DISSERTATION RESEARCH: Towards a biologically relevant interpretation of the genetic covariance matrix: A theoretical and experimental exploration of the breeder's equation

论文研究：对遗传协方差矩阵进行生物学相关的解释：对育种方程的理论和实验探索

• 批准号: 0909760
• 负责人: Charles Goodnight
• 金额: $ 1.17万
• 依托单位: University of Vermont & State Agricultural College
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-06-01 至 2010-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0909760&HistoricalAwards=false
• 关键词: DISSERTATION; RESEARCH; Towards; biologically; relevant

A major theoretical challenge is determining how natural selection acting within populations translates into the patterns of evolution seen at a larger scale. Specifically, there is no general understanding of how interactions among genes change as a result of processes such as natural selection and mutation. Developing the necessary theory and statistical tools to determine how these interactions shape evolution is crucial for predicting a population's capacity to adapt to climate change, and the ability of exotic species to invade new environments. This study develops a new statistical method (the "selection skewers" analysis) that identifies changes in the relationships among genetic components of traits that would significantly alter the predicted evolution of a population. The performance of this new statistical method will be compared to previous methods. In addition, using laboratory populations of red flour beetles (Tribolium castaneum) the method will be used to empirically determine when interactions among genes are stable over time, and thus when evolutionary change due to selection can be predicted accurately.The results will not only provide a needed statistical and conceptual framework for basic studies of evolutionary change, but will enable future studies examining the capacity for natural populations to adapt to climate change and the ability of exotic species to invade new environments. In addition, women and minority students will be trained in the field of quantitative genetics, an area where these groups are still underrepresented. The computer program to implement the selection skewers method will be made freely available on the web.

一个主要的理论挑战是确定自然选择如何在种群内转化为更大规模的进化模式。具体来说，对于基因之间的相互作用是如何在自然选择和突变等过程中发生变化的，目前还没有普遍的理解。发展必要的理论和统计工具来确定这些相互作用如何影响进化，对于预测种群适应气候变化的能力以及外来物种入侵新环境的能力至关重要。这项研究开发了一种新的统计方法（“选择串”分析），该方法确定了性状遗传成分之间关系的变化，这些变化将显著改变预测的种群进化。这种新的统计方法的性能将与以前的方法进行比较。此外，使用红粉甲虫（Tribolium castaneum）的实验室种群，该方法将用于经验确定基因之间的相互作用何时随时间稳定，从而何时可以准确预测由于选择而导致的进化变化。这些结果不仅为进化变化的基础研究提供了必要的统计和概念框架，而且将使未来的研究能够检查自然种群适应气候变化的能力和外来物种入侵新环境的能力。此外，妇女和少数民族学生将接受数量遗传学领域的培训，这些群体在这一领域的代表性仍然不足。实施选择串法的计算机程序将在网上免费提供。