A major goal of genetics and evolutionary biology is to understand how changes in genotype affect phenotype. Genetic variants affecting fitness are especially informative for investigating evolution, since natural selection acts exclusively on these variants. By identifying specific variants that influence fitness, we can begin to understand the molecular mechanisms driving the incredible adaptations of all organisms to their respective environments. We recently developed an approach that allows us to edit genomes with unprecedented efficiency (~100%) and throughput. In our initial screen, we measured the fitness effects of 16,000 natural genetic variants differing between two strains of Saccharomyces cerevisiae. In this pilot experiment, we measured the effects of each variant in isolation, in a single condition. We found that nearly all strong fitness effects were from promoter variants, rather than protein-coding regions, and these were especially enriched at transcription factor binding sites. Here we propose to utilize this powerful system to investigate two types of interactions of fundamental importance: gene-by-environment (GxE) in Aim 1, and gene-by-gene (GxG, or epistasis) in Aim 2. Understanding the context-dependence of fitness effects will reveal key insights into the evolutionary process that would be unapproachable without our high-throughput precision genome editing technology. !

Public Health Relevance

The subject of this project?the fitness effects of natural genetic variants?is of great importance to biomedicine. The basic lessons we learn from yeast will likely apply broadly, including in human diseases, where GxE interactions and epistasis both play a key role. Therefore, investigating these interactions in a simpler model organism holds great promise for advancing our understanding of how genotype and environment determine phenotype in any species.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
1R01GM134228-01
Application #
9800753
Study Section
Genetic Variation and Evolution Study Section (GVE)
Program Officer
Janes, Daniel E
Project Start
2019-08-01
Project End
2023-05-31
Budget Start
2019-08-01
Budget End
2020-05-31
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Stanford University
Department
Biology
Type
Schools of Arts and Sciences
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305