Bayesian Estimation of Species Divergence Times Integrating Both Fossil and Molecular Information

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

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. Nevertheless, representation of errors and uncertainties in the fossil record in a molecular dating analysis remains a challenging task. In this project, we will use models of clade divergences, fossil preservation and discovery, and morphological character evolution to derive statistical distributions of divergence times, which will be used as calibration densities for molecular clock dating. We will develop new models to describe the change in the evolutionary rate. The new models and methods will be applied to large datasets to date divergences among mammals and to date the host-switching events of the influenza virus.

Impact summary and pathways to impact

Accurate estimates of species divergence times are important to assessing the current biodiversity, and the impact of geological and environmental changes on biodiversity. The research results from this project will thus be useful for providing advice on decision making concerning biodiversity management and conservation policies.
Knowledge of absolute times of divergence between viral subtypes, and times of viral transmission from one host to another host (such as the host switch of the flu virus) is important for understanding viral transmission dynamics and vitally important for decision making concerning prevention of flu pandemics.

Academic beneficiaries

The main beneficiaries of knowledge arising from this research are scientists working in biodiversity, conservation biology, systematics, evolutionary biology, and virology. The analytical methods and computer software to be developed in this project will allow them to analyze their genetic sequence datasets rigorously, to obtain accurate estimates of divergence times.

We will attend local and international meetings to present our research results. Yang also co-organizes an advanced workshop on Computational Molecular Evolution, partially funded by the Wellcome and the EMBO, which are also relevant venues for publicizing research results from this project.

We will implement the methods and algorithms to be developed in this project in the MCMCTREE program in the PAML software package, and distribute it at its web site, free of charge to academics