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Mitochondrial DNA (mtDNA) is a maternally inherited, high-copy-number genome required for oxidative phosphorylation 1 . Heteroplasmy refers to the presence of a mixture of mtDNA alleles in an individual and has been associated with disease and ageing. Mechanisms underlying common variation in human heteroplasmy, and the influence of the nuclear genome on this variation, remain insufficiently explored. Here we quantify mtDNA copy number (mtCN) and heteroplasmy using blood-derived whole-genome sequences from 274,832 individuals and perform genome-wide association studies to identify associated nuclear loci. Following blood cell composition correction, we find that mtCN declines linearly with age and is associated with variants at 92 nuclear loci. We observe that nearly everyone harbours heteroplasmic mtDNA variants obeying two principles: (1) heteroplasmic single nucleotide variants tend to arise somatically and accumulate sharply after the age of 70 years, whereas (2) heteroplasmic indels are maternally inherited as mixtures with relative levels associated with 42 nuclear loci involved in mtDNA replication, maintenance and novel pathways. These loci may act by conferring a replicative advantage to certain mtDNA alleles. As an illustrative example, we identify a length variant carried by more than 50% of humans at position chrM:302 within a G-quadruplex previously proposed to mediate mtDNA transcription/replication switching 2 , 3 . We find that this variant exerts cis -acting genetic control over mtDNA abundance and is itself associated in- trans with nuclear loci encoding machinery for this regulatory switch. Our study suggests that common variation in the nuclear genome can shape variation in mtCN and heteroplasmy dynamics across the human population. We quantify mitochondrial DNA copy number and heteroplasmy levels and study their association with nuclear genetic loci in population-scale biobanks.

Cancer is a serious health problem with a high mortality rate worldwide. Given the relevance of mitochondria in numerous physiological and pathological mechanisms, such as adenosine triphosphate (ATP) synthesis, apoptosis, metabolism, cancer progression and drug resistance, mitochondrial genome (mtDNA) analysis has become of great interest in the study of human diseases, including cancer. To date, a high number of variants and mutations have been identified in different types of tumors, which coexist with normal alleles, a phenomenon named heteroplasmy. This mechanism is considered an intermediate state between the fixation or elimination of the acquired mutations. It is suggested that mutations, which confer adaptive advantages to tumor growth and invasion, are enriched in malignant cells. Notably, many recent studies have reported a heteroplasmy-shifting phenomenon as a potential shaper in tumor progression and treatment response, and we suggest that each cancer type also has a unique mitochondrial heteroplasmy-shifting profile. So far, a plethora of data evidencing correlations among heteroplasmy and cancer-related phenotypes are available, but still, not authentic demonstrations, and whether the heteroplasmy or the variation in mtDNA copy number (mtCNV) in cancer are cause or consequence remained unknown. Further studies are needed to support these findings and decipher their clinical implications and impact in the field of drug discovery aimed at treating human cancer.

Mitochondrial DNA (mtDNA) has an important yet often overlooked role in health and disease. Constraint models quantify the removal of deleterious variation from the population by selection and represent powerful tools for identifying genetic variation that underlies human phenotypes 1 , 2 , 3 – 4 . However, nuclear constraint models are not applicable to mtDNA, owing to its distinct features. Here we describe the development of a mitochondrial genome constraint model and its application to the Genome Aggregation Database (gnomAD), a large-scale population dataset that reports mtDNA variation across 56,434 human participants 5 . Specifically, we analyse constraint by comparing the observed variation in gnomAD to that expected under neutrality, which was calculated using a mtDNA mutational model and observed maximum heteroplasmy-level data. Our results highlight strong depletion of expected variation, which suggests that many deleterious mtDNA variants remain undetected. To aid their discovery, we compute constraint metrics for every mitochondrial protein, tRNA and rRNA gene, which revealed a range of intolerance to variation. We further characterize the most constrained regions within genes through regional constraint and identify the most constrained sites within the entire mitochondrial genome through local constraint, which showed enrichment of pathogenic variation. Constraint also clustered in three-dimensional structures, which provided insight into functionally important domains and their disease relevance. Notably, we identify constraint at often overlooked sites, including in rRNA and noncoding regions. Last, we demonstrate that these metrics can improve the discovery of deleterious variation that underlies rare and common phenotypes. Development of a constraint model specifically for mitochondrial DNA and applied to data from the Genome Aggregation Database provides insights into which sites in the mitochondrial genome are important for health and disease.

