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

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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.