One of the biggest challenges in quantitative genetics and evolutionary biology is that the phenotypic effects of genetic change differ across environments and genetic backgrounds. This makes it more difficult to identify the genetic basis of complex traits and to predict whether evolution will proceed via the same genetic changes when faced with similar selection pressures. When mutations have context-dependent effects, it can also lead to fundamental problems with reproducibility in biological research. My lab?s goal is to shed light on context- dependency by drawing insights from cell biology. We hypothesize that basic properties of cells can change the phenotypic impacts of mutation in predictable ways, and that trends exist that explain how specific types of mutations interact with specific types of environmental or genetic perturbations. In the next five years, we will quantify how the impact of genetic change on budding yeast?s growth rate is modulated by (1) other genes participating in the same regulatory network, and (2) accumulation of toxic misfolded proteins in cells. We will engineer large numbers of yeast strains that differ by single point mutations and quantify the impact of these mutations on cell growth as we systematically change the genetic background (i.e. impair each gene in the network, one at a time) or the environment (incrementally increase levels of a stress that destabilizes protein folding). This strategy ? re-measuring the impacts of many mutations as we slowly and systematically perturb systems ? gives us power to distinguish consistent trends that describe how the impact of mutations depends on context. It feasible and cost-effective to measure the impact of thousands of mutations across hundreds of systematic perturbations due to recent advances in yeast genetics (e.g. modifications to the CRISPR system and DNA barcoding approaches). The trends describing how particular types of mutations respond to particular types of perturbations will allow us to make, and to test, predictions about (1) how the impacts of untested mutations will change depending on context, and (2) ranges of conditions in which laboratory evolution experiments will proceed via similar genetic changes. Overall, this research direction will result in a mechanistic and quantitative understanding of one of biology?s most challenging questions: how the impacts of mutation depend on context.
The effects of genetic change often depend on environment and interactions with other genes, making it difficult to identify which genetic variants contribute to complex human diseases or allow infectious populations to invade human hosts. A mechanistic understanding of why mutations have context-dependent effects would improve predictions of phenotype from genotype. This proposal uses novel, high-throughput technologies accessible in the model eukaryotic cell, Saccharomyces cerevisiae, to investigate the basic cellular properties that modulate the context-dependent impacts of genetic variation.