Somatic cells accumulate genomic alterations with age; however, our understanding of mitochondrial DNA (mtDNA) mosaicism remains limited. Here we investigated the genomes of 2,096 clones derived from three cell types across 31 donors, identifying 6,451 mtDNA variants with heteroplasmy levels of ≳0.3%. While the majority of these variants were unique to individual clones, suggesting stochastic acquisition with age, 409 variants (6%) were shared across multiple embryonic lineages, indicating their origin from heteroplasmy in fertilized eggs. The mutational spectrum exhibited replication-strand bias, implicating mtDNA replication as a major mutational process. We evaluated the mtDNA mutation rate (5.0 × 10 −8 per base pair) and a turnover frequency of 10–20 per year, which are fundamental components shaping the landscape of mtDNA mosaicism over a lifetime. The expansion of mtDNA-truncating mutations toward homoplasmy was substantially suppressed. Our findings provide comprehensive insights into the origins, dynamics and functional consequences of mtDNA mosaicism in human somatic cells. Analysis of 2,096 single-cell clones from three tissues of 31 healthy donors characterizes mitochondrial DNA mosaicism and highlights the following two origins of mtDNA variants: heteroplasmy in the fertilized egg and postzygotic mutations.

Heteroplasmy occurs when wild-type and mutant mitochondrial DNA (mtDNA) molecules co-exist in single cells 1 . Heteroplasmy levels change dynamically in development, disease and ageing 2 , 3 , but it is unclear whether these shifts are caused by selection or drift, and whether they occur at the level of cells or intracellularly. Here we investigate heteroplasmy dynamics in dividing cells by combining precise mtDNA base editing (DdCBE) 4 with a new method, SCI-LITE (single-cell combinatorial indexing leveraged to interrogate targeted expression), which tracks single-cell heteroplasmy with ultra-high throughput. We engineered cells to have synonymous or nonsynonymous complex I mtDNA mutations and found that cell populations in standard culture conditions purge nonsynonymous mtDNA variants, whereas synonymous variants are maintained. This suggests that selection dominates over simple drift in shaping population heteroplasmy. We simultaneously tracked single-cell mtDNA heteroplasmy and ancestry, and found that, although the population heteroplasmy shifts, the heteroplasmy of individual cell lineages remains stable, arguing that selection acts at the level of cell fitness in dividing cells. Using these insights, we show that we can force cells to accumulate high levels of truncating complex I mtDNA heteroplasmy by placing them in environments where loss of biochemical complex I activity has been reported to benefit cell fitness. We conclude that in dividing cells, a given nonsynonymous mtDNA heteroplasmy can be harmful, neutral or even beneficial to cell fitness, but that the ‘sign’ of the effect is wholly dependent on the environment. A new method for tracking single-cell heteroplasmy, called SCI-LITE, is combined with mitochondrial DNA base editing to reveal principles of heteroplasmy dynamics in dividing cells.

Background Mitochondrial dysfunction is a feature of neurodegenerative diseases, including Alzheimer’s disease (AD). Changes in the mitochondrial DNA copy number (mtDNAcn) and increased mitochondrial DNA mutation burden have both been associated with neurodegenerative diseases and cognitive decline. This study aims to systematically identify which common brain pathologies in the aged human brain are associated with mitochondrial recalibrations and to disentangle the relationship between these pathologies, mtDNAcn, mtDNA heteroplasmy, aging, neuronal loss, and cognitive function. Methods Whole-genome sequencing data from n  = 1361 human brain samples from 5 different regions were used to quantify mtDNAcn as well as heteroplasmic mtDNA point mutations and small indels. Brain samples were assessed for 10 common pathologies. Annual cognitive test results were used to assess cognitive function proximal to death. For a subset of samples, neuronal proportions were estimated from RNA-seq profiles, and mass spectrometry was used to quantify the mitochondrial protein content of the tissue. Results mtDNAcn was 7–14% lower in AD relative to control participants. When accounting for all 10 common neuropathologies, only tau was significantly associated with lower mtDNAcn in the dorsolateral prefrontal cortex. In the posterior cingulate cortex, TDP-43 pathology demonstrated a distinct association with mtDNAcn. No changes were observed in the cerebellum, which is affected late by pathologies. Neither age nor gender was associated with mtDNAcn in the studied brain regions when adjusting for pathologies. Mitochondrial content and mtDNAcn independently explained variance in cognitive function unaccounted by pathologies, implicating complex mitochondrial recalibrations in cognitive decline. In contrast, mtDNA heteroplasmy levels increased by 1.5% per year of life in the cortical regions, but displayed no association with any of the pathologies or cognitive function. Conclusions We studied mtDNA quantity and quality in relation to mixed pathologies of aging and showed that tau and not amyloid-β is primarily associated with reduced mtDNAcn. In the posterior cingulate cortex, the association of TDP-43 with low mtDNAcn points to a vulnerability of this region in limbic-predominant age-related TDP-43 encephalopathy. While we found low mtDNAcn in brain regions affected by pathologies, the absence of associations with mtDNA heteroplasmy burden indicates that mtDNA point mutations and small indels are unlikely to be involved in the pathogenesis of late-onset neurodegenerative diseases.

