GEO series

Modular neuroinflammatory network discovery from large-scale phenotypic screening in genetically heterogeneous mice [part10]

GSE294832 Mus musculus Expression profiling by high throughput sequencing 1000 samples Submitted 2026/04/11 Platform GPL24247

Summary

The central nervous system represents a uniquely immune-privileged environment, with inflammatory responses involving several resident CNS-specific cell types. While stereotyped cellular and transcriptional responses recur across varied diseases, relevant signaling pathways and regulatory networks are not fully understood. Here, we describe a screening platform based on high-throughput RNA-seq analysis and glial cell state gene set scores that enables multimodal investigation of inflammatory networks at scale. As proof-of-concept, we investigate genetically heterogeneous mice from a large-scale chemical mutagenesis screen to identify novel functionally relevant variants in six genes previously linked to human CNS disorders: Nrros, Ctsd, Smpd1, Idua, Nlrp1a, and Inpp5d . We leverage the rich and readily-interpretable data from our study to demarcate distinct inflammatory states arising from each mutation. In all, our work provides a methodology for discovering novel regulators of CNS neuroimmune homeostasis and provides a validated analysis framework for identifying discrete neuroinflammatory modules that are engaged divergently across disease contexts.

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Direct links to NCBI, no account and no request form: the whole study as GSE294832_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 1000 samples. Raw sequencing reads are also available from ENA.

Whole study · RAW.tar ↓ Series matrix ↓ All supplementary files ↗ Raw reads on ENA ↗

Also filed as BioProject PRJNA1251662 and SRA study SRP579134. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

40 conditions, each sampled once — no replicated groups

Read from the first 40 of 1000 sample titles: 40 distinct titles with little repetition. Check it against the sample list below before relying on it.

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