GEO series

Notch3 Directs a Regulatory T Cells-Microglia axis to Promote Autoimmune Neuroinflammation

GSE253097 Mus musculus (mouse) RNA-seq (gene expression) 24 samples Submitted 2025/07/02 Platform GPL21493

At a glance

RNA-seq (gene expression) · mouse · 24 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: 24 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.

Summary (written by the submitters)

Deciphering the mechanisms that promote central nervous system inflammation in multiple sclerosis is critical for developing precision therapies. We show that a specific regulatory T (Treg) cell subpopulation expressing Notch3 was increased in the peripheral blood and cerebrospinal fluid of individuals with multiple sclerosis (MS) and in the central nervous system (CNS) of mice with experimental autoimmune encephalomyelitis (EAE).

Read the full summary ↓

Notch3 expression was upregulated by mechanisms involving the gut microbiota and Treg cell-specific toll-like receptor (TLR) signaling to promote EAE severity. Notch3 interaction with delta-like ligand 1 (DLL1) on microglia subverted Treg cells into T helper 17 (Th17) cells by Hippo pathway-dependent mechanisms while also inducing an inflammatory microglial response. Its deletion inhibited EAE by preventing Treg cell destabilization into Th17 cells while simultaneously promoting the expansion of a novel brain-protective neuropeptide receptor 1 (NPY1R)+ Treg cell population that suppressed pathogenic IFN+ and GM-CSF+ effector T cells. Our studies thus identify Notch3-mediated immune tolerance subversion as a fundamental mechanism that licenses autoimmune neuroinflammation.

This dataset

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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 GSE253097_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 PRJNA1064033 and SRA study SRP483443. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Samples in this study

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+ 24 more — browse all 24 samples with per-sample file links →

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