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Deciphering the role of histone modifications in memory and exhausted CD8 T cells [CUT&Run]

GSE285245 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 86 samples Submitted 2025/05/20 Platform GPL21626
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 86 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
86 samples: 23 conditions, mostly with about 4 replicates eachGroups 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
Deciphering the role of histone modifications in memory and exhausted CD8 T cellsScientific reports · 2025
Summary (written by the submitters)
Exhausted CD8 T cells (TEX) arising during chronic infections and cancer have reduced functional capacity and limited fate flexibility that prevents optimal disease control and response to immunotherapies. Compared to memory (TMEM) cells, TEX have a unique open chromatin landscape underlying a distinct gene expression program. How TEX transcriptional and epigenetic landscapes are regulated through histone post-translational modifications (hPTMs) remains unclear.
Read the full summary ↓
Here, we profiled key activating (H3K27ac and H3K4me3) and repressive (H3K27me3 and H3K9me3) histone modifications in naive CD8 T cells (TN), TMEM and TEX. We identified H3K27ac-associated super-enhancers that distinguish TN, TMEM and TEX, along with key transcription factor networks predicted to regulate these different transcriptional landscapes. Promoters of some key genes were poised in TN, but activated in TMEM or TEX whereas other genes poised in TN were repressed in TMEM or TEX, indicating that both repression and activation of poised genes may enforce these distinct cell states. Moreover, narrow peaks of repressive H3K9me3 were associated with increased gene expression in TEX, suggesting an atypical role for this modification. These data indicate that beyond chromatin accessibility, hPTMs differentially regulate specific gene expression programs of TEX compared to TMEM through both activating and repressive pathways.
Published in
Deciphering the role of histone modifications in memory and exhausted CD8 T cells
Huang H, Baxter AE, Zhang Z et al. · Scientific reports 2025 · PMID 40389726 · doi:10.1038/s41598-025-99804-0
This dataset
Open GSE285245 in finder → Find more mouse ChIP / ATAC / CUT&Tag 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 GSE285245_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 PRJNA1202103 and SRA study SRP553381. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40389726) ↗
Study design
23 conditions, mostly with about 4 replicates each
TN_Naive, H3K27ac, Day30, ×4 TN_Naive, H3K27ac, Day32, ×4 TMEM_Memory, H3K27ac, Day30, ×4 TEX_Exhaustion, H3K27ac, Day32, ×4 TN_Naive, H3K4me3, Day30, ×4 TN_Naive, H3K4me3, Day32, ×4 TMEM_Memory, H3K4me3, Day30, ×4 TEX_Exhaustion, H3K4me3, Day32, ×4 +15 more

Supports a between-group comparison across 86 samples.

How we read this: 23 replicated groups read from 86 sample titles; they account for 86 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

+ 46 more — browse all 86 samples with per-sample file links →

Datasets on a similar topic

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