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Inferring selection and demography from population genomic data

Thursday 11 October 2018, 1.00PM

Speaker(s): Dr Kai Zeng, Sheffield

With continuing improvements in sequencing technologies, genome-scale datasets are readily obtainable for the vast majority of organisms. These data offer new opportunities for gaining deeper insights into how the course of evolution is shaped by forces such as natural selection and demographic changes. Theoretical modelling plays an important role in this quest, as realistic models help to generate new hypotheses and enable information to be extracted from the data more accurately and efficiently.

Here I present the results of several studies that involve both the development of new population genetic models and their application to large-scale datasets. This combined approach has allowed us to address a range of questions in several different species (including passerine birds and Drosophila): (1) what determines the efficacy of natural selection; (2) how does GC-biased gene conversion interact with natural selection and what are the evolutionary consequences of these interactions; (3) what effects do polymorphic insertions and deletions (INDELs) have on fitness and are patterns of INDEL polymorphism shaped by genetic hitchhiking; (4) how to compare polymorphism data collected from autosomes and sex chromosomes so as to find evidence for male-driven evolution, unequal sex ratios, or sex-biased demographic changes; (5) how to improve the accuracy of demographic inferences by accounting for heterogeneity across the genome in, e.g., the mutation rate. The models are non-organism specific and our results suggest that they should be applicable to a wide range of species.

Location: K018