Selection and explosive growth alter genetic architecture and hamper the detection of causal rare variants
Year: 2016
Type: preprint
Abstract: The role of rare alleles in complex phenotypes has been hotly debated, but most rare variant association tests (RVATs) do not account for the evolutionary forces that affect genetic architecture. Here, we use simulation and numerical algorithms to show that explosive population growth, as experienced by human populations, can dramatically increase the impact of very rare alleles on trait variance. We then assess the ability of RVATs to detect causal loci using simulations and human RNA-seq data. Surprisingly, we find that statistical performance is worst for phenotypes in which genetic variance is due mainly to rare alleles, and explosive population growth decreases power. Although many studies have attempted to identify causal rare variants, few have reported novel associations. This has sometimes been interpreted to mean that rare variants make negligible contributions to complex trait heritability. Our work shows that RVATs are not robust to realistic human evolutionary forces, so general conclusions about the impact of rare variants on complex traits may be premature.
Source: Genome Research
Institutions: University of California, San Francisco, QB3
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: bronze
Funders: Alfred P. Sloan Foundation, California Institute for Quantitative Biosciences, National Institutes of Health, University of California, San Francisco, National Heart, Lung, and Blood Institute, National Human Genome Research Institute, National Cancer Institute, National Institute of General Medical Sciences, National Institute on Minority Health and Health Disparities
Awards: Powerful Simulation Tools for the Genomics Age, Richer Models of Asthma Risk: Bridging the Environment-Genetics Divide, Addressing disparities in chronic disease with a teen and young adult focus, The Airway Functional Genomics of Bronchodilator Drug Response in Minority Children with Asthma, Genetic Epidemiology of Prostate Cancer Risk and Progression, BMI Bioinformatics Training Grant, Genomewide Association Study of Prostate Cancer, SPORE in Prostate Cancer
OpenAlex ID: W2402771944