Fitness Effects of Beneficial Mutations

项目摘要/摘要 进化过程是许多人类疾病的病因学基础。例如， 传染病，不管是慢性的还是急性的，都是病原体进行军备竞赛的进化过程。 与它们的人类宿主。在现代，疫苗和抗生素使人类能够扭曲结果 在这些比赛中。然而，这些防止危机蔓延的堡垒正在被稳步侵蚀。突变与自然 选择，再加上快速的世代时间和巨大的病原菌种群规模，似乎提供了 病原体在进化竞赛中占据决定性优势。为了重新占据上风，我们必须更好地理解 进化过程本身，以帮助开发新型抗菌剂并设计出治疗方法 考虑到这些武器如何工作以及病原体如何自适应进化以颠覆它们的战略。 然而，直到最近，我们在努力获得对适应性的深刻理解方面一直受到阻碍 过程，因为适应性突变很少见。我的实验室开发了一种血统跟踪系统，它使用HIGH 吞吐量测序使我们能够几乎实时地跟踪进化过程。我们能够追踪到 进化过程很容易分离出数千个适应性谱系，重新衡量这些谱系的适合性 在许多环境中，以及廉价的全基因组序列中，有数百到数千个这样的突变体。 我提出了一个雄心勃勃的综合计划，将利用这个血统追踪系统。首先，我们 将决定种群进化的环境--以及该种群的倍性--如何控制 选择了哪些突变以及它们的适应度效应的分布。接下来，我们将确定突变是如何 在一个环境中选择，在其他环境中进行权衡，并确定为什么他们机械地这样做。最后，我们将 研究适应性突变之间的上位性，系统地确定符号和 基因相互作用的大小取决于它们的环境背景。为了实现这些目标，我们将进化 酿酒酵母单倍体和二倍体群体的合理设计 实验条件，从这些进化中分离出数百个适应谱系，然后重新测量 这些适应性克隆在其他每个条件下的适合度。这一实验计划将使 我们来描述“适应度效应的联合分布”，这是一个基因组适应性的全面图景 一种条件下的可能性，对这些可能性的进化限制，其他的，以及机械论的 这些机会和限制之间的联系，都是通过倍性和上位性的透镜来看待的。 执行这一计划将提供前所未有的洞察在替代形式下的适应过程 选择和基因组结构。对这些突变体的比较分析将有助于揭示潜在的遗传 允许遵循某些进化轨迹，但阻止其他进化轨迹的回路。用这个更深的地方武装起来 了解适应过程，我们将能够更好地预测进化的未来 基因组的存在，并在我们与慢性传染病的斗争中保持优势。

Project Summary/Abstract Evolutionary processes underlie the etiology of many human diseases. For example, the progress of infectious disease, be it chronic or acute, is an evolutionary process, in which pathogens engage in an arms race with their human hosts. In modern times, vaccines and antibiotics have enabled mankind to skew the outcome of these contests. However, these bulwarks against contagion are being steadily eroded. Mutation and natural selection, coupled with the rapid generation times and immense pathogen population sizes, appear to provide pathogens a decisive advantage in the evolutionary contest. To regain the upper hand we must better understand the evolutionary process itself, to aid in the development of novel classes of antimicrobials and devise therapeutic strategies that take into account how these weapons work and how pathogens adaptively evolve to subvert them. However, until recently, we have been stymied in our efforts to gain a deep understanding of the adaptive process, because adaptive mutations are rare. My lab has developed a lineage tracking system that uses high throughput sequencing to allows us to follow the evolutionary process in almost real time. We are able to track the evolutionary process, readily isolate thousands of adaptive lineages, remeasure fitness of those lineages across many environments, and cheaply whole genome sequence hundreds to thousands of such mutants. I propose an ambitious, integrated program that will take advantage of this lineage tracking system. First, we will determine how the environment in which a population is evolving – and the ploidy of that population – controls which mutations are selected and the distribution of their fitness effects. Next, we will identify how mutations selected in one environment trade-off in others and establish why they do so mechanistically. Lastly, we will investigate epistasis between adaptive mutations, systematically determining the degree to which the sign and magnitude of gene interactions depend on their environmental context. To achieve these goals, we will evolve both haploid and diploid populations of Saccharomyces cerevisiae under a rationally designed set of experimental conditions, isolate hundreds of adaptive lineages from each of these evolutions, then remeasure the fitness of these adaptive clones under each of the other conditions. This experimental program will enable us to describe the “joint distribution of fitness effects”, a comprehensive picture of a genome’s adaptive possibilities under one condition, the evolutionary constraints on those possibilities others, and the mechanistic connection between those opportunities and constraints, all viewed through the lenses of ploidy and epistasis. Executing this program will provide unprecedented insight the adaptive process under alternative forms of selection and genome structure. Comparative analysis of these mutants will shed light on the underlying genetic circuitry that allows certain evolutionary trajectories to be followed but prevents others. Armed with this deeper understanding of the adaptive process, we will better be able to predict evolutionary futures given knowledge of a genomic present, and maintain the upper hand in our battle with chronic infectious disease.