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Tregs stimulate intestinal repair by integrating epithelial IFNy/IL-10 signaling

GSE252335 Mus musculus (mouse) Single-cell RNA-seq 12 samples Submitted 2025/10/02 Platform GPL30172
At a glance

Single-cell RNA-seq · mouse · 12 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
12 samples: 6 conditions, mostly in duplicateGroups 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
Tissue-adapted Tregs harness inflammatory signals to promote intestinal repair from therapy-related injurySignal transduction and targeted therapy · 2025
Summary (written by the submitters)
To understand the transcriptional changes on cellular level within the murine intestinal epithelial tissue, we generated small intestinal organoids from wild type mice, co-cultured them with Treg cells +/- rIL10/rIFNg or anti-IFNg/IL10R, dissagregated the samples, sorted into single cells and profiled them by single-cell RNA-seq
Published in
Tissue-adapted Tregs harness inflammatory signals to promote intestinal repair from therapy-related injury
Fischer JC, Göttert S, Giller M et al. · Signal transduction and targeted therapy 2025 · PMID 41290566 · doi:10.1038/s41392-025-02476-5
This dataset
Open GSE252335 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 GSE252335_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1060238 and SRA study SRP480906. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41290566) ↗
Study design
6 conditions, mostly in duplicate
Mixed sample, replicate I, GEX, B ×2 Mixed sample, replicate II, GEX, B ×2 Mixed sample, replicate III, GEX, B ×2 Mixed sample, replicate I, HTO, B ×2 Mixed sample, replicate II, HTO, B ×2 Mixed sample, replicate III, HTO, B ×2

Supports a between-group comparison across 12 samples.

How we read this: 6 replicated groups read from 12 sample titles; they account for 12 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
Datasets on a similar topic

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