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Cell composition and gene-expression dynamics of skeletal muscle regeneration after contraction-induced injury

GSE306977 Homo sapiens (human) RNA-seq (gene expression) 70 samples Submitted 2025/12/02 Platform GPL24676Platform GPL24247
At a glance

RNA-seq (gene expression) · human · 70 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
70 samples: 70 samples, each with a distinct title — no replicated groupsGroups 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
Common and distinct roles of AMPKγ isoforms in small-molecule activator-stimulated glucose uptake in mouse skeletal muscleMolecular metabolism · 2026
Summary (written by the submitters)
Small-molecule activators targeting the allosteric drug and metabolite (ADaM) site of AMPK enhance insulin-independent glucose uptake in skeletal muscle and promote blood glucose lowering in preclinical models of hyperglycemia. The regulatory AMPKγ subunit plays a central role in energy sensing, and the skeletal muscle-selective γ3 isoform is essential for AMP/ZMP-induced glucose uptake, but not for ADaM site activators. We hypothesized that the predominant γ1 isoform is required for ADaM site activator-stimulated glucose uptake in skeletal muscle.
Published in
Common and distinct roles of AMPKγ isoforms in small-molecule activator-stimulated glucose uptake in mouse skeletal muscle
Biswas D, Espino-Gonzalez E, Ahwazi D et al. · Molecular metabolism 2026 · PMID 41325841 · doi:10.1016/j.molmet.2025.102294
This dataset
Open GSE306977 in finder → Find more 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 GSE306977_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 PRJNA1314071 and SRA study SRP616680. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41325841) ↗
Study design
70 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 70 sample titles: 70 distinct titles with little repetition. 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

+ 30 more — browse all 70 samples with per-sample file links →

Datasets on a similar topic

Search all RNA-seq datasets in GEO →

Share this dataset

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.