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Dietary Glutamine Supplementation Mitigates Age-Associated Cardiac Decline by Restricting H3K27me3

GSE317412 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 14 samples Submitted 2026/02/06 Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 14 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Mus musculus (mouse)
Samples
14 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.
Summary (written by the submitters)
Epigenetic alterations are central drivers of cardiovascular aging, with histone modifications regulating gene expression through chromatin remodeling and changes in DNA accessibility. However, the mechanisms underlying these epigenetic shifts in the aging heart remain poorly defined. Here, we identify an age-associated accumulation of the repressive histone mark H3K27me3 in the myocardium of mice and humans, implicating this modification in myocardial aging.
Read the full summary ↓
Elevated H3K27me3 was associated with impaired glutamine metabolism, driven by reduced expression of the amino acid transporter SLC1A5. Clinically, low circulating glutamine levels correlated with increased heart failure incidence, and genetic variants in SLC1A5 were linked to heightened cardiovascular disease risk. Mechanistically, elevated myocardial H3K27me3 suppressed cardiomyocyte autophagy and induced metabolic reprogramming, thereby promoting age-related myocardial dysfunction. Dietary glutamine supplementation in aged mice reduced H3K27me3 accumulation and improved myocardial function. Collectively, these findings identify a novel epigenetic mechanism underlying cardiac aging and highlight the glutamine–SLC1A5 axis as a potential therapeutic target for preserving myocardial function with age.
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 GSE317412_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 peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1412552 and SRA study SRP665852. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 14 more — browse all 14 samples with per-sample file links →

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