Interference Selection and the Statistics of Evolution in Microbes

该奖项资助哈佛大学迈克尔·德赛教授的研究活动。在许多微生物和病毒的大型无性群体中，多种突变经常同时出现。自然选择不能单独作用于每个染色体，而只能作用于物理染色体上连接在一起的突变组合，这种效应被称为干扰选择。这些种群的进化涉及到有益突变的积累（适应）和弱有害突变的随机积累（穆勒棘轮）之间的复杂平衡。在这个项目中，PI将开发数学模型来预测这种有益和有害突变之间的干扰选择如何改变微生物种群的进化动态和遗传多样性，并使用芽殖酵母作为模型系统的实验进化来测试这些预测。该项目将侧重于(1)种群内的适应度分布，(2)固定突变的适应度效应分布，以及(3)种群内遗传多样性模式。这项研究还将产生更广泛的重大影响。它将包括研究生和博士后，提供跨学科的培训，涉及统计物理学、进化生物学、群体遗传学和应用数学的综合方法。PI还将开发新的课程，以帮助物理科学家过渡到进化和群体遗传学的研究。这将包括一门本科课程，提供数学上复杂但生物学上naïve介绍进化理论的定量基础。此外，PI将在法国Cargese共同组织一所暑期学校，为寻求过渡到进化和群体遗传学的研究生和博士后水平的物理科学家提供服务。该暑期学校将使用该提案中的研究作为几个案例研究之一，说明群体遗传理论、生物信息学和定量实验如何有助于我们对进化的理解。

This award funds the research activities of Professor Michael Desai at Harvard University. In the large and mostly asexual populations characteristic of many microbes and viruses, multiple mutations are often present simultaneously. Natural selection cannot act on each separately, but rather only on combinations of mutations linked together on physical chromosomes, an effect known as interference selection. Evolution in these populations involves a complex balance between the accumulation of beneficial mutations (adaptation) and the stochastic accumulation of weakly deleterious mutations (Muller's ratchet). In this project, the PI will develop mathematical models to predict how this interference selection among the full spectrum of beneficial and deleterious mutations alters evolutionary dynamics and genetic diversity in microbial populations, and test these predictions using experimental evolution of budding yeast as a model system. The project will focus on (1) the distribution of fitness within a population, (2) the distribution of fitness effects of fixed mutations, and (3) the within-population patterns of genetic diversity.This research will also have significant broader impacts. It will involve graduate students and postdocs, providing interdisciplinary training involving the integration of methods from statistical physics, evolutionary biology, population genetics, and applied mathematics. The PI will also develop new course curricula to help physical scientists transition into research in evolution and population genetics. This will include an undergraduate course providing a mathematically sophisticated but biologically naïve introduction to the quantitative basis of evolutionary theory. In addition, the PI will co-organize a summer school in Cargese, France, to serve the broader community of physical scientists at the graduate and postdoctoral levels seeking to transition into evolution and population genetics. The summer school will use the research in this proposal as one of several case studies illustrating how population genetic theory, bioinformatics, and quantitative experiments can all contribute to our understanding of evolution.