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Epigenetic profiling of mouse uteri across reproductive aging

GSE298816 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 59 samples Submitted 2025/08/11 Platform GPL19057
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 59 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
59 samples: 59 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.
Summary (written by the submitters)
Advanced maternal age increases the risk of pregnancy complications because of a higher incidence of karyotypic imbalances in the oocyte. A very important yet much less explored contribution to this risk, however, is the declining capacity of the uterus to adapt to the hormonal stimulus of pregnancy. As such, it has remained unknown what drives the uterine aging phenotype on the molecular and cellular level.
Read the full summary ↓
Here, we show in mice that maternal aging is associated with a progressive increase in transcriptional variation that is accompanied by a drastic accumulation of activating histone marks. Importantly, the transcriptional signatures associated with uterine aging differ substantially from those of organismal aging. Single-cell deconvolution analysis demonstrates that maternal age-induced effects originate in the epithelial compartment and specifically entail a dramatic up-regulation of the pioneer transcription factor FOXC1, linked to an accumulation of H3K4me3 and H3K27ac across the locus. FOXC1 over-expression in human endometrial cells causes profound transcriptomic shifts and increases proliferation rates, recapitulating the aging phenotype. Using endometrial epithelial organoids of young and aged mice, we find that aging hallmarks including Foxc1 up-regulation and H3K27ac hyper-enrichment are conserved in vitro. In line with the epithelial hyperplasia phenotype seen in vivo, endometrial epithelial organoids from aged mice are larger and mis-express key factors critical for uterine gland maturity and function, most notably SOX9. Collectively, our data highlight the specific susceptibility of uterine epithelial cells to early-onset aging, with early changes manifesting in an increase in activating epigenetic marks that coalesce on the mis-regulation of FOXC1.
This dataset
Open GSE298816 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 GSE298816_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 PRJNA1271427 and SRA study SRP589523. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
59 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 59 sample titles: 59 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

+ 19 more — browse all 59 samples with per-sample file links →

Datasets on a similar topic

Search all mouse ChIP / ATAC / CUT&Tag datasets in GEO →

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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.