Department of Mathematics, University of Bergen, Bergen, Norway.
Computational Biology Unit, University of Bergen, Bergen, Norway.
PLoS Comput Biol. 2023 Mar 23;19(3):e1010953. doi: 10.1371/journal.pcbi.1010953. eCollection 2023 Mar.
Mitochondria are highly dynamic organelles, containing vital populations of mitochondrial DNA (mtDNA) distributed throughout the cell. Mitochondria form diverse physical structures in different cells, from cell-wide reticulated networks to fragmented individual organelles. These physical structures are known to influence the genetic makeup of mtDNA populations between cell divisions, but their influence on the inheritance of mtDNA at divisions remains less understood. Here, we use statistical and computational models of mtDNA content inside and outside the reticulated network to quantify how mitochondrial network structure can control the variances of inherited mtDNA copy number and mutant load. We assess the use of moment-based approximations to describe heteroplasmy variance and identify several cases where such an approach has shortcomings. We show that biased inclusion of one mtDNA type in the network can substantially increase heteroplasmy variance (acting as a genetic bottleneck), and controlled distribution of network mass and mtDNA through the cell can conversely reduce heteroplasmy variance below a binomial inheritance picture. Network structure also allows the generation of heteroplasmy variance while controlling copy number inheritance to sub-binomial levels, reconciling several observations from the experimental literature. Overall, different network structures and mtDNA arrangements within them can control the variances of key variables to suit a palette of different inheritance priorities.
线粒体是高度动态的细胞器,包含分布在整个细胞中的重要线粒体 DNA (mtDNA) 群体。线粒体在不同的细胞中形成不同的物理结构,从遍布整个细胞的网状网络到碎片化的单个细胞器。这些物理结构已知会影响细胞分裂之间 mtDNA 群体的遗传组成,但它们对分裂时 mtDNA 的遗传影响了解较少。在这里,我们使用在线粒体网状结构内外的 mtDNA 含量的统计和计算模型,来量化线粒体网络结构如何控制遗传 mtDNA 拷贝数和突变负荷的方差。我们评估了基于矩的近似值来描述异质性方差的用途,并确定了在几种情况下,这种方法存在缺陷。我们表明,网络中一种 mtDNA 类型的偏向性包含可以显著增加异质性方差(充当遗传瓶颈),而通过细胞控制网络质量和 mtDNA 的分布则可以相反地将异质性方差降低到二项式遗传模式以下。网络结构还可以在控制拷贝数遗传到亚二项式水平的同时产生异质性方差,从而调和实验文献中的几个观察结果。总的来说,不同的网络结构和其中的 mtDNA 排列可以控制关键变量的方差,以适应不同的遗传优先级。