Abstract

Understanding and quantifying the rates of change in the mitochondrial genome is a major component of many areas of biological inquiry, from phylogenetics to human health. A critical parameter in understanding rates of change is estimating the mitochondrial mutation rate (mtDNA MR). Although the first direct estimates of mtDNA MRs were reported almost 20 years ago, the number of estimates has not grown markedly since that time. This is largely owing to the challenges associated with time- and labour-intensive mutation accumulation (MA) experiments. But even MA experiments do not solve a major problem with estimating mtDNA MRs—the challenge of disentangling the role of mutation from other evolutionary forces acting within the cell. Now that it is widely understood that any newly generated mutant allele in the mitochondria will initially be at very low frequency (1/N, where N is the number of mtDNA molecules in the cell), the importance of understanding the effective population size (Ne) of the mtDNA and the size of genetic bottlenecks during gametogenesis and development has come into the spotlight. In addition to these factors regulating the role of genetic drift, advances in our understanding of mitochondrial replication and turnover allow us to more easily envision how natural selection within the cell might favour or purge mutations in multi-copy organellar genomes. Here, we review the unique features of the mitochondrial genome that pose a challenge for accurate MR estimation and discuss ways to overcome those challenges. Estimates of mtDNA MRs remain one of the most widely used parameters in biology, thus accurate quantification and a deeper understanding of how and why they may vary within and between individuals, populations and species is an important goal.This article is part of the theme issue ‘Linking the mitochondrial genotype to phenotype: a complex endeavour’.

Highlights

  • Understanding and quantifying the rates of change in the mitochondrial genome is a major component of many areas of biological inquiry, from phylogenetics to human health

  • In principle, mtDNA mutation rates (MRs) depend only on the rate of replication mistakes and unrepaired DNA damage, the fact that there are multiple copies of the mtDNA genome per mitochondrion and multiple mitochondria per cell means that the fate of a given mutation in the cell depends on its selective coefficient and the efficacy of selection to act upon that mutation, relative to the likelihood that it will be lost or fixed by genetic drift

  • It is essential 5 that we obtain estimates just for a single genotype from a few model species, but expand our empirical assays to include non-model organisms and multiple genotypes per taxon, in order to understand how mtDNA MRs evolve. Investigating both germline and somatic mtDNA MRs represents a current frontier in the field

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Summary

Why estimating mtDNA ‘mutation rates’ is such a challenge

The existence of mtDNA genomes in multiple copies within each cell (heteroplasmy) means that estimating ‘MRs’ in the mtDNA requires calculating the rates of occurrence of very low frequency (1/N) new mutant alleles. The advent of short read/high coverage sequencing platforms has made it possible to sequence the mtDNA to sufficient depth to detect even low-frequency variants, but given the number of mtDNA per nucleoid, the number of nucleoids per cell, and the number of cells per individual, our ability to detect new mutations is still extremely limited. This makes it difficult to distinguish between low-frequency variants that might already exist in the ‘population’ and new mutant alleles. The problem of disentangling mutation, selection and drift for estimating mtDNA MRs may be relegated to the world of modelling and simulations for the time being (e.g. [30]), while empiricists settle for composite estimates that do not isolate the MR, per se, but do provide a more accurate estimate than classical substitution rates calculated based on sequence comparisons alone

Is it possible to more accurately estimate mtDNA mutation rates?
Conclusion
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