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

职业：整合理论

基本信息

批准号：
2143063
负责人：
Amy Dapper
金额：
$ 74.06万
依托单位：
Mississippi State University
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2022
资助国家：
美国
起止时间：
2022-06-01 至 2027-05-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2143063&HistoricalAwards=false
关键词：
CAREER Integrating Theory &amp Data

项目摘要

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.

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。这项研究将增进我们对基因在染色体对之间改组（重组）速率演变的理解。植物和动物的繁殖需要重组。重组率在物种和种群之间存在差异，甚至在个体染色体之间和内部也可能存在差异。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却知之甚少。该项目将推进有关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界面的理解，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本科生与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。该框架允许通过生成适用于描述群体内和群体间重组率变化的数据集的预测来清晰地测试现有假设。这种新颖的方法是建立在越来越多的证据之上的，这些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可变特征。这弥合了理论与不断增长的现实世界基因组数据之间的差距。开发和实施模拟重组率作为响应直接和间接选择的数量性状的进化所需的计算工具，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，并通过使用评估被认为值得支持。基金会的智力价值和更广泛的影响审查标准。