Uncovering the effect of apparent stabilizing selection on genetic architecture

理解为什么面对持续的选择，特征会停止进化，这是一个挑战。我的长期研究目标是了解进化停滞的原因和后果。具有高度遗传变异的特征通常被认为是最具进化性的特征。我的假设是，这些特征在进化上比我们想象的更有限，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，对一种性状有利的基因变化可能会对其他许多总体上有害的性状产生相应的影响。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：性状将如何随着环境变化而进化，遗传变异如何在种群中保持，以及哪些性状具有最大的进化潜力。我的研究使用了一种遗传模式生物(果蝇)来解决这些问题。我的工作是研究遗传学、基因组学和新兴的表型组学领域。它回答了进化论中的基本问题，为大数据的分析开发了新的统计方法，并始终如一地突破了数量遗传学的界限。这项资助旨在通过解决三个基本问题来加深我们对进化极限的理解：1)高遗传变异性状组合背后的遗传变异是否比低遗传变异性状组合背后的遗传变异对生物体中的特征产生更多影响？2)高遗传变异性状组合是否因此比我们目前认为的更有限的进化？3)雄性和雌性共享大部分基因组如何影响种群的进化潜力？这个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。预计它将为选拔研究提供新的方法，并促进跨学科合作。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，有助于推动加拿大在这些领域的研究。这些技能，特别是我的学员将发展的量化技能，广泛适用于学术界、工业界、政府和快速增长的数据科学领域的职业。总体而言，对进化极限的更好理解将有助于更好地预测自然种群在短时间和长时间尺度上将如何进化，以及它们灭绝的风险。

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.