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

该奖项全部或部分由2021年美国救援计划法案（公法117-2）资助。这项研究将促进我们对基因在染色体对之间洗牌（重组）的速率进化的理解。植物和动物的繁殖需要重组。不同物种和种群之间的染色体畸变率不同，甚至在个体的染色体之间和染色体内部也不同。重组率影响突变的命运和适应过程，但重组率变化的原因和后果知之甚少。该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和真实的世界的界面的理解，并提高数学素养。这将通过实施合并的本科-研究生课程的数学建模在密西西比州立大学和数学建模模块的高中生物课堂的发展与密西西比学校数学和科学的合作伙伴关系。该研究将开发一个理论框架，允许明确测试现有的假设，通过生成预测，适用于数据集，描述重组率的种群内和种群间变异。这种新方法是建立在越来越多的证据表明，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性状。这弥合了理论与现实世界中不断增长的基因组数据之间的差距。开发和实施所需的计算工具来模拟重组率的进化作为一种数量性状，以响应直接和间接的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，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

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.