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Genetic diversity of Collaborative Cross mice reveals FFAR3 as a target for ILC2 anti-inflammatory reprogramming

GSE288176 Mus musculus (mouse) RNA-seq (gene expression) 26 samples Submitted 2025/11/14 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 26 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
26 samples: 12 conditions, mostly in duplicateGroups 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
Genetic diversity of Collaborative Cross mice implicates FFAR3 as a target for ILC2 anti-inflammatory reprogrammingNature communications · 2026
Summary (written by the submitters)
Pulmonary group 2 innate lymphoid cells (ILC2s) are key drivers of Type 2 inflammation in diseases like asthma, yet the molecular mechanisms regulating their function are incompletely understood. Using the genetically diverse Collaborative Cross (CC) mouse panel, we mapped a quantitative trait locus (QTL) that governs ILC2 prevalence in the lung after aeroallergen exposure.
Read the full summary ↓
This QTL creates a large population of ILC2s in the lung that are resistant to activation and have diminished Type 2 effector function. We identified free-fatty acid receptor 3 (FFAR3) as a gene responsible for this effect and demonstrated that FFAR3 signaling reprograms ILC2s to an anti-inflammatory state by promoting their survival, reducing Type 2 cytokine production, and enhancing IL-10 expression. This reprogramming is mediated by epidermal growth factor receptor (EGFR) upregulation. We showed that FFAR3's anti-inflammatory effect is conserved in human ILC2s, making it a potential therapeutic target for Type 2 inflammation.
Published in
Genetic diversity of Collaborative Cross mice implicates FFAR3 as a target for ILC2 anti-inflammatory reprogramming
Rusznak M, Toki S, Hao Y et al. · Nature communications 2026 · PMID 41484153 · doi:10.1038/s41467-025-67813-2
This dataset
Open GSE288176 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 GSE288176_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 PRJNA1216526 and SRA study SRP560327. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41484153) ↗
Study design
12 conditions, mostly in duplicate
C57BL6J ILC2 ×3 CC030GeniUnc ×3 CC030 ILC2 Vehicle Mouse 1 Day ×2 CC030 ILC2 Vehicle Mouse 2 Day ×2 CC030 ILC2 Vehicle Mouse 3 Day ×2 CC030 ILC2 Vehicle Mouse 4 Day ×2 CC030 ILC2 Vehicle Mouse 5 Day ×2 CC030 ILC2 AR420626 Mouse 1 Day ×2 +4 more

Supports a between-group comparison across 26 samples.

How we read this: 12 replicated groups read from 26 sample titles; they account for 26 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
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