GEO series

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

GSE331489 Mus musculus Genome binding/occupancy profiling by high throughput sequencing 725 samples Submitted 2026/05/31 Platform GPL32159Platform GPL24247

Summary

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. 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

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Direct links to NCBI, no account and no request form: the whole study as GSE331489_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 725 samples. Raw sequencing reads are also available from ENA.

Whole study · RAW.tar ↓ Series matrix ↓ All supplementary files ↗ Raw reads 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

21 × mouse kidney EdU,EXP123_Kidney_EdU vs 12 × mouse kidney EdU,EXP122_Kidney_EdU vs 7 × mouse kidney EdU,EXP152_Kidney_EdU

Supports a between-group comparison across 40 samples.

3 replicated groups read from the first 40 of 725 sample titles; they account for 40 of them. Check it against the sample list below before relying on it.

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