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

Area of Science:

• Genomics
• Cell Biology
• Bioinformatics

Background:

• Somatic mitochondrial DNA (mtDNA) mutations serve as natural barcodes for lineage tracing.
• Challenges include mtDNA inheritance dynamics and sparse sampling, complicating lineage reconstruction.

Purpose of the Study:

• To develop MitoDrift, a probabilistic framework for high-precision, engineering-free lineage tracing.
• To refine lineage trees and enhance accuracy of clonal relationships in human tissues.

Main Methods:

• Integrated Wright-Fisher drift dynamics with sparse single-cell mtDNA measurements.
• Validated MitoDrift using lentiviral barcoding and whole-genome sequencing.
• Applied the framework to human hematopoiesis and multiple myeloma models.

Main Results:

• MitoDrift demonstrated superior precision and clonal recovery compared to existing methods.
• Identified age-associated decline in hematopoietic clonal diversity and linked AP-1/stress programs to clonal expansions.
• Captured therapy-associated clonal remodeling in multiple myeloma, revealing phenotypic transitions and drug sensitivity links.

Conclusions:

• MitoDrift enables scalable, high-precision lineage tracing in primary human tissues.
• Establishes quantitative lineage-state analysis, linking clonal history to cellular programs in homeostasis, aging, and disease.