Synthesising methods and data to understand the mutational processes that shape genomes (Visiting Scholar)
Mutation is one of the most fundamentally important sources of variation between living organisms, and understanding the causes and consequences of mutation is central to evolutionary biology. However, we still know relatively little about how and why mutational processes vary between taxa. This is critical because understanding mutation is central to how we use and interpret DNA sequence data, and there is a growing reliance upon such data across the biological sciences. Studies on model organisms have led to a detailed knowledge of the biochemical causes of mutation in a handful of taxa. However, we lack methods with which to exploit this knowledge in order to understand mutation in a broader framework. I will synthesise the results from model organism studies with novel statistical and phylogenetic methods. These methods will use DNA sequence data to estimate biologically meaningful parameters that relate directly to particular mutational processes. I will integrate these methods with large DNA, life-history and protein structure datasets to test specific hypotheses about the causes and consequences of mutation. This work will significantly extend our current understanding of how and why mutational processes vary between taxa, generate novel insights from existing data, and spur the development of more appropriate methods of DNA sequence analysis across the biological sciences.