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。在以许多微生物和病毒为特征的庞大且主要是无性的种群中，多个突变经常同时存在。自然选择不能单独作用于其中的每一个，而只能作用于物理染色体上链接在一起的突变的组合，这一效应被称为干扰选择。这些种群的进化涉及有益突变的积累(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在有益和有害突变的全谱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，并使用发芽酵母的实验进化作为模型系统来测试这些预测。该项目将专注于(1)种群内适应度的分布，(2)固定突变的适应度效应的分布，以及(3)遗传多样性的种群内模式。这项研究也将产生重大的更广泛的影响。它将涉及研究生和博士后，提供跨学科的培训，涉及统计物理、进化生物学、种群遗传学和应用数学方法的整合。PI还将开发新的课程课程，以帮助物理学家过渡到进化论和种群遗传学的研究。这将包括一门本科课程，提供一门数学上复杂但生物学上幼稚的课程，介绍进化论的量化基础。此外，PI将在法国Cargese共同举办暑期班，为寻求过渡到进化论和种群遗传学的更广泛的研究生和博士后水平的物理学家社区服务。暑期班将使用这项提案中的研究作为几个案例研究之一，说明人口遗传学理论、生物信息学和定量实验如何都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.