Single-cell variant landscape of the human mitochondrial genome reveals cell type-specific functions and disease mechanisms
- 1Children's Hospital of Philadelphia and University of Pennsylvania
Abstract
Mitochondrial DNA (mtDNA) heteroplasmy is a significant source of cellular genetic diversity and can cause disease yet its distribution and functional importance across different human cell types are poorly understood. Here we present scMOCHA (Single-Cell Mitochondrial Omics for Cellular Heteroplasmy Analysis), a scalable computational framework that resolves highconfidence, single-cell resolution mtDNA heteroplasmy directly from standard single-cell RNA sequencing (scRNA-seq) data. Using this tool to interrogate publicly available scRNA-seq datasets from human peripheral blood mononuclear cells (PBMC) and bone marrow (BM) uncovered the single-cell landscape of mtDNA single-nucleotide variants (SNVs) and heteroplasmy across ages in human hematopoietic cell types. PBMCs and BM share many inherited homoplasmic and highly heteroplasmic SNVs, whereas somatic SNVs are tissue- and cell type-specific and distributed across the mtDNA genome, suggesting that they arise largely stochastically. mtDNA replication error is a dominant force shaping homoplasmic variants, while oxidative stress potentially drives a significant portion of heteroplasmic and somatic mutations. Importantly, we discover previously unknown 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 by which disease-associated mtDNA SNVs impact cellular processes 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.
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BibTeX
@misc{liu2026singlecell,
title = {{Single-cell variant landscape of the human mitochondrial genome reveals cell type-specific functions and disease mechanisms}},
author = {C. Liu and T. Peng and Z. Cen and P. Lu and P. Potluri and P. Hu and S. Zhang and M. T. Lott and G. Widjaja and D. C. Wallace and Y. Xing and L. Pei},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.11.758340},
url = {https://www.biorxiv.org/content/10.64898/2026.10.11.758340v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Single-cell variant landscape of the human mitochondrial genome reveals cell type-specific functions and disease mechanisms
AU - C. Liu
AU - T. Peng
AU - Z. Cen
AU - P. Lu
AU - P. Potluri
AU - P. Hu
AU - S. Zhang
AU - M. T. Lott
AU - G. Widjaja
AU - D. C. Wallace
AU - Y. Xing
AU - L. Pei
PY - 2026
DA - 2026/10/11
PB - bioRxiv
DO - 10.64898/2026.10.11.758340
UR - https://www.biorxiv.org/content/10.64898/2026.10.11.758340v1
AB - Mitochondrial DNA (mtDNA) heteroplasmy is a significant source of cellular genetic diversity and can cause disease yet its distribution and functional importance across different human cell types are poorly understood. Here we present scMOCHA (Single-Cell Mitochondrial Omics for Cellular Heteroplasmy Analysis), a scalable computational framework that resolves highconfidence, single-cell resolution mtDNA heteroplasmy directly from standard single-cell RNA sequencing (scRNA-seq) data. Using this tool to interrogate publicly available scRNA-seq datasets from human peripheral blood mononuclear cells (PBMC) and bone marrow (BM) uncovered the single-cell landscape of mtDNA single-nucleotide variants (SNVs) and heteroplasmy across ages in human hematopoietic cell types. PBMCs and BM share many inherited homoplasmic and highly heteroplasmic SNVs, whereas somatic SNVs are tissue- and cell type-specific and distributed across the mtDNA genome, suggesting that they arise largely stochastically. mtDNA replication error is a dominant force shaping homoplasmic variants, while oxidative stress potentially drives a significant portion of heteroplasmic and somatic mutations. Importantly, we discover previously unknown 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 by which disease-associated mtDNA SNVs impact cellular processes 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.
ER -