EpiTrace: A Chromatin Clock to Map Cell Mitotic Age from scATAC‑seq

Atlas Research SpotlightsAging
Written By Atlasxomics Team

Introduction 

 A transformative study by Xiao et al. in Nature Biotechnology (May 2025) introduces EpiTrace, the first method to infer the mitotic age—a measure of how many times a cell has divided—directly from single-cell ATAC-seq data. By learning from clock-like regions of chromatin accessibility, EpiTrace allows researchers to reconstruct lineage trajectories and developmental timing—without relying on somatic mutations, cell barcoding, or RNA velocity models.

Fig. 1. a) Schematic of mitotic-age tracing via chromatin accessibility (ChrAcc) at ClockDML sites.
b) DNAm on G8-group ClockDML inversely correlates with PBMC age (R = −0.98, P < 2.2 × 10⁻¹⁶; 95 % CI shaded).
c) Enrichment odds ratios for mitosis-ClockDML, chronology-ClockDML and solo-WCGW loci across ATAC-seq peak sets from pan-cancer, bladder, normal, placenta and hematopoietic samples (Fisher’s exact test; whiskers = 95 % CI).
d) Outline of the EpiTrace algorithm.
e) UMAP of single-cell ATAC from early human embryos, colored by stage.
f) ClockDML accessibility (raw and HMM-smoothed) and iterative EpiTrace age ranks across stages (sample counts in legend). Pearson correlations shown; P values < 2.2 × 10⁻¹⁶ reported. “tropho.” = trophoblast.

Key findings from the spatial ATAC-seq analysis 

  • Clock‑like Chromatin Accessibility (ClockDML): Researchers identified ~126,000 genomic regions whose accessibility decreases with successive cell divisions. These “ClockDML” loci, derived from methylation aging clocks, serve as stable markers of mitotic age in the chromatin landscape.

  • EpiTrace Algorithm: EpiTrace generates a ClockAcc score for each cell by smoothing chromatin accessibility across the ClockDML loci, using graph-based refinement to predict relative mitotic age across a cell population.

  • Cross-System Validation: EpiTrace accurately reconstructed developmental trajectories across diverse systems—human fetal organs, mouse organoids, and even cross-species datasets (zebrafish, fly, mouse)—showing strong correlation with known timepoints (R = 0.8–0.97).

  • Phylogenetic Lineage Inference: Cells with similar ClockAcc profiles were more likely to share developmental origin, enabling unsupervised lineage tree construction that outperformed traditional pseudotime or mutational phylogenies.

Implications for Epigenomics, Development, and Spatial Biology:

 EpiTrace adds a powerful new dimension to the single-cell epigenomics toolkit—time. By turning chromatin accessibility into a mitotic “clock,” this method opens up exciting possibilities:

  • Aging, Reconstructed in Place: Researchers can now estimate the mitotic age of cells in their native tissue context—revealing which regions harbor older, more proliferative, or quiescent cell populations and how cellular aging unfolds across space and disease states.

  • Lineage Tracing Without Barcodes: Unlike traditional methods that require CRISPR barcoding or RNA-based assumptions, EpiTrace enables lineage reconstruction directly from chromatin, using endogenous, unmodified features. This makes it ideal for retrospective studies and human tissues.

  • Cross-Species and Cross-Platform Utility: EpiTrace is compatible with standard ATAC-seq data and leverages conserved regulatory regions, making it broadly applicable across model organisms and systems.

  • Unlocking Spatial Lineages: Critically, EpiTrace can be applied to spatial ATAC-seq data. This unlocks the ability to create mitotic age maps within intact tissues—combining lineage history with spatial structure to explore tumor evolution, tissue regeneration, or brain development in context.

  • New Avenues for Cancer, Regeneration, and Aging: In tumors, EpiTrace could highlight early clonal expansions or therapy-resistant subpopulations. In regenerative biology, it could help identify stem versus transit-amplifying cells. And in aging research, it offers a direct view of how cell turnover shapes tissue longevity.

Conclusion:

 By converting chromatin accessibility into a mitotic time axis, EpiTrace enables a new form of lineage and aging analysis—one that is quantitative, endogenous, and spatially compatible. This work from Xiao et al. positions chromatin as both a regulatory and temporal record of cell history, opening the door to new insights in development, disease, and beyond.

Further reading 

Atlasxomics Team
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