Mitochondria are the swarming powerplants of the cell, a bacteria-like herd of self-replicating machines that produce the chemical energy stores that power cellular processes. They bear their own DNA, and damage to this mitochondrial DNA (mtDNA) damage is important in aging. Per the mitochondrial free radical theory of aging, some types of mitochondrial DNA damage spread throughout the population of mitochondria in a cell, subverting the quality control mechanisms that normally destroy damaged mitochondria. This leads to harmfully altered mitochondrial function and malfunctioning cells that export damaging reactive compounds into the surrounding tissues.
At this point the fastest way to confirm theories on aging and mitochondrial DNA damage is to implement one of the ways to replace or repair mitochondria DNA. There are a range of potential methods that might result in therapies. In the future, people will probably have their mitochondrial DNA globally refreshed every few decades, removing this contribution to degenerative aging.
Here researchers argue that the spread of mitochondrial DNA damage to all the mitochondria in a cell can't be just random, and thus has be driven by some advantage in selection - such as the ability to fool quality control mechanisms, as is proposed in mitochondrial theories of aging. If damaged mitochondria are culled by the cell less often, they will eventually out-compete undamaged mitochondria.
Mitochondrial DNA deletions accumulate over the life course in post-mitotic cells of many species and may contribute to aging. Often a single mutant expands clonally and finally replaces the wild-type population of a whole cell. One proposal to explain the driving force behind this accumulation states that random drift alone, without any selection advantage, is sufficient to explain the clonal accumulation of a single mutant.
Existing mathematical models show that such a process might indeed work for humans. However, to be a general explanation for the clonal accumulation of mtDNA mutants, it is important to know whether random drift could also explain the accumulation process in short-lived species like rodents. To clarify this issue, we modelled this process mathematically and performed extensive computer simulations to study how different mutation rates affect accumulation time and the resulting degree of heteroplasmy. We show that random drift works for lifespans of around 100 years, but for short-lived animals, the resulting degree of heteroplasmy is incompatible with experimental observations.