Heteroplasmy, the mixture of mitochondrial genomes (mtDNA), varies among individuals and cells. Heteroplasmy levels alter the penetrance of pathological mtDNA mutations, and the susceptibility to age-related diseases such as Parkinson's disease. Although mitochondrial dysfunction occurs in age-related type 2 diabetes mellitus (T2DM), the involvement of heteroplasmy in diabetes is unclear. We hypothesized that the heteroplasmic mutational (HM) pattern may change in T2DM. To test this, we used next-generation sequencing, i.e. massive parallel sequencing (MPS), along with PCR-cloning-Sanger sequencing to analyze HM in blood and skeletal muscle DNA samples from monozygotic (MZ) twins either concordant or discordant for T2DM. Great variability was identified in the repertoires and amounts of HMs among individuals, with a tendency towards more mutations in skeletal muscle than in blood. Whereas many HMs were unique, many were either shared among twin pairs or among tissues of the same individual, regardless of their prevalence. This suggested a heritable influence on even low abundance HMs. We found no clear differences between T2DM and controls. However, we found ~5-fold increase of HMs in non-coding sequences implying the influence of negative selection (P < 0.001). This negative selection was evident both in moderate to highly abundant heteroplasmy (>5% of the molecules per sample) and in low abundance heteroplasmy (<5% of the molecules). Although our study found no evidence supporting the involvement of HMs in the etiology of T2DM, the twin study found clear evidence of a heritable influence on the accumulation of HMs as well as the signatures of selection in heteroplasmic mutations.

Mutations frequently reoccur in the human mitochondrial DNA (mtDNA). However, it is unclear whether recurrent mtDNA nodal mutations (RNMs), that is, recurrent mutations in stems of unrelated phylogenetic nodes, are functional and hence selectively constrained. To answer this question, we performed comprehensive parsimony and maximum likelihood analyses of 9,868 publicly available whole human mtDNAs revealing 1,606 single nodal mutations (SNMs) and 679 RNMs. We then evaluated the potential functionality of synonymous, nonsynonymous and RNA SNMs and RNMs. For synonymous mutations, we have implemented the Codon Adaptation Index. For nonsynonymous mutations, we assessed evolutionary conservation, and employed previously described pathogenicity score assessment tools. For RNA genes’ mutations, we designed a bioinformatic tool which compiled evolutionary conservation and potential effect on RNA structure. While comparing the functionality scores of nonsynonymous and RNA SNMs and RNMs with those of disease-causing mtDNA mutations, we found significant difference (P < 0.001). However, 24 RNMs and 67 SNMs had comparable values with disease-causing mutations reflecting their potential function thus being the best candidates to participate in adaptive events of unrelated lineages. Strikingly, some functional RNMs occurred in unrelated mtDNA lineages that independently altered susceptibility to the same diseases, thus suggesting common functionality. To our knowledge, this is the most comprehensive analysis of selective signatures in the mtDNA not only within proteins but also within RNA genes. For the first time, we discover virtually all positively selected RNMs in our phylogeny while emphasizing their dual role in past evolutionary events and in disease today.

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Multiple human mutational landscapes of normal and cancer conditions are currently available. However, while the unique mutational patterns of tumors have been extensively studied, little attention has been paid to similarities between malignant and normal conditions. Here we compared the pattern of mutations in the mitochondrial genomes (mtDNAs) of cancer (98 sequences) and natural populations (2400 sequences). De novo mtDNA mutations in cancer preferentially colocalized with ancient variants in human phylogeny. A significant portion of the cancer mutations was organized in recurrent combinations (COMs), reaching a length of seven mutations, which also colocalized with ancient variants. Thus, by analyzing similarities rather than differences in patterns of mtDNA mutations in tumor and human evolution, we discovered evidence for similar selective constraints, suggesting a functional potential for these mutations.

Several methods have been proposed for detecting insertion/deletions (indels) from chromatograms generated by Sanger sequencing. However, most such methods are unsuitable when the mutated and normal variants occur at unequal ratios, such as is expected to be the case in cancer, with organellar DNA or with alternatively spliced RNAs. In addition, the current methods do not provide robust estimates of the statistical confidence of their results, and the sensitivity of this approach has not been rigorously evaluated. Here, we present CHILD, a tool specifically designed for indel detection in mixtures where one variant is rare. CHILD makes use of standard sequence alignment statistics to evaluate the significance of the results. The sensitivity of CHILD was tested by sequencing controlled mixtures of deleted and undeleted plasmids at various ratios. Our results indicate that CHILD can identify deleted molecules present as just 5% of the mixture. Notably, the results were plasmid/primer-specific; for some primers and/or plasmids, the deleted molecule was only detected when it comprised 10% or more of the mixture. The false positive rate was estimated to be lower than 0.4%. CHILD was implemented as a user-oriented web site, providing a sensitive and experimentally validated method for the detection of rare indel-carrying molecules in common Sanger sequence reads.

Mitochondrial DNA (mtDNA) mutations are long known to cause diseases but also underlie tremendous population divergence in humans. It was assumed that the two types of mutations differ in one major trait: functionality. However, evidence from disease association studies, cell culture and animal models support the functionality of common mtDNA genetic variants, leading to the hypothesis that disease-causing mutations and mtDNA genetic variants share considerable common features. Here we provide evidence showing that the two types of mutations obey the rules of evolution, including random genetic drift and natural selection. This similarity does not only converge at the principle level; rather, disease-causing mutations could recapitulate the ancestral DNA sequence state. Thus, the very same mutations could either mark ancient evolutionary changes or cause disease.

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