PROJECT TITLE:
Population genetics of amphibian-killing fungi: from big genomic data to big ecological insights
SUPERVISORS:
Dr Matteo Fumagalli (Imperial College London, Life Sciences), Professor Matthew Fisher (Imperial College London, Infectious Disease Epidemiology), Dr Richard Everitt (University of Reading, Mathematics and Statistics)
PROJECT SUMMARY:
The ability to obtain and analyse large-scale genomic data from previously neglected species is allowing researchers to understand which demographic and adaptive factors characterised species’ evolution. Recently, statistical methods that take sequencing data uncertainty into account have been proposed to accurately estimate population parameters of interest from low-quality data (Nielsen et al. Nat Rev Genet. 2011). While promising, these tools rely on the assumption on known ploidy and may fail to capture the complexity of genomes with mixed ploidy. This point is particular relevant for several species of ecological interest.
The amphibian chytrid fungus Batrachochytrium dendrobatidis (Bd) is responsible for hundreds of species’ extinctions (Fisher et al. Nature. 2012). The genetic mechanisms that underpin Bd’s virulence are not known yet, although extreme chromosomal plasticity has been suggested to play a role (Farrer et al. PLoS Genet. 2013). Large-scale genomic data from worldwide isolates, coupled with appropriate computational methods, will provide us with an opportunity to address how virulent Bd strains spread around the globe.
This project will encompass three main aims: (i) the improvement of computational methods for the inference of ploidy from large-scale high-throughput sequencing data, (ii) the development of a comprehensive bioinformatics platform alongside software for processing sequencing data of mixed-ploidy genomes, (iii) the extension of the methods developed in previous aims to genomic data of Bd isolates distributed worldwide.
HOW TO APPLY:
This project is suitable for students with either a quantitative or empirical background. Applicants should be meet the UK NERC eligibility criteria.
To apply, please follow instructions provided at the Centre for Doctoral Training in Quantitative and Modelling Skills in Ecology & Evolution (http://www.imperial.ac.uk/qmee-cdt/). Informal queries can be address to [log in to unmask]
DEADLINE 19 JANUARY 2017
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