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Gudera, J.

Publications and source records attributed to Gudera, J..

2 recordsLinked to original sources

Low-heteroplasmy mitochondrial DNA mutations improve clonal reconstruction of human cells

Reconstructing clonal relationships among human cells is fundamental to understanding development, aging, and disease. Somatic mitochondrial DNA (mtDNA) mutations act as endogenous single-cell barcodes measurable alongside cell-state profiles, but lineage tracing has traditionally focused on high-heteroplasmy variants, which are easier to detect but few and potentially shaped by selection. Whether the more abundant lower-heteroplasmy variants encode bona fide lineage information has not been tested against an independent clonal reference. Using lentiviral barcoding of human hematopoietic cells to establish ground-truth clone identities, we show that after stringent molecule-level error filtering, mutation calls below 10% per-cell heteroplasmy account for roughly half of all lineage-informative calls. Retaining the full heteroplasmy spectrum approximately doubled the clonal-assignment area under the precision-recall curve relative to a >10% cutoff, and single-molecule-supported calls improved recovery when retained collectively. These findings establish lower-heteroplasmy mtDNA mutations as an abundant, bona fide record of clonal history, substantially expanding the clonal resolution attainable in human tissues without genetic engineering.

genomics↗

Modeling mitochondrial inheritance enables high-precision single-cell lineage tracing in humans

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 in vivo, 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.

genomics↗