MiTo: tracing the phenotypic evolution of somatic cell lineages via mitochondrial single-cell multi-omics.

Mitochondrial single-cell lineage tracing has recently emerged as a scalable and non-invasive tool to trace somatic cell lineages. However, the reliability and resolution of this technology remains highly debated. Here, we present MiTo, a novel end-to-end framework for robust mitochondrial single-cell lineage tracing data analysis. Benchmarked against real-world datasets, MiTo outperforms state-of-the-art methods and baselines in data pre-processing and clonal inference. Applied to a time-resolved dataset of breast cancer evolution (>2,500 cells), MiTo accurately infers ground-truth cell lineages (ARI = 0.94) and cell state transitions, detects clonal fitness markers, and quantifies heritability of gene regulatory networks. Comparing alternative lineage markers, MiTo quantifies the resolution limit of existing mitochondrial single-cell lineage tracing systems, which currently enable reliable inference of coarse-grained cellular ancestries, but not high-resolution phylogenetic inference. In conclusion, this work provides robust tools and practical guidelines to dissect somatic evolution with single-cell multi-omics.