Research

Population and evolutionary genetics are an integral part of modern evolution biology, which explore the evolutionary processes that have shaped genetic differences among individuals, populations and closely related species.

Adapatation and selection

A strong component of research in the lab focuses on understanding genetic adaptation including:
  • Understanding patterns left in genetic diversity by recent positive selection (e.g. Spencer and Coop, Teshima et al., Przeworski et al. )
  • Identifying genetic loci that appear to be the target of recent natural selection, to help understanding the phenotypes involved, the history and spatial scales and strength of selection within a species (e.g. Hancock et al).
  • Understanding what models predict about the type of variation that respond to selection pressures, e.g. are they novel or standing genetic variation, large or small effect loci.

Evolution of Recombination Rates

Recombination is a key evolutionary force, and has key duel roles in ensuring the correct segregation of chromosomes during meiosis and generating genetic diversity. Despite these vitial roles, recombination rates are often polymorphic within a species and evolve quickly between species (Coop and Przeworski). I work on the causes and consequences of this polymorphism and rapid evolution:
  • Characterising broad and fine scale variation in recombination rates (Coop et al)
  • The impact of recombination on the efficiency of selection (Bullaughey et al)
  • Developing models and theory of the evolution of modifiers of recombination ( Coop and Myers)

Population histories

Patterns in genetic diversity reflect the common ancestry of individuals and as such contain information about past population history. I work on methods to extract this information to make robust inferences about the past history of species:
  • Developing and applying methods to estimate patterns of population spliting ( Noonan et al ).
  • Understanding what we can learn from patterns of haplotype sharing and diversity (Conrad et al).
  • Developing methods to deal with data from large numbers of populations, and how to incorporate this information in to more reliable null models for estimating selection (e.g. Hancock et al).