Mitochondrial Eve Dating based on Computer Simulations of Coalescence Distributions for Stochastic vs. Deterministic Population Models

One of the crucial issues in contemporary evolutionary genetics is dating of the common ancestors of different species. Applicability of several existing approaches based on coalescence theory is limited to deterministic population trajectories, known to be unrealistic. In the paper the computer simulation based approach is presented, which is capable to deal with different population history scenarios, including populations evolving stochastically and with changing environment. This approach arises from comparison of O’Connell’s and Fisher-Wright models. It is applied to estimate the age of our most recent female common ancestor, called Mitochondrial Eve, based on the genetic material from mitochondrial DNA belonging to contemporary humans and Neanderthal fossils. Obtained results indicate that after changing the outgroup from chimpanzee to Neanderthals, the stochastic genetic models with different assumptions tend to give similar predictions, and therefore these predictions are much more reliable than they were before. Key-Words: Stochastic trajectories, coalescent distributions, Mitochondrial DNA, Neanderthal fossils, Mitochondrial Eve dating, Branching processes, Genetic information processing, Stochastic computer simulations.