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Somatic mutations in mitochondrial DNA (mtDNA) provide natural barcodes that enable engineering-free lineage tracing in human tissues, but the complex dynamics of mtDNA inheritance across cell divisions and incomplete sampling of mtDNA introduce uncertainty in reconstructed lineages. Here, we present MitoDrift, a probabilistic framework that integrates Wright-Fisher drift dynamics with sparse single-cell measurements to produce confidence-refined lineage trees enriched for accurate clonal relationships. Validation with gold-standard lentiviral barcoding and whole-genome sequencing demonstrates that MitoDrift outperforms existing tree reconstruction methods in precision while maintaining high clonal recovery, enabling robust analyses linking lineage to cell state. Applying MitoDrift to human hematopoiesis reveals an age-associated decline in clonal diversity with differential impact across cell types and identifies heritable regulatory programs in hematopoietic stem cells , linking AP-1/stress-associated programs to clonal expansions. In multiple myeloma, MitoDrift captures therapy-associated clonal remodeling undetectable by copy number analysis, revealing phenotypic transitions and linking gene regulatory programs to differential drug sensitivity. Collectively, MitoDrift enables high-precision lineage tracing at scale and establishes quantitative lineage-state analysis in primary human tissues, linking clonal history to transcriptional and epigenetic programs in tissue homeostasis, aging, and disease.