Single-cell multi-omic analysis of mitochondrial mutational mosaicism and dynamics

Area of Science:

• Genetics
• Cell Biology
• Genomics

Background:

• Mitochondrial DNA (mtDNA) mutations are frequent and linked to diseases.
• Single-cell sequencing allows heteroplasmy analysis but lacks a holistic view of cellular mtDNA mutational landscapes.

Purpose of the Study:

• To develop novel metrics for analyzing single-cell mtDNA mutational landscapes.
• To investigate cellular mutational loads and somatic mosaicism in mitochondrial DNA.

Main Methods:

• Utilized mitochondrial single-cell ATAC-seq.
• Employed mtDNA-hypermutated POLG^D274A knock-in HEK293 cell lines.
• Introduced single-cell mtDNA mutations per million base pairs (scmtMPM) and heteroplasmy-weighted mitochondrial local constraint scores (scwMSS).

Main Results:

• Demonstrated complex mtDNA mutational landscapes in individual POLG^D274A cells.
• Observed pathogenic and truncating variants at subthreshold levels, suggesting negative selection.
• Identified constrained mutations in complex I in human samples, revealing single-cell mtDNA heterogeneity.

Conclusions:

• scmtMPM and scwMSS offer a framework for studying mitochondrial genetics.
• The findings highlight previously unrecognized heterogeneity in mtDNA mutational landscapes at the single-cell level.
• Provides new tools to investigate mitochondrial disease and somatic mosaicism.