Uncovering the effect of apparent stabilizing selection on genetic architecture

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Understanding why traits stop evolving in the face of persistent selection is a challenge. My long-term research objective is to understand the causes and consequences of evolutionary stasis. Traits with high genetic variation are typically thought to be the most evolvable traits. My hypothesis is that these traits are more evolutionarily limited than we think, because the genetic variants that underlie these traits also underlie many other traits in an organism. A genetic change beneficial for one trait, may therefore have corresponding effects on many other traits that could be detrimental overall. Understanding how patterns of genetic variation, how the correlated effects of genes on many traits, and how selection interact is critical to understanding three central questions in evolutionary biology: how traits will evolve in response to environmental change, how genetic variation is maintained in populations, and which traits have the greatest evolutionary potential. My research uses a genetic model organism (Drosophila) to address these questions. My work is at the interface of genetics, genomics, and the emerging area of phenomics. It answers fundamental questions in evolutionary theory, develops new statistical methods for the analysis of `big data', and consistently pushes the boundaries of quantitative genetics. This grant seeks to further our understanding of evolutionary limits by addressing three fundamental questions: 1) Do the genetic variants that underlie trait combinations with high genetic variation affect more traits in an organism than the genetic variants that underlie trait combinations with low genetic variation? 2) Are trait combinations with high genetic variation more evolutionary limited than we currently think because of this? 3) How does males and females sharing most of their genome affect the evolutionary potential of populations? This project will develop and implement novel evolutionary and statistical manipulations and methods to provide fundamental insights into previously untested evolutionary theory. It is expected to provide new methods for the study of selection and to foster interdisciplinary collaborations. This research will also provide high caliber students and postdoctoral researchers with training in evolutionary biology, genetics and genomics, statistics, and computational techniques, helping to advance Canada's research profile in these areas. These skills, particularly the quantitative skills that my mentees will develop, are widely applicable to careers in academia, industry, government, and the rapidly growing field of data science. Overall, a better understanding of evolutionary limits will enable better predictions of how natural populations will evolve over short and long timescales, and their risks of extinction.