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cGAS-mediated IFN-I signaling contributes to disease progression in drug-refractory epilepsy

GSE334405 Mus musculus (mouse) RNA-seq (gene expression) 44 samples Submitted 2026/06/04 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 44 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
44 samples: 5 conditions, mostly with about 8 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.
Summary (written by the submitters)
Epilepsy is a prevalent neurological disease with a third of patients becoming non-responsive to antiepileptic drugs and developing drug-refractory epilepsy (DRE). Here we report that DRE disease progression is contributed by overactive cyclic GMP-AMP synthase (cGAS), a double-stranded DNA sensor that induces type I interferon (IFN-I) signaling.
Read the full summary ↓
In human DRE microglia, we observe a robust IFN-I signature and the activation of upstream cGAS-STING signaling. Further, in mouse models of Dravet syndrome, a genetic form of DRE, we observe the activation of the cGAS pathway. We show that microglial cGAS can be activated by DNA released from hyperexcitable neurons. Genetic reduction and pharmacological inhibition of cGAS reduces epileptic phenotypes, glial inflammatory signatures, and neuronal transcriptomic changes, underscoring the therapeutic potential of targeting cGAS for DRE treatment.
This dataset
Open GSE334405 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 GSE334405_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 PRJNA1474968 and SRA study SRP706912. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
5 conditions, mostly with about 8 replicates each
LG815_C ×16 LG815_Ctrl ×8 LG815_TDI ×8 DVPV_CTX ×6 DVPV_Hipp ×6

Supports a between-group comparison across 44 samples.

How we read this: 5 replicated groups read from 44 sample titles; they account for 44 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

+ 4 more — browse all 44 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.