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IL-10 Targets IRF1/5 to Suppress IFN and Inflammatory Responses by Epigenetic Mechanisms [Cut & Run]

GSE261245 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 28 samples Submitted 2025/04/11 Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 28 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
28 samples: 12 conditions, mostly in duplicateGroups 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
IL-10 targets IRF transcription factors to suppress IFN and inflammatory response genes by epigenetic mechanismsNature immunology · 2025
Summary (written by the submitters)
Interleukin-10 (IL-10) is pivotal in suppressing inflammation and innate immune activation, in large part by suppressing induction of genes by potent inflammatory factors such as TLR ligands. Despite decades of research, molecular mechanisms underlying this inhibition have not been resolved. This study utilized an integrated epigenomic analysis of gene transcription, chromatin accessibility, histone modifications and transcription factor binding to investigate IL-10-mediated suppression of LPS and TNF responses in primary human monocytes.
Read the full summary ↓
Instead of inhibiting core TLR4-activated pathways such as NF-kB, MAPK-AP-1 and TBK1-IRF3 signaling, IL-10 targeted IRF5 an IRF1-mediated amplification loop that is important for IFNB, ISG and inflammatory gene induction in monocytes. This resulted in near-complete suppression of ISGs, and significant inhibition of inflammatory NF-kB target genes, in whose activation IRFs play an amplifying role. Mechanisms of TLR4 and TNFR target gene inhibition included downregulation of chromatin accessibility, de novo enhancer formation, and IRF1-associated H3K27ac activating histone marks. These results describe an underappreciated suppression of IFN responses by IL-10 and provide epigenetic mechanisms by which IL-10 suppresses TLR/TNF-induced gene expression.
Published in
IL-10 targets IRF transcription factors to suppress IFN and inflammatory response genes by epigenetic mechanisms
Mishra B, Bachu M, Yuan R et al. · Nature immunology 2025 · PMID 40263613 · doi:10.1038/s41590-025-02137-3
This dataset
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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 GSE261245_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 PRJNA1086152 and SRA study SRP494343. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40263613) ↗
Study design
12 conditions, mostly in duplicate
CNR_IL10_IRF1 ×3 CNR_IL10_LPS_IRF1 ×3 CNR_LPS_IRF1 ×3 CNR_Rest_IRF1 ×3 CNR_IL10_H3k27ac ×2 CNR_IL10_LPS_H3k27ac ×2 CNR_LPS_H3k27ac ×2 CNR_Rest_H3k27ac ×2 +4 more

Supports a between-group comparison across 28 samples.

How we read this: 12 replicated groups read from 28 sample titles; they account for 28 of them. 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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