Date of Award
Doctor of Philosophy (PhD)
Predicting variation in complex traits from DNA sequence is a major public health goal, but our understanding of the genotype-to-phenotype relationship is incomplete. It will remain so unless we can adequately integrate genetic, epigenetic, and environmental information into a systems level framework. In a step towards that goal, quantitative trait mapping studies have attempted to account for environmental factors such as sex and diet, and epigenetic factors such as allelic parent-of-origin effects. Several studies used an advanced intercross of the LG/J and SM/J inbred mouse strains to unravel the genetic architecture of multiple metabolic traits. These studies found that parent-of-origin effects are surprisingly common, and that they can be mediated by the environment. This indicates that our ability to predict variation in metabolic phenotypes from genotype alone will be confounded unless environment and allelic parent-of-origin is considered. In this thesis, I explore mechanisms that could explain the prevalence of parent-of-origin effects on metabolic variation and develop tools to predict these effects more generally.I test the hypothesis that genetic effects can propagate through molecular pathways. I propose that non-imprinted genes can generate complex parent-of-origin effects on metabolic traits through interactions with imprinted genes. I employ data from mouse populations at different levels of intercrossing (F0, F1, F2, F16) of the LG/J and SM/J inbred mouse strains to test this hypothesis. Using multiple populations and incorporating genetic, genomic, and physiological data, I leverage orthogonal evidence to identify networks of genes through which parent-of-origin effects propagate. I identify a network comprising 3 imprinted and 6 non-imprinted genes that show parent-of-origin effects. This epistatic network forms a nutritional responsive pathway and the genes comprising it jointly serve cellular functions associated with growth. While epistatic interactions can explain some of the overabundance of parent-of-origin effects on metabolic traits, other biological explanations for these effects should be explored. Towards this end, I developed a generalized framework for modeling how genetic effects on expression might propagate through a network. I demonstrate that this method detects signatures of pathway structure and produces highly interpretable and actionable candidates for subsequent experimentation. This work lays the foundation for future studies of not only parent-of-origin effects but also other genetic phenomena that can extend to human studies.
Chair and Committee
Heather A. Lawson
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Macias-Velasco, Juan Francisco, "Genetic Effects Mediated Through Epistatic Networks Onto Metabolic Traits" (2021). Arts & Sciences Electronic Theses and Dissertations. 2613.