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A global view of cell-type-specific temporal dynamics in mammalian aging [I]

GSE331488 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 771 samples Submitted 2026/05/31 Platform GPL32159Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 771 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
771 samples: 11 conditions, mostly with about 52 replicates eachGroups 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)
A healthy adult human body regenerates around 330 billion cells per day, equivalent to about 1% of the total cell number in the entire organism. Cells from different types and tissues regenerate at various speeds, ranging from the fast-renewal of red blood cells, immune cells, and gut epithelial cells, to the rare genesis of adult neurons and glial cells in the brain.
Read the full summary ↓
With age, the regenerative properties of most tissues gradually decline due to a combination of age-dependent changes in tissue-specific stem cells and environmental cues. However, a consensus study of cell-type-specific turnover dynamics and how such cell-genesis processes change with aging is lacking. Recent advances in single-cell genomics have created unprecedented opportunities to explore the cell-type-specific molecular states across diverse mammalian systems. In particular, single-cell combinatorial indexing sequencing (sci-seq) has emerged as a powerful strategy to label the nucleic acid contents of individual cells in a scalable manner. However, current single-cell techniques only deliver a static snapshot of each isolated cell with temporal information lost, falling short of quantitatively capturing the dynamics such as proliferation and differentiation events. To address this gap, we previously introduced TrackerSci (PMID: 37774676), a single-cell genomic method that combines newborn cell labeling and combinatorial indexing to characterize the transcriptome and chromatin landscape of proliferating progenitor cells in vivo. In the present study, we applied TrackerSci to profile chromatin accessibility in over 3 million newborn cells across 21 mouse tissues, examining three different ages and both sexes. This dataset provides a comprehensive view of cell temporal dynamics throughout the body, enabling us to quantify cell-type-specific proliferation and differentiation changes during aging and uncover molecular programs associated with aging-related population shifts.
This dataset
Open GSE331488 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 GSE331488_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 PRJNA1215444 and SRA study SRP559751. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
11 conditions, mostly with about 52 replicates each
mouse spleen EdU,EXP125_Spleen_EdU ×96 mouse pancreas EdU,EXP131_Pancreas_EdU ×52 mouse mesenteric white adipose tissue EdU,EXP… ×52 mouse skin EdU,EXP140_Skin_EdU ×49 mouse ovary and uterus EdU,EXP135_OvaryUterus… ×48 mouse liver EdU,EXP118_Liver_EdU ×27 mouse skin EdU,EXP146_Skin_EdU ×20 mouse heart EdU,EXP127_Heart_EdU ×20 +3 more

Supports a between-group comparison across 400 samples.

How we read this: 11 replicated groups read from the first 400 of 771 sample titles; they account for 400 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

+ 731 more — browse all 771 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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