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m6A RNA modification cooperates with alternative polyadenylation to control T cell homeostasis via mTOR signaling

GSE202164 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2025/11/27 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 12 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
12 samples: 12 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
m(6)A RNA modification guides alternative polyadenylation to maintain T cell quiescenceScience advances · 2026
Summary (written by the submitters)
To identify all of the APA targets of NUDT21 or METTL3 and obtain gene expression profile, RNA from WT, Nudt21-deficient and Mettl3-deficient naïve CD4+ T cells stimulated with anti-CD3/CD28 for 0hr or 48hr were subject to RNA-Seq. By using a custom-designed algorithm and Gene ontology (GO) analysis, we found mRNA 3'UTR shortening phenomenon after TCR stimulation and both METTL3 and NUDT21 regulate 3'UTR length. In addition, we found most of up-regulated genes after Nudt21 deficiency are associated with immune activation pathway.
Published in
m(6)A RNA modification guides alternative polyadenylation to maintain T cell quiescence
Zhang X, Li H, Wang G et al. · Science advances 2026 · PMID 42127188 · doi:10.1126/sciadv.aea4983
This dataset
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.

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 GSE202164_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA834821 and SRA study SRP373471. Searching any of these in the dataset finder brings you back here.

Study design
12 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 12 sample titles: 12 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.