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Departmental Seminar - Peter Keightley : Understanding the causes of variation in nucleotide diversity across the genome

When Mar 02, 2017
from 02:00 PM to 03:00 PM
Where Biffen Lecture Theatre, underneath Dept of Genetics
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2nd March 2017 - Biffen Lecture Theatre

Title: Understanding the causes of variation in nucleotide diversity across the genome

Professor Peter Keightley, Institute of Evolutionary Biology, University of Edinburgh

Host: Aylwyn Scally 

Nucleotide diversity varies between species, between populations of the same species and potentially between individuals from the same population. Diversity also varies across the genome within a given species, a phenomenon that can be driven by variation in several factors including the mutation rate, base composition, the rate of recombination, and the local frequency of functional sites (such as sites within protein-coding exons that encode amino acids). In several species, nucleotide diversity has been shown to be positively correlated with the rate of recombination and negatively correlated with the local concentration of functional elements, including protein-coding exons and conserved noncoding elements. These correlations are likely to be driven by natural selection acting within the functional elements reducing diversity at linked sites. Diversity at linked sites might be reduced either because of selection favouring advantageous mutations (leading to selective sweeps) or selection against deleterious mutations (reducing diversity by a process known as background selection). However, the relative importance of advantageous versus deleterious mutations as drivers of the observed correlations with diversity has been hard to quantify. In this seminar, I will describe recent work to address this question by population genetics analysis of whole-genome polymorphism data from wild house mice and related species. The basis of our approach is to infer distributions of fitness effects of mutations occurring within functional elements, then to determine whether we capture patterns of diversity at neutral sites around functional elements, assuming parameters of the inferred distributions in models incorporating the spatial distribution of functional elements in the genome.