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The G3BP Stress-Granule Proteins Reinforce the Translation Program of the Integrated Stress Response

GSE256237 Homo sapiens (human) RNA-seq (gene expression) 68 samples Submitted 2025/12/08 Platform GPL24676Platform GPL11154
At a glance

RNA-seq (gene expression) · human · 68 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
68 samples: 22 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
The G3BP stress-granule proteins reinforce the integrated stress response translation programmeNature cell biology · 2026
Summary (written by the submitters)
When mammalian cells are exposed to extracellular stress, they coordinate the condensation of stress granules (SGs) through the action of key nucleating proteins G3BP1 and G3BP2 (G3BPs) and, simultaneously, undergo a massive reduction in translation. Although SGs and G3BPs have been linked to this translation response, their overall impact has been unclear.
Read the full summary ↓
Here, we investigate the longstanding question of how, and indeed whether, G3BPs and SGs shape the stress translation response. We find that SGs are enriched for mRNAs that are resistant to the stress-induced translation shutdown. Although the accurate recruitment of these stress-resistant mRNAs does require the context of stress, a combination of optogenetic tools and spike-normalized ribosome profiling demonstrates that G3BPs and SGs are necessary and sufficient to both help prioritize the translation of their enriched mRNAs and help suppress cytosolic translation. Together these results support a model in which G3BPs and SGs reinforce the stress translation program by prioritizing the translation of their resident mRNAs.
Published in
The G3BP stress-granule proteins reinforce the integrated stress response translation programme
Smith J, Bartel DP · Nature cell biology 2026 · PMID 41419572 · doi:10.1038/s41556-025-01834-3
This dataset
Open GSE256237 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 GSE256237_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 PRJNA1078759 and SRA study SRP490719. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41419572) ↗
Study design
22 conditions, mostly in duplicate
RNA_HCT_WT_Unstressed ×4 RNA_HCT_depleted_Unstressed ×4 RNA_HCT_WT_oxidative ×4 RNA_HCT_depleted_oxidative ×4 RPF_HCT_WT_Unstressed ×4 RPF_HCT_depleted_Unstressed ×4 RPF_HCT_WT_oxidative ×4 RPF_HCT_depleted_oxidative ×4 +22 more

Supports a between-group comparison across 60 samples.

How we read this: 22 replicated groups read from 68 sample titles; they account for 60 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

+ 28 more — browse all 68 samples with per-sample file links →

Datasets on a similar topic

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