Complex traits are inherited via the combined effects of quantitative trait loci segregating in a population. These genetic determinants may have large or small effects, and may combine in a myriad of ways. Despite a decade of work on mapping the genetic determinants of complex traits via genome-wide association studies and other methods, the field has as yet not determined an optimal approach to inferring phenotype from genotype. We propose to use yeast genetics to learn the underlying genetic architecture of a series of quantitative traits. The yeast system has superior experimental tools, conserved biology across eukaryotes, and a growing collection of diverse genome sequences on which to draw. We will first focus on loci of strong effect, i.e. """"""""Mendelian"""""""" traits. These lend themselves o easy genetic mapping and experimental confirmation via allele swap experiments. Our hypothesis is that genes with strong effect alleles will also harbor alleles of more quantitative effect across a population. This idea is akin to the """"""""rare variant"""""""" hypothesis in which low frequency strong effect alleles contribute to high disease risk. We seek to discover whether these same genes may also be of importance across the population due to lower effect alleles that may be more difficult to identify. We will pursue this project in three specific aims, each le by an expert investigator.
In Aim 1, we will explore the phenotypic diversity in natural yeast populations from the species S. cerevisiae and S. paradoxus. These species have a great deal of phenotypic and genotypic diversity that we can utilize. In particular, we will observe segregation of growth ability in the face of environmental stresses that yeasts may have experienced during their natural history.
The second aim i s to determine the genetic basis of those phenotypes that segregate as a small number of large effect loci. To map the causative loci, we will use a bulk segregant mapping method coupled with deep sequencing, followed by allele swap experiments to prove causation.
The third aim i s to test whether these same loci are important for phenotypic variation across a large panel of strains. We will amplify alleles from hundreds of genetically diverse isolates, transplant them into an isogenic background, and assay gene function via a pool-based, quantitative, competitive assay. Allele frequency will be measured using deep sequencing. This combination of methods will allow us to identify crosses in which stress tolerance traits segregate in a genetically simple manner, map the causative genes, and determine the importance of additional variants in these genes across a population. Our results will inform the understanding of the genetic basis of complex traits.
Most human diseases have a complex underlying genetic basis;however, a subset segregates as simple Mendelian traits. We will utilize the model eukaryote budding yeast to determine whether the genes whose variants are associated with genetically simple traits also harbor quantitative variation across populations. Our results could influence the study of such traits in humans.
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