Fitness Effects of Beneficial Mutations

有益突变的健身效果

• 批准号: 10391436
• 负责人: Gavin J Sherlock
• 金额: $ 42.92万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-05-01 至 2024-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10391436
• 关键词: Acute; Antibiotics; Chronic; Communicable Diseases; Coupled; Development; Diploidy; Drug resistance; Environment; Etiology; Evolution; Future; Generations; Genetic; Genetic Epistasis; Genome; Genomics; Goals; Haploidy; High-Throughput Nucleotide Sequencing; Human; Joints; Knowledge; Light; Modernization; Mutation; Natural Selections; Outcome; Pharmacotherapy; Ploidies; Population; Population Control; Population Sizes; Process; Research; Saccharomyces cerevisiae; Structure; System; Technology; Therapeutic; Time; Vaccines; Work; antimicrobial; arms race; comparative; contagion; design; fitness; gene interaction; human disease; improved; insight; lens; mutant; novel; pathogen; prevent; programs; rational design; tumor progression; weapons; whole genome

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.

项目总结/摘要 进化过程是许多人类疾病的病因学基础。例如， 传染病，无论是慢性的还是急性的，都是一个进化的过程，在这个过程中，病原体进行军备竞赛 与人类宿主的关系在现代，疫苗和抗生素使人类能够扭曲结果， 这些比赛。然而，这些抵御危机蔓延的壁垒正在被逐步侵蚀。突变和自然 选择，加上快速的世代时间和巨大的病原体种群规模，似乎提供了 病原体在进化竞争中的决定性优势。为了重新占上风，我们必须更好地了解 进化过程本身，以帮助开发新型抗菌剂和设计治疗方法， 这些战略考虑到这些武器如何工作，以及病原体如何适应性地进化以破坏它们。 然而，直到最近，我们一直在努力深入了解适应性 因为适应性突变是罕见的。我的实验室开发了一个血统追踪系统， 通量测序允许我们在几乎真实的时间内跟踪进化过程。我们能够追踪 进化过程很容易分离出成千上万适应性谱系，重新测量这些谱系的适应性 在许多环境中，并便宜地对数百到数千个这样的突变体进行全基因组测序。 我提出了一个雄心勃勃的综合计划，将利用这个血统跟踪系统。一是 将决定一个种群进化的环境--以及该种群的倍性--如何控制 选择哪些突变以及它们的适应性效应的分布。接下来，我们将确定突变是如何 在一个环境中选择，在其他环境中权衡，并建立为什么他们这样做机械。最后，我们将 研究适应性突变之间的上位性，系统地确定该标志和 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 酿酒酵母的单倍体和二倍体群体在一组合理设计的 在实验条件下，从这些进化中分离出数百个适应性谱系，然后重新测量 这些适应性克隆在其他条件下的适应性。这项实验计划将使 我们描述了“适应性效应的联合分布”，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约束，以及机械性 这些机会和限制之间的联系，都是通过倍性和上位性的镜头来看待的。 执行这一计划将提供前所未有的洞察力的适应过程下的替代形式， 选择和基因组结构。对这些突变体的比较分析将揭示潜在的遗传学 允许某些进化轨迹被遵循但阻止其他轨迹的电路。装备了这个更深的 了解适应过程，我们将能够更好地预测进化的未来， 一个基因组的存在，并保持在我们与慢性传染病的斗争中占上风。