The mitochondria powering your cells are not all genetically identical. Genetic variation across the mitochondria of a single individual is common. This diversity is called mitochondrial heteroplasmy, and it plays an important role in the severity of mitochondrial disease. Problematically, the complexities of mitochondrial inheritance makes it extremely difficult to predict how this diversity is transmitted between generations or cells.
In a report in GENETICS, Wilton et al. developed a mathematical model of mitochondrial heteroplasmy. Using previously published data, as well as a statistical framework based on population genetic principles, their model was able to account for observed diversity in mitochondria.
This model highlights how heteroplasmy is regulated by developmental bottlenecks: For example, because mitochondria are passed on mother-to-child, the random sample of mitochondria present in the mother’s egg cells determine the genetic makeup of mitochondria in her offspring—just like founder’s effect in classical population genetics. The authors also find evidence of less severe bottlenecks during the formation of distinct germ layers and organs; any time a cell or a small subset of cells gives rise to a larger structure during development, the mitochondria present in those first few cells set the mitochondrial heteroplasmy of the resulting organs.
The authors acknowledge that their model is preliminary. It doesn’t take into account any kind of quality control during the formation of egg cells that would change which mitochondrial mutations are passed on. Still, this model is an important starting point. It could be used to examine how natural selection plays out at the level of mitochondria, which in turn could help us better understand mitochondria-associated diseases and aging. It could even prove useful beyond heteroplasmy: cancer is another kind of genetic heterogeneity within a single person, and a similar approach could be used to investigate the bottlenecks and other factors that shape the evolution of a tumor.