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Lactate as a metabolic-epigenetic signal linking high-intensity interval training (HIIT) to miRNA-Centered remodeling of the skeletal muscle methylome and transcriptome

GSE308674 Mus musculus (mouse) DNA methylation 28 samples Submitted 2025/12/03 Platform GPL34290
At a glance

DNA methylation · mouse · 28 samples

What it is
DNA methylationChemical marks on DNA that help switch genes on or off.
Organism
Mus musculus (mouse)
Samples
28 samples
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
Lactate as a metabolic-epigenetic signal linking high-intensity interval training (HIIT) to miRNA-Centered remodeling of the skeletal muscle methylome and transcriptomeRedox biology · 2025
Summary (written by the submitters)
Lactate, a major exercise-derived metabolite, has been proposed to couple cellular metabolism to gene regulation, yet its direct impact on skeletal muscle remains unclear. Male mice underwent six-week interventions (Control, lactate, HIIT, MCT1/2 inhibition, or HIIT+inhibition). We profiled gastrocnemius DNA methylation, mRNA-seq and miRNA-seq, and assessed signaling proteins, metabolites, and running performance.
Read the full summary ↓
Lactate and HIIT each induced broad, site-specific remodeling of the methylome and transcriptome with substantial overlap at promoter CpGs and among DEGs. Promoter methylation changes showed weak coupling to steady-state mRNA, whereas integrative analyses revealed robust anti-directional miRNA–mRNA networks and enriched for chromatin/epigenetic regulators, identifying a lactate-driven miRNA axis as a proximate regulator of transcriptional output. At the protein level, lactate selectively increased TET2 and DNMT3A and activated PAX7, VEGF, and AKT–S6 signaling, consistent with integrative miRNA–mRNA findings. HIIT increased TET1/2 and DNMT3A with DNMT3B reduction and uniquely enhanced mitochondrial/antioxidant signaling. Blocking MCT1/2 abrogated HIIT-induced methylome and miRNA remodeling and blunted transcriptomic and protein adaptation, demonstrating that intact lactate flux is required for exercise-evoked epigenetic and transcriptomic reprogramming. Despite molecular convergence, chronic lactate did not improve running performance, indicating that lactate is necessary but not sufficient for the full physiological adaptation of training. These findings position a lactate–miRNA axis linking metabolic perturbation to epigenetic and transcriptional remodeling in skeletal muscle.
Published in
Lactate as a metabolic-epigenetic signal linking high-intensity interval training (HIIT) to miRNA-Centered remodeling of the skeletal muscle methylome and transcriptome
Zhou L, Mozaffaritabar S, Tanisawa K et al. · Redox biology 2025 · PMID 41314005 · doi:10.1016/j.redox.2025.103943
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 GSE308674_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: Look for beta-value tables or raw IDAT files among the supplementary files.

Also filed as BioProject PRJNA1332440 and SRA study SRP624138. Searching any of these in the dataset finder brings you back here.

Samples in this study

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

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