Dissertation/Thesis Abstract

Evolution of Synergistic Epistasis Underlying Complex Disease in Biologically-based Models
by Gervin, Joshua Lawrence, Ph.D., University of California, Irvine, 2017, 345; 10287816
Abstract (Summary)

The origins of complex, heritable traits -- such as familial risk for cancer, diabetes, and neuropsychiatric illness -- are poorly understood. For the past decade, genome-wide association studies (GWAS) have been used to search for sites of genetic variation associated with such traits, but the alleles thus discovered account, according to the statistical methods used, for only a small fraction of the probability of displaying the trait. One hypotheses put forth to explain this apparent failure concerns the nature of genetic interaction: If genes often interact synergistically, so that small-effect variants have a much greater than additive effect when combined, such genes will be difficult to discover by GWAS. This hypothesis is often rejected based on empirical evidence that natural genetic variants mostly tend to interact additively. Here I provide evidence that, for deleterious traits, the force of natural selection can alter this situation dramatically, producing inadvertent selection for synergistic interactions among small-effect alleles. To first demonstrate this, I created a variety of dynamical models of real and fictitious biological processes that are required to perform a series of tasks and, to mimic one likely effect of natural selection, optimized their parameters so that their outputs would be more robust to the values of their parameters (considered one at a time). In models of suitable complexity, I observed that optimization drove most parameter combinations (pairs, triples, etc.) toward additive interaction, but invariably drove a subset toward very high synergy (epistasis). Next, I used a simple model of non-additive gene-gene interaction to simulate populations evolving in the presence of “phenotypic noise” (i.e., intrinsic and environmental variability in the relationship between phenotype and genotype) to show the occurrence of common diseases (i.e., unfit phenotypes with frequencies on the order of 1%) can, under the right circumstances, be expected to be driven primarily by synergistic epistatic interactions. These results raise the possibility that the existence of complex, heritable disease traits with synergistic or combinatorial genetic origins may be an inevitable consequence of evolution.

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Indexing (document details)
Advisor: Lander, Arthur D.
Commitee: Bardwell, Lee, Calof, Anne, Long, Anthony D., Yu, Zhaoxia
School: University of California, Irvine
Department: Biological Sciences
School Location: United States -- California
Source: DAI-B 79/01(E), Dissertation Abstracts International
Source Type: DISSERTATION
Subjects: Biology, Genetics
Keywords: Disease, Epistasis, Evolution, Gwas, Models, Robustness
Publication Number: 10287816
ISBN: 978-0-355-22959-2
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