← BioTransfer GEO Dataset Finder
GEO series

Organism-wide cellular dynamics and epigenomic remodeling in mammalian aging

GSE288730 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 21 samples Submitted 2025/05/15 Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 21 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
21 samples: 21 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
Organism-wide cellular dynamics and epigenomic remodeling in mammalian agingbioRxiv : the preprint server for biology · 2025
Summary (written by the submitters)
Aging leads to functional decline across tissues, often accompanied by profound changes in cellular composition and cell-intrinsic molecular states. However, a comprehensive catalog of how the population of individual cell types change with age and the associated epigenomic dynamics is lacking. Here, we constructed a single-cell chromatin accessibility atlas consisting of ~7 million cells from 21 tissue types spanning three age groups in both sexes.
Read the full summary ↓
This dataset revealed 536 main cell types and 1,828 finer‐grained subtypes, defined by unique chromatin accessibility landscapes at ~1.3 million cis‐regulatory elements. We observed widespread remodeling of immune lineages, with increases in plasma cells and macrophages, and depletion of T and B cell progenitors. Additionally, non-immune cell populations, including kidney podocytes, ovary granulosa cells, muscle tenocytes and lung aerocytes, showed marked reductions with age. Meanwhile, many subtypes changed synchronously across multiple organs, underscoring the potential influence of systemic inflammatory signals or hormonal cues. At the molecular level, aging was marked by thousands of differentially accessible regions, with the most concordant changes shared across cell types linked to genes related to inflammation or development. Putative upstream factors, such as intrinsic shifts in transcription factor usages and extrinsic cytokine signatures, were identified. Notably, around 40% of aging‐associated main cell types and subtypes showed sex‐dependent differences, with tens of thousands of chromatin accessibility peaks altered exclusively in one sex. Together, these findings present a comprehensive framework of how aging reshapes the chromatin landscape and cellular composition across diverse tissues, offering a comprehensive resource for understanding the molecular and cellular programs underlying aging and supporting the exploration of targeted therapeutic strategies to address age-related dysfunction.
Published in
Organism-wide cellular dynamics and epigenomic remodeling in mammalian aging
Lu Z, Zhang Z, Xu Z et al. · bioRxiv : the preprint server for biology 2025 · PMID 40463164 · doi:10.1101/2025.05.12.653376
This dataset
Open GSE288730 in finder → Find more mouse ChIP / ATAC / CUT&Tag 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 GSE288730_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1212703 and SRA study SRP558326. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40463164) ↗
Study design
21 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 21 sample titles: 21 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
Datasets on a similar topic

Search all mouse ChIP / ATAC / CUT&Tag 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.