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Control of naive T cell reactivity and peripheral tolerance by ascorbate and TET activity [RNAseq in vitro stimulation] 

GSE224402 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2026/05/08 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 18 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
18 samples: 18 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
Control of naive T cell reactivity and peripheral tolerance by ascorbate and TET activityScience advances · 2026
Summary (written by the submitters)
Maintenance of T cell naïve (Tn) state and restricting effector T cell differentiation upon basal level stimulations would be critical for immune homeostasis and prevention of autoimmunity. To understand how Tn state is regulated by nutrient cues in a cell-intrinsic manner, here we perform an in vivo CRISPR screening to identify required solute carrier (SLC) proteins that transport metabolites and ions into T cells.
Read the full summary ↓
Among SLC proteins revealed by this experiment, vitamin C transporter Slc23a2 appears to play a role. Conditional ablation of Slc23a2 in T cells by genetic approaches reduces intracellular vitamin C levels by approximately 80%, accompanied by spontaneous activation and differentiation of Tn cells, autoantibody production, and autoimmune pathology in select organs. Slc23a2-deficient Tn cells exhibit profound DNA hypermethylation, dysregulation of genes controlling signaling transduction and transcription, and enhanced differentiation of helper T cells upon stimulation. These results define a broad regulatory space of vitamin C as a cofactor of Tet enzymes in controlling active DNA demethylation. In agreement, conditional deletion of Tet genes impairs Tn state and increases helper T cell differentiation. Thus, our study reveals a cell-intrinsic mechanism by which micronutrient vitamin C via Slc23a2 maintains Tn state and self-tolerance by promoting Tet-mediated DNA demethylation.
Published in
Control of naive T cell reactivity and peripheral tolerance by ascorbate and TET activity
Hao X, Bai L, Li J et al. · Science advances 2026 · PMID 42308298 · doi:10.1126/sciadv.aeh1439
This dataset
Open GSE224402 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 GSE224402_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 PRJNA930778. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42308298) ↗
Study design
18 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 18 sample titles: 18 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.