CAREER: Integrating Theory & Data to Uncover the Evolutionary Advantages of Recombination

该奖项的全部或部分资金来自《2021年美国救援计划法案》(公法117-2)。这项研究将促进我们对基因在染色体对之间打乱(重组)的进化的理解。动植物的繁殖需要重组。重组率因物种和种群的不同而不同，甚至可能在个体的染色体之间和内部有所不同。重组率影响突变的命运和适应过程，但重组率变异的原因和后果尚不清楚。这个项目将推进有利于不同重组率的条件的进化理论。这项工作还将增加学生对理论与现实世界的接口的理解，并提高数学素养。这将通过在密西西比州立大学实施数学建模的本科生和研究生相结合的课程，以及与密西西比数学与科学学院合作开发高中生物课堂的数学建模模块来实现。这项研究将开发一个理论框架，通过生成适用于描述重组率的种群内和种群间变化的数据集的预测，允许对现有假设进行明确的测试。这一新方法是建立在越来越多的证据基础上的，即重组的遗传结构是复杂的。该模型将重组率视为反映复杂性的连续变量特征。这在理论和不断增长的现实世界基因组数据之间架起了一座桥梁。开发和实施所需的计算工具来模拟重组率的进化，以响应直接和间接选择，将是理解基因组进化的重要一步。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).This research will advance our understanding of the evolution of the rates at which genes are shuffled among pairs of chromosomes (recombination). Reproduction in plants and animals requires recombination. Recombination rates differ between species and populations, and can even vary among and within the chromosomes of an individual. The rate of recombination influences the fate of mutations and the process of adaptation, but the causes and consequences of recombination rate variation are poorly understood. This project will advance evolutionary theory about the conditions which favor different recombination rates. The work will also increase student understanding of the interface of theory and the real world and increase mathematical literacy. This will be accomplished through the implementation of a combined undergraduate-graduate course in mathematical modeling at Mississippi State University and the development of mathematical modeling modules for high school biology classrooms in partnership with the Mississippi School for Mathematics and Science.The research will develop a theoretical framework that allows clear testing of existing hypotheses by generating predictions that are applicable to datasets that describe intra- and interpopulation variation in recombination rate. This novel approach is founded on a growing body of evidence that the genetic architecture of recombination is complex. This model will treat recombination rate as a continuously variable trait reflecting that complexity. This bridges a gap between theory and the growing body of real-world genomic data. The development and implementation of computational tools needed to simulate the evolution of recombination rate as a quantitative trait in response to direct and indirect selection will be a major step in understanding genome evolutionThis award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.