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Effect of depletion of PERK on gene expression in T cells after polyclonal or allogeneic stimulation

GSE307389 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2025/09/16 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 12 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
12 samples: 3 × T cells, PERK-KO, Ploy stimulation vs 3 × T cells, WT, Ploy stimulation vs 3 × T cells, PERK-KO, Allo stimulation vs 3 × T cells, WT, Allo stimulationGroups 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
ER stress sensor PERK promotes T cell pathogenicity in GVHD by regulating ER-associated degradationThe Journal of clinical investigation · 2025
Summary (written by the submitters)
PERK differentially regulates T cell allogeneic and anti-tumor responses. To further elucidate the mechanism, we performed transcriptomics analyses via bulk RNA sequencing on WT and PERK-deficient T cells after polyclonal or allogeneic stimulation. We here report that endoplasmic reticulum-associated degradation (ERAD)-associated genes, including Sel1l and Erlec1, were significantly increased in PERK conditional knock out (cKO) compared with WT T cells upon allogeneic but not polyclonal stimulation.
Read the full summary ↓
SEL1L-HRD1 axis plays a central role in ERAD pathway, we also observed that PERK binds to SEL1L in activated human T-cell line. By using PERK-/-SEL1L-/- mice, we eluciated that PERK regulates T-cell allogeneic responses and GVHD induction through SEL1L-mediated ERAD pathway.
Published in
ER stress sensor PERK promotes T cell pathogenicity in GVHD by regulating ER-associated degradation
Cheng Q, Choi HJ, Wu Y et al. · The Journal of clinical investigation 2025 · PMID 41026526 · doi:10.1172/JCI190958
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 GSE307389_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 PRJNA1320635 and SRA study SRP617744. Searching any of these in the dataset finder brings you back here.

Study design
3 × T cells, PERK-KO, Ploy stimulation vs 3 × T cells, WT, Ploy stimulation vs 3 × T cells, PERK-KO, Allo stimulation vs 3 × T cells, WT, Allo stimulation

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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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