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Chemically-induced protein degradation reveals inflammation-dependent requirement for Treg lineage-defining transcription factor FOXP3

GSE289371 Mus musculus (mouse) RNA-seq (gene expression) 58 samples Submitted 2025/06/26 Platform GPL34328
At a glance

RNA-seq (gene expression) · mouse · 58 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Mus musculus (mouse)
Samples
58 samples: 58 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.
Paper
Inducible protein degradation reveals inflammation-dependent function of the T(reg) cell lineage-defining transcription factor Foxp3Science immunology · 2025
Summary (written by the submitters)
Regulatory T (Treg) cells are immunosuppressive CD4 T cells defined by expression of the transcription factor FOXP3. Genetic loss-of-function mutations in Foxp3 cause lethal multi-organ autoimmune inflammation resulting from defects in Treg cell development and suppressive activity. Whether FOXP3 is continuously required to maintain existing Treg cells is still unclear, however.
Read the full summary ↓
Here, we leveraged chemically-induced protein degradation to show that functionally suppressive Treg cells in healthy organs can persist in the near-complete absence of FOXP3 protein for at least 10 days. Conversely, Treg cells responding to type 1 inflammation in settings of autoimmunity, viral infection, or cancer were selectively lost upon FOXP3 protein depletion. Acute degradation experiments revealed that FOXP3 acts as a direct transcriptional repressor to modulate responsiveness to cytokine stimulation. This inflammation-dependent requirement for FOXP3 enabled induction of a selective anti-tumor immune response upon systemic FOXP3 depletion, without causing deleterious T cell expansion in healthy organs.
Published in
Inducible protein degradation reveals inflammation-dependent function of the T(reg) cell lineage-defining transcription factor Foxp3
Jäger C, Dimitrova P, Sun Q et al. · Science immunology 2025 · PMID 40478934 · doi:10.1126/sciimmunol.adr7057
This dataset
Open GSE289371 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 GSE289371_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1222798 and SRA study SRP563416. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40478934) ↗
Study design
58 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 58 sample titles: 58 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

+ 18 more — browse all 58 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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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.