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A pathogenic CD4 T cell phenotype in experimental uveitis shares common features with other immune mediated inflammatory diseases [EAU]

GSE289821 Mus musculus (mouse) Single-cell RNA-seq 24 samples Submitted 2025/06/16 Platform GPL19057
At a glance

Single-cell RNA-seq · mouse · 24 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
24 samples: 24 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
A pathogenic CD4 T cell phenotype in experimental uveitis shares common features with other immune mediated inflammatory diseasesDiscovery immunology · 2026
Summary (written by the submitters)
Experimental autoimmune uveoretinitis, a mouse model of ocular autoimmunity, was induced by the transfer of allelically marked T cells. Thirteen days after transfer, CD4 cells were sorted from spleens and individual eyes and processed using the SMART-Seq v4 Ultra Low Input RNA kit. Samples were classified as: transferred cells from the eye, transferred cells from the spleen, endogenous cells from the eye, endogenous cells from the spleen. Analysis of differential gene expression revealed an extended pathogenic phenotype that shared common features with other models of autoimmunity.
Published in
A pathogenic CD4 T cell phenotype in experimental uveitis shares common features with other immune mediated inflammatory diseases
Ward A, Bell OH, Martinez-Robles L et al. · Discovery immunology 2026 · PMID 42211685 · doi:10.1093/discim/kyaf019
This dataset
Open GSE289821 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 GSE289821_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 PRJNA1225132 and SRA study SRP564537. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42211685) ↗
Study design
24 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 24 sample titles: 24 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 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.