← BioTransfer GEO Dataset Finder
GEO series

TOX sustains the longevity and multipotency of CD4 Tprog cells during chronic LCMV infection

GSE314874 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 16 samples Submitted 2026/08/05 Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 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
Mus musculus (mouse)
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.
Summary (written by the submitters)
Progenitor CD4 T cells (Tprog) develop during chronic viral infection and cancer and retain developmental plasticity to replenish Tfh and Th1 populations over time. Although considerable attention has been given to progenitor CD8 T cells, the distinct biological roles and multiple fates of CD4 T cells raise questions about the molecular circuitry controlling CD4 Tprog in settings of chronic stimulation.
Read the full summary ↓
Here, we interrogated the impact of the HMG-box transcription factor (TF) TOX on the developmental flexibility of virus-specific CD4 T cells and the role of this TF in coordinating the transcriptional and epigenetic program of CD4 Tprog during chronic infection. These studies revealed key elements of CD4 Tprog biology that are central to sustaining T cell responses to persistent infection. First, TOX was dispensable for CD4 Tprog development but required for maintenance and function of these cells over time. Second, TOX promoted CD4 Tprog maintenance and survival by regulating expression of BIM and BCL-2. Third, loss of TOX in CD4 Tprog resulted in transcriptional and epigenetic dysregulation, highlighted by loss of TCF-1 pathway activity and gain of NFAT, NFkB, and RUNX-coordinated transcriptional circuitry. Finally, functional interrogation revealed a key role for TOX in the multipotent potential of CD4 Tprog to differentiate into Th1-like or Tfh-like cells during chronic viral infection. These data reveal a TOX-driven molecular network that sustains the core function of CD4 Tprog, highlighting a role for this TF not just in terminal exhaustion, but also in stem-like CD4 T cells that support development of downstream CD4 T cell subsets during persisting antigen stimulation.
This dataset
Open GSE314874 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 GSE314874_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 PRJNA1393039. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
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

Search all mouse ChIP / ATAC / CUT&Tag datasets in GEO →

Share this dataset

Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.