Improving Bayesian methods for estimating divergence times integrating genomic and trait data

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After one species splits into two, their genes and genomes will evolve independently. If the rate of evolution is constant over time, the genetic differences between species will accumulate at a fixed pace, proportional to the time of species separation. Thus molecules can serve as a clock, keeping time of species separation by the accumulated changes. If fossil records or geological events can be used to assign an absolute geological time to a species divergence event on the evolutionary tree, one can convert all calculated genetic distances into absolute geological times. This rationale for molecular clock dating has recently been extended to deal with variable evolutionary rate over time in the so-called relaxed-clock models. For fast-evolving viral DNA, the different sampling times of the viral sequences allows us to similarly calibrate the molecular and to obtain estimates of the absolute divergence times and evolutionary rates. In this project, we will develop statistical models of trait evolution, which will be used to analyse morphological trait data for both living and extinct species to generate fossil calibrations, which are crucially important to molecular dating analysis. Such models of trait evolution will also allow us to study the correlation between viral molecular sequence evolution and viral genotypes such as antigenic drift. We will apply the new methods to analyse real datasets to date major divergence events in the tree of life, such as the divergences of the human and the apes, the primates, the animals, and the flowering plants.