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Integrated Sensing of Viral RNA and RNase L-Driven Intron Retention Orchestrates Anti-Poxvirus Immunity

GSE308598 Homo sapiens (human) RNA-seq (gene expression) 28 samples Submitted 2026/07/20 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 28 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
Homo sapiens (human)
Samples
28 samples: 14 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.
Summary (written by the submitters)
The recognition of double-stranded RNA (dsRNA) is a critical component of antiviral innate immune responses, yet how distinct sensors integrate their activities to enforce restriction remains unclear. Here, we uncover a cooperative mechanism linking the OAS3-RNase L and PKR pathways during vaccinia virus (VacV) infection. Transcriptome-wide analyses reveal that RNase L activation disrupts pre-mRNA splicing, inducing widespread intron retention.
Read the full summary ↓
These retained introns form dsRNA structures that evade nuclear quality control, accumulate in the cytoplasm, and serve as ligands for PKR. Thus, RNase L reshapes the transcriptome to enhance the generation of immunostimulatory substrates, amplifying PKR activation. In parallel, we identify conserved viral RNAs derived from the VacV telomeres, whose terminal loop architectures directly modulate PKR activity, with distinct species either promoting or dampening its activation. Together, our findings establish that PKR signaling emerges from the integrated detection of host-derived introns and conserved viral terminal structures, revealing innate immune cooperativity at the interface of RNA processing, viral replication, and gene regulation.
This dataset
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.

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 GSE308598_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1331676 and SRA study SRP622329. Searching any of these in the dataset finder brings you back here.

Study design
14 conditions, mostly in duplicate
Uninfected Input ×2 24hpi VacV Input ×2 24hpi VacV_dE3L Input ×2 6hpi VacV Input ×2 6hpi VacV_dE3L Input ×2 Uninfected J2IP ×2 24hpi VacV J2IP ×2 24hpi VacV_dE3L J2IP ×2 +6 more

Supports a between-group comparison across 28 samples.

How we read this: 14 replicated groups read from 28 sample titles; they account for 28 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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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.