|Funding for:||UK Students, EU Students|
|Funding amount:||£14,777 per annum for 2018-19|
|Placed On:||6th November 2018|
|Closes:||7th January 2019|
Dr Erik Postma Centre for Ecology and Conservation, University of Exeter
Prof David Studholme Department of Biosciences, College of Life and Environmental Sciences, University of Exeter
Prof Michael Bruford University of Cardiff
Location: University of Exeter, Penryn Campus, Penryn, Cornwall TR10 9FE
This project is one of a number that are in competition for funding from the NERC Great Western Four+ Doctoral Training Partnership (GW4+ DTP). The partnership aims to provide a broad training in earth and environmental sciences, designed to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/
Despite a large body of theory describing how genetic variation and selection shape evolutionary trajectories, theoretical predictions are often at odds with what we observe in the real world. Being able to understand the source(s) of this discrepancy would significantly advance our understanding of the evolutionary process and provide a much-needed understanding of the ability of population to persist in a world changing at unprecedented rates. Although considerable effort has gone into incorporating the complexities that are typical of wild populations into our models of evolutionary change, this crucially assumes that evolution is in essence predictable. However, there is a potentially important role for stochastic processes (i.e. chance) in shaping all steps of the evolutionary process. For example, non-relatives may be genetically more similar than relatives due to Mendelian sampling, two otherwise identical individuals may differ in reproductive success because one got lucky and the other not, and random genetic drift can be responsible for large genetic changes from one year to the next. However, as of yet we lack a comprehensive understanding of the importance of stochastic versus deterministic (but unknown) processes in shaping the evolutionary dynamics of populations.
To quantify the importance of stochasticity in shaping the evolutionary dynamics of wild populations, this project capitalises on over a decade worth of individual-based long-term data for a small and isolated population of snow voles (Chionomys nivalis) in the Swiss alps. Since 2006, all individuals have been caught, individually marked, weighed and measured. DNA samples allow for the assignment of offspring to their parents, resulting in a well-resolved multigenerational pedigree. Recently this population has provided a rare example of adaptive evolution-in-action, revealing an adaptive decline in body mass in response to a change in snow fall patterns.
In this project, we will generate high-density whole-genome sequence data for individuals from different time periods, and of varying degrees of relatedness. By combining these with extensive morphological, life-history and pedigree data, as well as individual based simulations, we can quantify the relationship between pedigree and genomic relatedness, an individual’s long-term genetic contribution to the gene pool, and the role of selection versus drift in shaping allele frequency changes. Together, this will provide a unique insight into the genomics of adaptation in a wild vertebrate and the evolutionary process in general.
This project capitalises on a uniquely rich and powerful dataset that allows for answering a wide range questions, and the student is encouraged to shape the project according to their interests.
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