Mutation provides the raw material for all genetic variation and evolution. How those mutations affect the fitness of an individual and the distribution of those fitness effects, known as the fitness landscape, is of fundamental importance for understanding almost all evolutionary processes. This project will explore the fitness landscapes of a yeast gene. The data will offer unprecedented details of the fitness effects of mutations, including properties of genetic interaction among mutations, and provide an invaluable opportunity to test many theoretical models. These models are applied to many important phenomena such as the basis of genetic diseases, the origins of multidrug resistance in pathogens, and the domestication of animals and plants.
This research explores the fitness landscape of the tRNA-ARG gene in the yeast Saccharomyces cerevisiae and studies epistasis between point mutations in the gene. The study will generate approximately 100,000 yeast strains, each carrying, at its native genomic location, a variant of the tRNA gene that has on average two single nucleotide changes compared to the wild-type. The fitness values of approximately 20,000 genotypes will be measured en masse by a sensitive high-throughput method, and epistasis will be estimated for a large number of mutation pairs. This study offers a rare opportunity to understand the biophysical basis of epistasis and fitness effects of mutations, because tRNA function is largely determined by its secondary structure, which can be computationally predicted with high accuracy. Further, fitness landscapes and epistasis will be quantified under multiple conditions to understand genotype by environment interactions. In addition, the expressions of different tRNA variants will be probed to better understand how the internal promoter of the tRNA works and how fitness is affected by the expression level of the tRNA.
