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The TCR-SUB1-DOCK2 Signaling Axis Governs Autoimmunity by Regulating CD4+ T Cell Migratory Capacity

GSE309052 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 14 samples Submitted 2026/02/01 Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 14 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
14 samples: 14 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)
Aberrant activated T cell infiltration is a key driver of autoimmune pathogenesis, highlighting the therapeutic potential of inhibiting T cell migration. However, the regulatory mechanisms governing tissue ingress of antigen-specific T cells remain elusive. Here, we report that SUB1, a transcription factor upregulated in CD4+ T cells from patients with autoimmune disorders, is regulated by the TCR–IRF4 axis.
Read the full summary ↓
SUB1 deficiency diminished DOCK2 expression by 50%, impairing Rac-dependent actin polymerization and T cell migration, and consequently suppressed the onset of experimental autoimmune encephalomyelitis (EAE). Mechanistically, SUB1 promotes chromatin accessibility at the Junb and Dock2 loci via liquid–liquid phase separation (LLPS), facilitating biomolecular condensate formation. Furthermore, SUB1 directly activates Junb transcription and cooperates with JUNB to enhance Dock2 expression. Our results identify SUB1 as a critical regulator of antigen-specific CD4+ T cell migration and propose it as a promising therapeutic target for autoimmune diseases.
This dataset
Open GSE309052 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 GSE309052_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 PRJNA1333869 and SRA study SRP626390. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
14 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 14 sample titles: 14 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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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.