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Riall, K.

Publications and source records attributed to Riall, K..

2 recordsLinked to original sources

Mutation-selection-drift balance models of complex diseases

Genetic variation that influences complex disease susceptibility is introduced into the population by mutation and removed by natural selection and genetic drift. This mutation-selection-drift-balance (MSDB) shapes the prevalence of a disease and its genetic architecture. To date, however, MSDB has only been modeled for monogenic (Mendelian) diseases. Here, we develop a MSDB model for complex disease susceptibility: we assume that genotype relates to disease risk according to the canonical liability threshold model and that selection on variants affecting risk derives from the fitness cost of the disease, and focus on diseases that are highly polygenic, entail a substantial fitness cost, and are neither extremely common in the population nor exceedingly rare. Contrasting model predictions with GWAS and other findings in humans suggests that directional selection plays little role in shaping common genetic variation affecting complex disease susceptibility but might substantially affect rare, large effect variation. In turn, common variation affecting complex disease susceptibility appears to be dominated by pleiotropic stabilizing selection on other traits. Our results further suggest that current estimates of disease heritability are likely biased. More generally, our model provides a better understanding of the evolutionary processes that shape the architecture and prevalence of complex diseases.

genetics↗

The impact of purifying and background selection on the inference of population history: problems and prospects

Current procedures for inferring population history generally assume complete neutrality - that is, they neglect both direct selection and the effects of selection on linked sites. We here examine how the presence of direct purifying selection and background selection may bias demographic inference by evaluating two commonly-used methods (MSMC and fastsimcoal2), specifically studying how the underlying shape of the distribution of fitness effects (DFE) and the fraction of directly selected sites interact with demographic parameter estimation. The results show that, even after masking functional genomic regions, background selection may cause the mis-inference of population growth under models of both constant population size and decline. This effect is amplified as the strength of purifying selection and the density of directly selected sites increases, as indicated by the distortion of the site frequency spectrum and levels of nucleotide diversity at linked neutral sites. We also show how simulated changes in background selection effects caused by population size changes can be predicted analytically. We propose a potential method for correcting for the mis-inference of population growth caused by selection. By treating the DFE as a nuisance parameter and averaging across all potential realizations, we demonstrate that even directly selected sites can be used to infer demographic histories with reasonable accuracy.

evolutionary biology↗