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ZFP36-family RNA-binding proteins in regulatory T cells reinforce immune homeostasis [single cell RNA-seq]

GSE240517 Mus musculus (mouse) Single-cell RNA-seq 3 samples Submitted 2024/08/08 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 3 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Mus musculus (mouse)
Samples
3 samples
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
ZFP36-family RNA-binding proteins in regulatory T cells reinforce immune homeostasisNature communications · 2025
Summary (written by the submitters)
RNA binding proteins (RBP) of the ZFP36 family limit the differentiation and effector functions of CD4 and CD8 T cells, but little is known of their expression or function in regulatory T cells (Treg). By Treg-restricted deletion of Zfp36 family members we identify the essential role of Zfp36l1 and Zfp36l2 in Treg to maintain immune homeostasis.
Read the full summary ↓
Mice with Tregs deficient in these RBP display an inflammatory phenotype with an expansion in the numbers of type-2 conventional dendritic cells, T effector cells, T follicular helper and germinal center B cells and elevated serum cytokines and immunoglobulins. In the absence of Zfp36l1 and Zfp36l2, the pool of cycling CTLA-4 in naïve Treg was reduced, Tregs were less sensitive to IL-2 and IL-7 but were more sensitive to IFNγ. In mice lacking both RBP in Treg, the deletion of a single allele of Ifng is sufficient to ameliorate the pathology. Thus, ZFP36L1 and ZFP36L2 regulate multiple pathways that enable Tregs to enforce immune homeostasis.
Published in
ZFP36-family RNA-binding proteins in regulatory T cells reinforce immune homeostasis
Sáenz-Narciso B, Bell SE, Matheson LS et al. · Nature communications 2025 · PMID 40328742 · doi:10.1038/s41467-025-58993-y
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 GSE240517_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: 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 PRJNA1004105 and SRA study SRP454406. Searching any of these in the dataset finder brings you back here.

Samples in this study

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