Single-cell variant landscape of the human mitochondrial genome reveals cell type-specific and disease-associated changes

Mitochondria generate over 90% of the cellular energy and are central to health and disease. Mitochondrial DNA (mtDNA) heteroplasmy represents a significant source of cellular genetic diversity and has been shown to cause impaired mitochondrial function and even mitochondrial diseases. However, mitochondrial genetic heterogeneity across different human cell types at the population level is poorly understood. Here we present scMOCHA, a scalable computational framework that resolves high-confidence, single-cell resolution mtDNA heteroplasmy directly from standard single-cell RNA sequencing (scRNA-seq) data. Applying scMOCHA to all publicly available human peripheral blood mononuclear cells (PBMC) and bone marrow (BM) scRNA-seq datasets comprising 5.5 million cells, we uncover the single-cell landscape of mtDNA single-nucleotide variants (SNVs) and heteroplasmy levels in the human hematopoietic system across ages and cell types, including previously unreported SNVs and recurrent somatic hotspot SNVs in unrelated individuals. PBMCs and BM share many inherited homoplasmic and highly heteroplasmic SNVs but few somatic SNVs. Somatic SNVs are tissue- and cell type-specific and distributed across the mtDNA genome, suggesting that they arise in a largely random fashion. Although mtDNA replication error is the most likely dominant force shaping homoplasmic variants, oxidative stress may drive a significant portion of heteroplasmic and somatic mutations in the mtDNA genome. Importantly, we discover cell type-specific and human disease-associated mtDNA SNVs. By coupling mtDNA genotypes with matched single-cell nuclear transcriptomes and structural modeling, we uncover potential molecular mechanisms of how these disease-associated mtDNA SNVs impact cellular function such as inflammation and contribute to disease. Together, these findings define the single-cell variant landscape of the human mitochondrial genome and reveal previously unrecognized lineage- and disease-associated patterns of mtDNA variation in the human hematopoietic system.