Uncovering the effect of apparent stabilizing selection on genetic architecture

理解为什么性状在持续选择面前停止进化是一个挑战。我的长期研究目标是了解进化停滞的原因和后果。具有高遗传变异的性状通常被认为是最可进化的性状。我的假设是，这些特征在进化上比我们想象的更受限制，因为构成这些特征的遗传变异也构成了生物体中许多其他特征的基础。因此，对一个性状有益的遗传变化可能对许多其他性状产生相应的影响，而这些影响可能是有害的。了解遗传变异的模式、基因对许多性状的相关影响以及选择如何相互作用，对于理解进化生物学中的三个核心问题至关重要：性状如何响应环境变化而进化，遗传变异如何在种群中维持，以及哪些性状具有最大的进化潜力。我的研究使用遗传模式生物（果蝇）来解决这些问题。我的工作是在遗传学，基因组学和表型组学的新兴领域的接口。它回答了进化理论中的基本问题，开发了用于分析“大数据”的新统计方法，并不断推动数量遗传学的界限。这项资助旨在通过解决三个基本问题来进一步理解进化极限：1）作为具有高遗传变异的性状组合基础的遗传变异是否比作为具有低遗传变异的性状组合基础的遗传变异影响生物体中更多的性状？2)因此，具有高遗传变异的性状组合是否比我们目前认为的更具进化限制性？3)男性和女性共享大部分基因组如何影响种群的进化潜力？该项目将开发和实施新的进化和统计操作和方法，以提供对以前未经测试的进化理论的基本见解。它有望为选择的研究提供新的方法，并促进跨学科的合作。这项研究还将为高素质的学生和博士后研究人员提供进化生物学，遗传学和基因组学，统计学和计算技术方面的培训，帮助推进加拿大在这些领域的研究概况。这些技能，特别是我的学员将发展的定量技能，广泛适用于学术界，工业界，政府和快速发展的数据科学领域的职业生涯。总的来说，更好地理解进化极限将有助于更好地预测自然种群在短期和长期时间尺度上的进化方式及其灭绝风险。

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.