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HDAC1 controls the generation and maintenance of effector-like CD8+ T cells during chronic viral infection

GSE255887 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 76 samples Submitted 2025/05/22 Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 76 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
76 samples: 20 conditions, mostly in triplicateGroups 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
HDAC1 controls the generation and maintenance of effector-like CD8+ T cells during chronic viral infectionThe Journal of experimental medicine · 2025
Summary (written by the submitters)
CD8+ T cell exhaustion is a complex process involving the differentiation of persistently acti-vated CD8+ T cells into functionally distinct cell subsets. Here, we investigated the role of the key epigenetic regulator histone deacetylase 1 (HDAC1) in the differentiation of exhausted T (Tex) cells during chronic viral infection. We uncovered that HDAC1 controls the generation and maintenance of effector-like CX3CR1+ Tex cells in a CD8+ T cell-intrinsic manner.
Read the full summary ↓
Dele-tion of HDAC1 led to expansion of an alternative Tex subset characterized by high expression of T cell exhaustion markers, and this was accompanied by elevated viremia. HDAC1 bound to and facilitated an open chromatin state of effector-like signature gene loci in progenitor Tex cells, thereby priming cell fate specification toward the CX3CR1+ Tex subset. Our study un-covers a selective role for HDAC1 in CX3CR1+ Tex subset differentiation, which is essential for controlling viral load during chronic infection.
Published in
HDAC1 controls the generation and maintenance of effector-like CD8+ T cells during chronic viral infection
Rica R, Waldherr M, Miyakoda E et al. · The Journal of experimental medicine 2025 · PMID 40464916 · doi:10.1084/jem.20240829
This dataset
Open GSE255887 in finder → Find more mouse 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 GSE255887_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 PRJNA1076916 and SRA study SRP490082. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40464916) ↗
Study design
20 conditions, mostly in triplicate
mouse, WT, early-TexProg, HDAC1, biol ×3 mouse, WT, early-TexProg, H3K27ac, biol ×3 mouse, WT, early-TexProg, Runx3, biol ×3 mouse, WT, early-TexProg, H3K27me3, biol ×3 mouse, WT, early-TexProg, IgG, biol ×3 mouse, HDAC1-cKO, early-TexProg, HDAC1, biol ×3 mouse, HDAC1-cKO, early-TexProg, H3K27ac, biol ×3 mouse, HDAC1-cKO, early-TexProg, Runx3, biol ×3 +28 more

Supports a between-group comparison across 60 samples.

How we read this: 20 replicated groups read from 76 sample titles; they account for 60 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

+ 36 more — browse all 76 samples with per-sample file links →

Datasets on a similar topic

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