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.

该项目的目标是通过分析建立在各种关键特征中的各种模型，对具有丰富选择和重组的大型种群的进化动力学进行定量理解。将在以下几种情况下研究在一个谱系中积累的多个有益突变与将这些突变分离并聚集在一起的重组之间的相互作用：重配，个体之间的染色体交换，而不发生流感病毒的重组；转移：基因组小片段的转移，如细菌间的基因横向转移；无性交配：在无性进化的种群间的偶然交配，如在酵母中；以及染色体线性结构中产生的各种连锁度谱的近似。突变之间的上位相互作用以及变化的连锁导致了个体基因选择和基因组选择之间的平衡：这将在各种相互作用模型中进行探讨，这些模型关注的是罕见的、异常良好的突变组合的统计特性，这些突变组合在未来的进化中占主导地位。上位的模型将被告知，并告知，在实验室进化的出芽酵母进行的合作者的实验。无性进化种群内部或之间的交配已经被“条形码”，应该提供关于父母及其后代健康的关键信息，并且该理论的发展将使对性的好处的预测能够在未来的实验中得到验证。除了所有个体直接竞争的混合良好的种群之外，还将研究在实验室中可以实现的其他形式的竞争（例如选择种群中最好的一半）。在更长的时间尺度上，还将研究空间结构和局部竞争与混合之间的相互作用，重点是重组对进化速度和多样性动态的影响。将进一步发展与若干小组的合作，以酵母或细菌进行实验室进化实验，以获得建模所需的统计信息，并提出和计划未来的实验。对细菌种群的深度测序数据的分析将与合作者一起进行，以推断进化史的各个方面，包括重组，并为最具信息的未来采样和测序制定计划。参与的学生和博士后将从来自不同领域的几位教师的指导中受益匪浅。在研究之外，PI正在为定量科学家和生物学家开发新的进化课程：课堂笔记将在互联网上提供。PI还将进一步参与对公众的进化论教育，包括进化论未来的挑战和成功。