Recombination, Genetic Interactions, and Observable Evolutionary Dynamics

重组、遗传相互作用和可观察的进化动力学

• 批准号: 1305433
• 负责人: Daniel Fisher
• 金额: $ 42万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1305433&HistoricalAwards=false
• 关键词: Recombination; Genetic; Interactions; Observable; Evolutionary

The goal of this project is to develop quantitative understanding of the evolutionary dynamics of large populations with abundant selection and recombination by analyzing a variety of models that build in various of the key features. The interplay between multiple beneficial mutations accumulating in one lineage and recombination that breaks apart and brings together collections of such mutations will be studied in several situations: re-assortment, the exchange of chromosomes between individuals without recombination as occurs for influenza viruses; transfer of small segments of a genome as in lateral gene transfer between bacteria; occasional mating between otherwise asexually evolving populations, as in yeast; and various approximations of the spectrum of degrees of linkage that arise from the linear structure of chromosomes. Epistatic interactions between mutations together with changing linkage leads to a balance between selection on individual genes and selection on genomes: this will be explored for various models of the interactions focusing on the statistical properties of the rare, anomalously good combinations of mutations that dominate the future evolution. The models of epistasis will be informed by, and inform, experiments on laboratory evolution of budding yeast carried out by collaborators. Mating within or between asexually evolved populations that have been "barcoded", should provide crucial information about the fitness of parents and their offspring, and the theory developed will enable predictions about the benefits of sex that can be tested in future experiments. Going beyond well-mixed populations in which all individuals compete directly, other forms of competition that could be realized in the laboratory (such as selection of the best half of a population) will be studied. Spatial structure and the interplay between local competition and mixing on longer time scales will also be investigated, focusing on the effects of recombination on rates of evolution and dynamics of diversity. Collaborations with several groups carrying out laboratory evolution experiments with yeast or bacteria will be further developed to obtain statistical information needed for the modeling, and to propose and plan future experiments. Analysis of deep sequencing data of bacterial populations will be carried out with collaborators to infer aspects of the evolutionary history, including recombination, and to develop plans for the most informative future sampling and sequencing. The students and postdocs involved will greatly benefit from mentoring by several faculty from different fields. Beyond the research, the PI is developing new courses on evolution for quantitative scientists and biologists: lecture notes will be made available on the internet. The PI will also become further involved in educating the general public about evolution, including the future challenges, as well as the successes, of evolutionary theory.

该项目的目的是通过分析以各种关键特征构建的各种模型来对大量人群的进化动态进行定量理解。在一个谱系中积累的多个有益突变与重组分裂并汇集了这种突变的集合之间的相互作用将在几种情况下进行研究：重新分类，在没有重新组合的个体之间的染色体交换（用于流感病毒的情况下）；基因组的小片段的转移，如细菌之间的横向基因转移；如酵母中，偶尔的交配是在其他无性不断发展的种群之间；以及由染色体线性结构产生的链接度光谱的各种近似值。突变之间的上毒相互作用以及不断变化的链接可以在单个基因的选择与基因组的选择之间保持平衡：对于重点介绍稀有的统计特性的各种相互作用的模型，将探索这一点，这些突变的统计特性异常良好，占主导地位的突变组合进化。上毒模型将由合作者进行的实验室进化的实验性进化来告知并告知实验。在已被“条形码”的人群中或无性发展的人群之间或之间的交配应提供有关父母及其后代适应性的关键信息，而开发的理论将有助于对可以在未来实验中测试的性别的好处进行预测。将研究所有个人直接竞争的混杂人群，还可以研究实验室中可以实现的其他形式的竞争（例如选择最佳人群的选择）。还将研究空间结构以及本地竞争与较长时间尺度上的混合之间的相互作用，重点是重组对进化速率和多样性动态的影响。 将进一步开发与使用酵母或细菌进行实验室进化实验的几个小组的合作，以获取建模所需的统计信息，并提出和计划未来的实验。对细菌种群的深层测序数据的分析将与合作者进行，以推断进化史的各个方面，包括重组，并制定计划，以确定未来最有用的未来采样和测序。参与的学生和博士后将从不同领域的几个教师指导中受益匪浅。除了研究之外，PI还为定量科学家和生物学家开发了有关进化的新课程：将在互联网上提供讲座笔记。 PI还将进一步参与有关进化的教育，包括未来的挑战以及进化论的成功。