Lineage tracing is a powerful tool to study development, tissue homeostasis, aging, and disease progression. Over the past decades, lineage tracing techniques have progressed substantially by employing new genetic engineering tools. However, due to their invasive nature, these approaches are difficult to apply to humans. Although endogenous DNA mutations can be used for in vivo lineage tracing in humans, their extremely low mutation rate presents substantial technical challenges. Mitochondrial DNA mutations are an alternative, but their inheritance may suffer from neutral drift or undergo both positive and negative selection, and their analysis is plagued by excessive data noise. Thus, developing non-invasive, high-resolution lineage tracing methods for human tissues is crucial.

Recently, a team from Westlake University led by Dr. Shou-Wen Wang published an article "DNA methylation meets lineage tracing: History, recent progress, and future directions" in Quantitative Biology. The article presents a comprehensive overview of DNA methylation-based lineage tracing, focusing on two recently developed approaches, MethylTree and EPI-Clone. MethylTree is the first generic lineage-tracing tool based on single-cell DNA methylation epimutations, achieving near 100% accuracy across diverse biological systems. EPI-Clone is a complementary targeted approach that enables scalable and cost-effective identification of expanded clones in blood. The authors compare these two approaches and highlight that MethylTree provides a unified computational framework for both genome-wide and targeted DNA methylation data.

Figure 1 illustrates the comparison between MethylTree and EPI-Clone. Panel A shows the workflow of MethylTree, which utilizes sparse single-cell whole-genome methylation sequencing data, with optional phenotypic labels from fluorescence-activated cell sorting or single-cell RNA sequencing. MethylTree computes cell-cell similarity, corrects noise, and removes cell-type signals to infer lineage trees. Panel B depicts the EPI-Clone workflow, which includes CpG panel selection, targeted scTAM-seq, and identification of static and dynamic CpGs to cluster expanded clones. Panels C-E demonstrate that MethylTree can also be applied to EPI-Clone's targeted data, providing a unified solution for epimutation-based lineage tracing. Panel G compares the two experimental strategies, highlighting that the genome-wide approach offers higher accuracy and richer information, while the targeted approach is more scalable and cost-effective.
DOI: 10.1002/qub2.70017