Award details

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

Reference	BB/J00538X/1
Principal Investigator / Supervisor	Professor Philip Donoghue
Co-Investigators / Co-Supervisors
Institution	University of Bristol
Department	Earth Sciences
Funding type	Research
Value (£)	64,476
Status	Completed
Type	Research Grant
Start date	18/05/2012
End date	31/07/2015
Duration	38 months

Abstract

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.

Summary

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 programs to analyze fossil and molecular data to accurately represent and incorporate the information in the fossil record in molecular dating analysis. The new methods will be applied to analyze datasets to estimate divergence times among mammals and to date viral transmission events.

Impact Summary

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

Committee	Research Committee C (Genes, development and STEM approaches to biology)
Research Topics	Technology and Methods Development
Research Priority	Technology Development for the Biosciences
Research Initiative	X - not in an Initiative
Funding Scheme	X – not Funded via a specific Funding Scheme

Associated awards:

BB/J009709/1 Bayesian Estimation of Species Divergence Times Integrating Fossil and Molecular Information

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