← BioTransfer GEO Dataset Finder
GEO series

Inflammation-induced epigenetic erosion drives stem cell ferroptosis during aging

GSE228013 Mus musculus (mouse) RNA-seq (gene expression) 14 samples Submitted 2025/04/16 Platform GPL21626
At a glance

RNA-seq (gene expression) · mouse · 14 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
14 samples: 3 × KO_2wks vs 3 × KO_2years vs 3 × KO_6wks vs 3 × WT_2wksGroups 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
Epigenetic erosion of H4K20me1 induced by inflammation drives aged stem cell ferroptosisNature aging · 2025
Summary (written by the submitters)
Aging is a complex process associated with multiple events that lead to the decline in stem cell number and function. However, the relationship between these events and their initiation in biological systems remains ambiguous. Here, we investigate the effects of sustained, low-grade systemic inflammation on muscle stem cells (MuSCs) during aging.
Read the full summary ↓
We show that the slow rise in inflammation during aging causes long-lasting epigenetic remodeling in MuSCs, leading to premature exit of quiescence followed by rapid ferroptotic cell death. The elevation of circulating cytokines results in erosion of histone H4 lysine 20 methylation, fine-tuning of the MuSC transcriptome for future injury response that resembles the Galert state. Prolonged exposure to inflammatory signals during aging results in the loss of H4K20me1 maintenance by lysine methyltransferase 5a (Kmt5a), leading to a disruption of key transcriptional programs required to preserve MuSC quiescence and survival. Mechanistically, we established that Kmt5a genetic deletion prematurely activates MuSC through Notch signaling. Activated cells cannot cycle properly as they display aberrant iron metabolism and repressed Gpx4, resulting in the accumulation of reactive oxygen species, genomic instability, lipid peroxidation, and ultimately, cell death by ferroptosis. Notably, a lifelong reduction in inflammation restores the MuSC number and function and rejuvenates MuSC iron homeostasis. Our findings demonstrates that chronic systemic inflammatory signals reprogram the MuSC epigenome into a primed state, which drives premature cell cycle re-entry and ferroptosis during aging.
Published in
Epigenetic erosion of H4K20me1 induced by inflammation drives aged stem cell ferroptosis
Blanc RS, Shah N, Hachmer S et al. · Nature aging 2025 · PMID 40588650 · doi:10.1038/s43587-025-00902-5
This dataset
Open GSE228013 in finder → Find more mouse 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 GSE228013_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 PRJNA947664 and SRA study SRP428836. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40588650) ↗
Study design
3 × KO_2wks vs 3 × KO_2years vs 3 × KO_6wks vs 3 × WT_2wks

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 14 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
Datasets on a similar topic

Search all mouse 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.