Pea has been hitherto considered to have strict maternal inheritance of mitochondria, as most of flowering plants. Using a CAPS marker we detected a case of paternal inheritance of mitochondrial DNA (mtDNA) in the second generation of a cross between a wild and a cultivated representatives of the common pea (Pisum sativum L.). Heteroplasmy for mitochondrial and plastid DNA was detected in arrays of high throughput sequence reads and confirmed by analysis of CAPS markers in an accession of Pisum fulvum Sm. and probable heteroplasmy for mtDNA marker was detected in an accession of the wild P. sativum subsp, elatius. A case of mtDNA recombination in one of accessions of the same subspecies from Turkey was observed as a ca 13 Kb long insert originating from a distant evolutionary lineage. Thus, three phenomena described in this work, occasional paternal leakage of mitochondria, naturally occurring heteroplasmy and recombination of diverged mitochondrial genomes in pea, elucidated microevolutionary processes which shaped diversity in this important crop.

Plasmids have a key role in bacterial ecology and evolution because they mobilize accessory genes by horizontal gene transfer. However, recent studies have revealed that the evolutionary impact of plasmids goes above and beyond their being mere gene delivery platforms. Plasmids are usually kept at multiple copies per cell, producing islands of polyploidy in the bacterial genome. As a consequence, the evolution of plasmid-encoded genes is governed by a set of rules different from those affecting chromosomal genes, and these rules are shaped by unusual concepts in bacterial genetics, such as genetic dominance, heteroplasmy or segregational drift. In this Review, we discuss recent advances that underscore the importance of plasmids in bacterial ecology and evolution beyond horizontal gene transfer. We focus on new evidence that suggests that plasmids might accelerate bacterial evolution, mainly by promoting the evolution of plasmid-encoded genes, but also by enhancing the adaptation of their host chromosome. Finally, we integrate the most relevant theoretical and empirical studies providing a global understanding of the forces that govern plasmid-mediated evolution in bacteria.Recent studies have revealed that the evolutionary impact of plasmids goes above and beyond their being mere gene delivery platforms. In this Review, Rodríguez-Beltrán, San Millán and colleagues discuss the advances that underscore the importance of plasmids in bacterial ecology and evolution beyond horizontal gene transfer.

Background  PacBio high fidelity (HiFi) sequencing reads are both long (15–20 kb) and highly accurate (> Q20). Because of these properties, they have revolutionised genome assembly leading to more accurate and contiguous genomes. In eukaryotes the mitochondrial genome is sequenced alongside the nuclear genome often at very high coverage. A dedicated tool for mitochondrial genome assembly using HiFi reads is still missing. Results  MitoHiFi was developed within the Darwin Tree of Life Project to assemble mitochondrial genomes from the HiFi reads generated for target species. The input for MitoHiFi is either the raw reads or the assembled contigs, and the tool outputs a mitochondrial genome sequence fasta file along with annotation of protein and RNA genes. Variants arising from heteroplasmy are assembled independently, and nuclear insertions of mitochondrial sequences are identified and not used in organellar genome assembly. MitoHiFi has been used to assemble 374 mitochondrial genomes (368 Metazoa and 6 Fungi species) for the Darwin Tree of Life Project, the Vertebrate Genomes Project and the Aquatic Symbiosis Genome Project. Inspection of 60 mitochondrial genomes assembled with MitoHiFi for species that already have reference sequences in public databases showed the widespread presence of previously unreported repeats. Conclusions  MitoHiFi is able to assemble mitochondrial genomes from a wide phylogenetic range of taxa from Pacbio HiFi data. MitoHiFi is written in python and is freely available on GitHub ( https://github.com/marcelauliano/MitoHiFi ). MitoHiFi is available with its dependencies as a Docker container on GitHub (ghcr.io/marcelauliano/mitohifi:master).

The extent of cell-to-cell variation in tumor mitochondrial DNA (mtDNA) copy number and genotype, and the phenotypic and evolutionary consequences of such variation, are poorly characterized. Here we use amplification-free single-cell whole-genome sequencing (Direct Library Prep (DLP+)) to simultaneously assay mtDNA copy number and nuclear DNA (nuDNA) in 72,275 single cells derived from immortalized cell lines, patient-derived xenografts and primary human tumors. Cells typically contained thousands of mtDNA copies, but variation in mtDNA copy number was extensive and strongly associated with cell size. Pervasive whole-genome doubling events in nuDNA associated with stoichiometrically balanced adaptations in mtDNA copy number, implying that mtDNA-to-nuDNA ratio, rather than mtDNA copy number itself, mediated downstream phenotypes. Finally, multimodal analysis of DLP+ and single-cell RNA sequencing identified both somatic loss-of-function and germline noncoding variants in mtDNA linked to heteroplasmy-dependent changes in mtDNA copy number and mitochondrial transcription, revealing phenotypic adaptations to disrupted nuclear/mitochondrial balance. Amplification-free single-cell whole-genome sequencing shows that genomic, evolutionary and biophysical factors collectively drive cell-to-cell variation in mitochondrial DNA copy number.