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Sprint interval exercise drives a unique transcriptional mitochondrial stress response in humans

GSE302582 Homo sapiens (human) RNA-seq (gene expression) 72 samples Submitted 2025/11/06 Platform GPL23227
At a glance

RNA-seq (gene expression) · human · 72 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
72 samples: 6 conditions, mostly with about 12 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.
Paper
Sprint interval exercise disrupts mitochondrial ultrastructure driving a unique mitochondrial stress response and remodelling in menNature communications · 2025
Summary (written by the submitters)
The molecular mechanisms by which different exercise prescriptions dictate mitochondrial remodelling are poorly understood in humans. Here, we show that, compared to moderate-intensity continuous exercise (MICE), sprint-interval exercise (SIE) – a known time-efficient high-intensity exercise – leads to mitochondrial stress and transcriptionally activates the mitochondrial unfolded protein response (UPRmt).
Published in
Sprint interval exercise disrupts mitochondrial ultrastructure driving a unique mitochondrial stress response and remodelling in men
Botella J, Perri E, Caruana NJ et al. · Nature communications 2025 · PMID 41326383 · doi:10.1038/s41467-025-66625-8
This dataset
Open GSE302582 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 GSE302582_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 PRJNA1021961 and SRA study SRP465627. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41326383) ↗
Study design
6 conditions, mostly with about 12 replicates each
Muscle, baseline, MICE group, Participant # ×12 Muscle, +2.5h, MICE group, Participant # ×12 Muscle, +24h, MICE group, Participant # ×12 Muscle, baseline, SIE group, Participant # ×12 Muscle, +2.5h, SIE group, Participant # ×12 Muscle, +24h, SIE group, Participant # ×12

Supports a between-group comparison across 72 samples.

How we read this: 6 replicated groups read from 72 sample titles; they account for 72 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

+ 32 more — browse all 72 samples with per-sample file links →

Datasets on a similar topic

Search all human 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.