Measuring the statistics of pleiotropic and epistatic fitness effects of beneficial mutations during microbial adaptation across environments

测量微生物跨环境适应过程中有益突变的多效性和上位适应性效应的统计数据

• 批准号: 9396806
• 负责人: Parris Humphrey
• 金额: $ 5.71万
• 依托单位: HARVARD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-07-01 至 2019-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9396806
• 关键词: Affect; Architecture; Biological; Biological Assay; Case Study; DNA; Dependence; Drug resistance; Environment; Evolution; Experimental Models; Frequencies; Future; Genes; Genetic; Genetic Enhancement; Genetic Epistasis; Genetic Recombination; Genome; Genotype; Goals; Link; Measurement; Measures; Modeling; Mutation; Organism; Outcome; Parasites; Pattern; Phenotype; Population; Population Genetics; Process; Recombinants; Research; Role; Saccharomyces cerevisiae; Saccharomycetales; Shapes; Source; Speed; System; Testing; Theoretical Studies; Uncertainty; Variant; Work; Yeasts; asexual; base; combinatorial; fitness; gene environment interaction; gene interaction; innovation; microbial; novel; offspring; pathogen; pleiotropism; prevent; sex; statistics; trait; tumor progression

Project Summary. Two main sources of uncertainty can combine to make the outcome of adaptive evolution unpredictable: how the effects of mutations on evolutionary fitness depend on either the environment (i.e. pleiotropy) or genotype (i.e. epistasis) of the organism. By conferring substantial context dependence to the fitness effects of mutations, epistasis and pleiotropy independently and jointly impact the repeatability—and thus predictability—of evolution at phenotypic and genotypic levels. Yet we lack an empirical and conceptual basis for predicting their general importance in evolution, leaving a fundamental question unanswered: how much of the future depends on the past? The answers may be as pertinent to the causes of biological diversification and speciation as they are to predicting cancer progression, parasite host switches, and the emergence of drug resistant pathogens— adaptive processes for which predictability is greatly needed. When studied in detail, pleiotropy and epistasis reveal important facets of how the genetic architecture of organismal traits interacts with the environment to affect the outcomes of adaptation. This work moves beyond case-studies by proposing to systematically measure the distribution of fitness effects of beneficial mutations across environments, as well as how these effects change when paired with other mutations in the genome. Progress on these fronts has been impeded by practical combinatorial limits to the gene–gene and gene– environment interactions that can be assayed at once, as well as by the limited availability of study systems allowing controlled manipulation of recombination to isolate its effect on the evolution of such interactions. Using budding yeast as a model for microbial adaptation, the proposed work removes the combinatorial upper limit that has for so long prevented estimation of the statistics of epistatic and pleiotropic mutational effects, and permits an analysis of how recombination affects their role in evolution. This work uses innovative sequencing-based approaches to track the fitness of thousands of genotypes via DNA barcodes in bulk across a wide range of environments, and will reveal the statistical context in which important forms of pleiotropy (e.g. trade-offs) actually tend to arise. Additionally, this work tests how the effects, and genetic basis, of epistasis and pleiotropy evolve differently in sexual versus asexual populations, by using DNA barcode fitness tracking of thousands of recombinant offspring across multiple environments. Together, this work will provide a comprehensive study of classic but poorly measured evolutionary quantities that impact the genetic and phenotypic dynamics of adaptation and its predictability.

项目摘要。 不确定性的两个主要来源可以联合收割机结合起来，使适应性进化的结果不可预测：如何 突变对进化适应性的影响取决于环境（即多效性）或基因型 (i.e.上位性）。通过赋予突变的适应性效应实质上的上下文依赖性， 上位性和多效性独立地和共同地影响进化的可重复性，从而影响可预测性 在表型和基因型水平上。然而，我们缺乏经验和概念基础来预测他们的一般情况。 进化的重要性，留下了一个基本的问题没有回答：未来有多少取决于 过去？答案可能与生物多样性和物种形成的原因有关，因为它们是 预测癌症进展、寄生虫宿主转换和耐药病原体的出现- 适应性过程，其中的可预测性是非常需要的。 当详细研究时，多效性和上位性揭示了遗传结构的重要方面， 生物体特征与环境相互作用，影响适应的结果。这项工作超越了 案例研究，建议系统地测量有益突变的健身效果的分布 以及当与基因组中的其他突变配对时，这些效应如何变化。 基因-基因和基因-基因的实际组合限制阻碍了这些方面的进展。 环境相互作用，可以立即测定，以及有限的可用性研究系统 允许重组的受控操作以分离其对这种相互作用的进化的影响。 使用芽殖酵母作为微生物适应的模型，所提出的工作去除了组合上 长期以来一直阻碍着上位性和多效性突变效应的统计估计的限制， 并允许分析重组如何影响它们在进化中的作用。这项工作采用了创新的 基于测序的方法，通过DNA条形码批量跟踪数千种基因型的适应性， 广泛的环境，并将揭示统计背景下，重要形式的多效性（例如， 权衡）实际上倾向于出现。此外，这项工作测试了上位性的影响和遗传基础， 和多效性在有性与无性种群中的进化不同，通过使用DNA条形码健身跟踪， 在多种环境中的数千个重组后代。总之，这项工作将提供一个 对经典但测量不佳的进化量进行了全面的研究，这些进化量影响了遗传和 适应的表型动态及其可预测性。