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Loss of cellular RNA homeostasis contributes to MDA5 activation during virus infection

GSE338264 Homo sapiens (human) Single-nucleus RNA-seq 22 samples Submitted 2026/07/13 Platform GPL30173
At a glance

Single-nucleus RNA-seq · human · 22 samples

What it is
Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue). Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
22 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.
Summary (written by the submitters)
MDA5 is an innate immune RNA sensor that senses infection with a range of viruses and other pathogens. MDA5’s RNA agonists are not well defined. We used single-nucleotide resolution crosslinking and immunoprecipitation (iCLIP) to study its ligands. Surprisingly, upon infection with SARS-CoV-2 or encephalomyocarditis virus, MDA5 bound overwhelmingly to cellular RNAs.
Read the full summary ↓
Many binding sites were intronic and proximal to Alu elements and to potentially base-paired structures. Concomitantly, cytoplasmic levels of aberrant transcripts and intron-containing unspliced transcripts increased in infected cells and displayed enrichment of MDA5 iCLIP peaks. Moreover, overexpression of the splicing factor SRSF3 reduced aberrant transcription and abrogated MDA5 activation. Taken together, we propose that MDA5 surveys RNA processing fidelity and can detect infections by sensing perturbations of posttranscriptional events such as splicing.
This dataset
Open GSE338264 in finder → Find more human 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 GSE338264_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 PRJNA1493081 and SRA study SRP717000. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly with about 4 replicates each
LIM1215-GFP, EMCV infected ×4 LIM1215-GFP, uninfected ×4 LIM1215-SRSF3, EMCV infected ×4 LIM1215-SRSF3, uninfected ×4 LIM1215-GFP, IFN treated ×3 LIM1215-SRSF3 IFN treated ×3

Supports a between-group comparison across 22 samples.

How we read this: 6 replicated groups read from 22 sample titles; they account for 22 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
Datasets on a similar topic

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