Representation and Incorporation of Fossil Data in Molecular Dating of Species Divergences

If our genes accumulate changes over time at a constant rate, the genetic distance between two species, measured by the number of changes accumulated, will be proportional to the time of species divergence. Thus molecules can serve as a clock, keeping time of species divergence 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 phylogenetic 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 local variation in evolutionary rate. Critical to molecular dating is the use of fossil information to calibrate the clock. In this project, we will develop statistical models and computer algorithms to accurately represent and incorporate fossil calibration information in molecular dating analysis. We will also implement models that explicitly consider errors in fossil calibrations. The new methods will be applied to analyze large sequence datasets to estimate divergence times among primates and vertebrates.

Two major improvements have recently been made to molecular clock dating methods: (i) relaxation of the clock assumption through local-clock models and (ii) incorporation of uncertainties in fossil calibrations. Furthermore, modern dating methods can analyze multiple genes and use multiple calibrations simultaneously. Nevertheless, representation of errors and uncertainties in the fossil record in a molecular dating analysis remains a challenging task. In this project, we will study models of clade divergences and species preservation in the fossil record to improve our representation of fossil calibration information for molecular clock dating. We will implement models that explicitly account for errors in the fossil record. We will conduct computer simulation to examine the impact of fossil calibrations on divergence time estimation. The new models and methods will be applied to large datasets to estimate the divergence times among primates and among vertebrates.