 16 samples Submitted 2024/09/25 Platform GPL16791Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 16 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
Homo sapiens (human)
Samples
16 samples: 16 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
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.
Paper
Identification of a transcription factor network regulating anti-TNF mediated IL10 expression in human CD4+ T cellsDiscovery immunology · 2024
Summary (written by the submitters)
CD4+ T-cells are key players in the pathogenesis of rheumatoid arthritis (RA) through potent production of inflammatory mediators including IL-17A, IFNg and TNF. Anti-TNF therapy has revolutionized the treatment of RA and we previously demonstrated that in vitro treatment of human CD4+ T-cells with the anti-TNF monoclonal antibody adalimumab (ADA) promotes anti-inflammatory IL-10 expression in multiple subpopulations of CD4+ T-cells.
Read the full summary ↓
Here we investigated the transcriptional mechanisms underlying the IL-10 induction by TNF-blockade in in vitro stimulated CD4+ T-cells. CD4+ T-cells were isolated from PBMC of healthy volunteers by magnetic isolation and cultured for 3 days with anti-CD3/CD28 mAb in the absence or presence of anti-TNF. After culture, CD45RA+ cells were depleted and RNA was extracted for gene expression profiling by RNA-seq and cell nuclei were isolated for chromatin accessibility analysis by ATAC-seq. Gene expression analysis of memory CD4+ T-cells showed a distinct gene signature of 183 genes (q-value <0.05) conferred by anti-TNF treatment. Pathway enrichment analysis of the differentially expressed genes revealed multiple pathways related to cytokine signalling and regulation of cytokine production; in particular, IL10 was the most upregulated gene by anti-TNF, while the proinflammatory cytokines and chemokines IFNG, IL9, IL22 and CXCL10 were significantly downregulated (q-value <0.05). Transcription factor (TF) motif analysis at the differentially open chromatin regions after anti-TNF treatment revealed 58 TF motifs, shared by all donors, enriched at the IL10 locus. We identified 7 TF candidates for the anti-TNF mediated regulation of IL-10, which were either differentially expressed or whose locus was differentially accessible upon anti-TNF stimulation. We postulate that this TF network, which includes MAF and PRMD1, drives transcriptional regulation of IL-10 in anti-TNF treated T-cells.
Published in
Identification of a transcription factor network regulating anti-TNF mediated IL10 expression in human CD4+ T cells
Povoleri GAM, Ridley ML, Marrow RJ et al. · Discovery immunology 2024 · PMID 39290825 · doi:10.1093/discim/kyae013
This dataset
Open GSE216688 in finder → Find more human RNA-seq datasets →
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.

Series matrix ↓
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 GSE216688_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
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.

Raw reads on ENA ↗

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 PRJNA894970 and SRA study SRP404855. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39290825) ↗
Study design
16 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 16 sample titles: 16 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
Datasets on a similar topic

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