Genetic Interactions and Gene-by-Environment Interactions in Evolution

Abstract

The phenotypic effect of a mutation depends on both genetic interactions (G×G) and gene-by-environment interactions (G×E). G×G and G×E can distort the additive relationship between genotypes and phenotypes and complicate biological and biomedical studies. Understanding the patterns and mechanisms of these interactions is important for predicting evolutionary trajectories, designing plant and animal breeding strategies, detecting “missing heritability”, and guiding “personalized medicine”. In this thesis, I study how G×G and G×E affect mutational effects, including developing new methods and new models. Recent advancements in high-throughput DNA sequencing and high-throughput phenotyping provide powerful tools to study the relationships among genotypes, phenotypes, and the environment at unprecedented scales. Therefore, I take advantage of several published large datasets in my study, each containing hundreds to thousands of different genotypes of model organisms and their corresponding phenotypes in tens of environments. In Chapter 2, I report some general patterns of G×E and demonstrate the importance of considering potential environmental variations in mapping quantitative trait loci. In Chapter 3, I report how the environment affects diminishing returns epistasis and propose a modular life model to explain the patterns of diminishing returns. In Chapter 4, I propose and demonstrate that genetic dominance is a special case of diminishing returns epistasis. In Chapter 5, I report how and why the relationship between growth rate (r) and carrying capacity (K) in density-dependent population growth varies across environments. In Chapter 6, I demonstrate the existence of an intermediate optimal mating distance for hybrid performance in three model organisms. Overall, I find that large genomic and phenomic data are useful resources to address classical genetic questions, such as the origin of dominance (Chapter 4), the relationship between r and K (Chapter 5), and presence of an optimal mating distance (Chapter 6). The environment is a key player in the phenotypic effects of mutations, but it is also a high-dimension complex system that is hard to quantify. In this thesis, I define environment quality (Q) as the average fitness of many different genotypes measured in the environment. I demonstrate that Q is useful in studying how the environment affects additive (Chapter 3), interactive (Chapters 3 and 4), and pleiotropic mutational effects (Chapter 5). Many classical theories and models were developed based on observations made in a single environment, and they are often insufficient to explain across-environment observations. Studying across-environment effects provides valuable information for testing old models and for designing new models when old models fail. I conclude that studying G×G and G×E shed light on underlying biological mechanisms.PHDEcology and Evolutionary BiologyUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/144160/1/xinzhuw_1.pd