Stochastic modelling, Bayesian inference, and new in vivo measurements elucidate the debated mtDNA bottleneck mechanism

Abstract

Dangerous damage to mitochondrial DNA (mtDNA) can be ameliorated during mammalian development through a highly debated mechanism called the mtDNA bottleneck. Uncertainty surrounding this process limits our ability to address inherited mtDNA diseases. We produce a new, physically motivated, generalisable theoretical model for mtDNA populations during development, allowing the first statistical comparison of proposed bottleneck mechanisms. Using approximate Bayesian computation and mouse data, we find most statistical support for a combination of binomial partitioning of mtDNAs at cell divisions and random mtDNA turnover, meaning that the debated exact magnitude of mtDNA copy number depletion is flexible. New experimental measurements from a wild-derived mtDNA pairing in mice confirm the theoretical predictions of this model. We analytically solve a mathematical description of this mechanism, computing probabilities of mtDNA disease onset, efficacy of clinical sampling strategies, and effects of potential dynamic interventions, thus developing a quantitative and experimentally-supported stochastic theory of the bottleneck.DOI: http://dx.doi.org/10.7554/eLife.07464.001

A Population Phylogenetic View of Mitochondrial Heteroplasmy

“…This is concordant with a recent analysis of the time-evolution of heteroplasmy variance in mouse oocytes, which concluded that the actual minimal bottleneck size is difficult to determine and may have only limited impact on overall heteroplasmy dynamics during oogenesis (Johnston et al, 2015). However, our estimates of the EBS (median 24.5, 95% CI: 11.6-35.1) are similar to other recent estimates of the oogenic bottleneck size, including an estimate of 32.3 in a previous analysis of the data used in this study (Rebolledo-Jaramillo et al, 2014), and a previous estimate of 9 in Li et al (2016).…”

“…There has been considerable debate about whether the mechanism of this bottleneck involves an actual decrease in the number of mitochondrial genome copies versus co-segregation of genetically homogeneous groups of mitochondrial DNA (e.g., Jenuth et al, 1996;Cao et al, 2007;Cree et al, 2008;Wai et al, 2008;Carling et al, 2011). Nevertheless, in order to better predict the change in heteroplasmy frequencies between generations, previous studies have sought to infer the size of the oogenic bottleneck, either through direct observation (in mice) of the number of mitochondrial DNA genome copies (Cree et al, 2008;Cao et al, 2007), or through indirect measurement, making statistical conclusions about the bottleneck size based on observed frequency changes between generations (Johnston et al, 2015;Rebolledo-Jaramillo et al, 2014;Millar et al, 2008;Hendy et al, 2009;Li et al, 2016). Recently, Johnston et al (2015) have proposed a statistical framework that combines direct observations of mtDNA copy number with genetic variance in order to make inferences about the dynamics of the oogenic bottleneck.…”

“…Such an approach would need to account for the phylogenetic and developmental relationships between sampled tissues in order to make full use of the information contained in the observed heteroplasmy allele frequencies. While a number of studies have employed or developed population-genetic models to study mitochondrial heteroplasmy (e.g., Wonnapinij et al, 2008;Hendy et al, 2009;Johnston et al, 2015;Johnston and Jones, 2016), few have considered the phylogenetic relationship between tissues in doing so, often because only a single tissue type is under consideration. Recently, Burgstaller et al (2014) inferred tissue-specific rates of heteroplasmy segregation in artificially heteroplasmic mouse lines, implicitly relating the sampled tissues by a star-like phylogeny.…”

“…Nevertheless, in order to better predict the change in heteroplasmy frequencies between generations, previous studies have sought to infer the size of the oogenic bottleneck, either through direct observation (in mice) of the number of mitochondrial DNA genome copies (Cree et al, 2008;Cao et al, 2007), or through indirect measurement, making statistical conclusions about the bottleneck size based on observed frequency changes between generations (Johnston et al, 2015;Rebolledo-Jaramillo et al, 2014;Millar et al, 2008;Hendy et al, 2009;Li et al, 2016). Recently, Johnston et al (2015) have proposed a statistical framework that combines direct observations of mtDNA copy number with genetic variance in order to make inferences about the dynamics of the oogenic bottleneck. In mice, estimates of the physical bottleneck size have ranged from 200 to more than 1000 (Cree et al, 2008;Cao et al, 2007;Johnston et al, 2015), and in a recent re-analysis of previous data, it was claimed that the minimal bottleneck size may have only small effects on heteroplasmy transmission dynamics, depending on the details of how oogonia proliferate (Johnston et al, 2015).…”

“…Recently, Johnston et al (2015) have proposed a statistical framework that combines direct observations of mtDNA copy number with genetic variance in order to make inferences about the dynamics of the oogenic bottleneck. In mice, estimates of the physical bottleneck size have ranged from 200 to more than 1000 (Cree et al, 2008;Cao et al, 2007;Johnston et al, 2015), and in a recent re-analysis of previous data, it was claimed that the minimal bottleneck size may have only small effects on heteroplasmy transmission dynamics, depending on the details of how oogonia proliferate (Johnston et al, 2015). In humans, indirect estimates of the effective genetic bottleneck size have ranged from 1 to 200, depending on the dataset and the statistical methods used to estimate the bottleneck size (Marchington et al, 1997;Guo et al, 2013).…”