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 environments. We recently developed an approach that allows us to edit genomes with unprecedented efficiency (~100%) and throughput, and precisely measure each edit?s effect on fitness. 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 concepts of fundamental importance: the role of selection in shaping genetic variation in Aim 1, and gene-by-environment (GxE) interactions in Aim 2. This project 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?mapping genotype to phenotype?is of great importance to biomedicine. For example, mutations are a major source of human disease, and understanding how genetic variants impact fitness in a model organism may shed light on these relationships in humans as well.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
2R01GM097171-09
Application #
9885245
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Janes, Daniel E
Project Start
2012-02-05
Project End
2025-07-31
Budget Start
2020-08-01
Budget End
2021-07-31
Support Year
9
Fiscal Year
2020
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
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Artieri, Carlo G; Fraser, Hunter B (2014) Transcript length mediates developmental timing of gene expression across Drosophila. Mol Biol Evol 31:2879-89

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