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<p>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 (&gt;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.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月25日

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  • Andrea Cossa,
  • Alberto Dalmasso,
  • Guido Campani,
  • Elisa Bugani,
  • Chiara Caprioli,
  • Noemi Bulla,
  • Andrea Tirelli,
  • Yinxiu Zhan,
  • Pier Giuseppe Pelicci

摘要

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.