GEO series

Immune-responsive gene-1: The mitochondrial Key to Th17 Cell Pathogenicity in CNS Autoimmunity

GSE298306 Mus musculus (mouse) Single-cell RNA-seq 18 samples Submitted 2025/05/28 Platform GPL34290Platform GPL24247

At a glance

Single-cell RNA-seq · mouse · 18 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: 18 samples: 6 conditions, mostly with about 4 replicates eachGroups 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: Immune-responsive gene 1: The mitochondrial key to Th17 cell pathogenicity in CNS autoimmunityProceedings of the National Academy of Sciences of the United States of America · 2025

Summary (written by the submitters)

Pathogenic Th17 cells play crucial roles in CNS autoimmune diseases such as multiple sclerosis (MS), but their regulation by endogenous mechanisms remains unknown. Through RNA-seq analysis of primary brain glial cells, we identified immuno-responsive gene 1 (Irg1) as one of the highly upregulated gene under inflammatory conditions. Validation in the spinal cord of animals with experimental autoimmune encephalomyelitis (EAE), an MS model, confirmed elevated Irg1 levels in myeloid, CD4, and B cells in the EAE group raising the concern if Irg1 is detrimental or protective.

Read the full summary ↓

Irg1 knockout (KO) mice exhibited severe EAE disease, increased mononuclear cell infiltration, and increased levels of triple-positive CD4+ T cells expressing IL17a, GM-CSF, and IFNγ. A lack of Irg1 in macrophages elevates Class II expression, promoting the polarization of myelin-primed CD4+ T cells into pathogenic Th17 cells via the NLRP3/IL-1β axis. Adoptive transfer in Rag-1 KO and single-cell RNA sequencing highlighted the crucial role of Irg1 in shaping pathogenic Th17 cells. Moreover, bone marrow chimeras revealed that immune cells lacking Irg1 maintained pathogenic and inflammatory phenotypes, suggesting its protective role in autoimmune diseases, including MS.

Published in

Immune-responsive gene 1: The mitochondrial key to Th17 cell pathogenicity in CNS autoimmunity

Nematullah M, Fatma M, Zhou G et al. · Proceedings of the National Academy of Sciences of the United States of America 2025 · PMID 40758870 · doi:10.1073/pnas.2427052122

This dataset

Open GSE298306 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 GSE298306_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 PRJNA1268916 and SRA study SRP588204. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40758870) ↗

Study design

6 conditions, mostly with about 4 replicates each

CD45.1_WT ×4 CD45.2_Irg1KO ×4 Un ×3 LI_8h ×3 Irg1 KO EAE ×2 WT EAE ×2

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 of them. 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

GSM9011854 CD45.1_WT1 CD45.1_WT
GSM9011855 CD45.1_WT2 CD45.1_WT
GSM9011856 CD45.1_WT3 CD45.1_WT
GSM9011857 CD45.1_WT4 CD45.1_WT
GSM9011858 CD45.2_Irg1KO1 CD45.2_Irg1KO
GSM9011859 CD45.2_Irg1KO2 CD45.2_Irg1KO
GSM9011860 CD45.2_Irg1KO3 CD45.2_Irg1KO
GSM9011861 CD45.2_Irg1KO4 CD45.2_Irg1KO
GSM9014638 Irg1 KO EAE Replicate 1 Irg1 KO EAE
GSM9014639 Irg1 KO EAE Replicate 2 Irg1 KO EAE
GSM9014640 WT EAE Replicate 1 WT EAE
GSM9014641 WT EAE Replicate 2 WT EAE
GSM9014642 Un_1 Un
GSM9014643 Un_2 Un
GSM9014644 Un_3 Un
GSM9014645 LI_8h_1 LI_8h
GSM9014646 LI_8h_2 LI_8h
GSM9014647 LI_8h_3 LI_8h

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