The Genetic Architecture of Complex Traits in Yeast

Abstract

Many phenotypes of biological, medical, and agricultural relevance display continuous variation and complex genetic inheritance. Mapping the genetic basis of traits that are influenced by environmental factors and multiple genetic loci has been notoriously difficult. Controlled crosses in model organisms can help elucidate general principles that govern the genetic basis of trait variation.

In this thesis, we use a cross between two strains of the yeast Saccharomyces cerevisiae to accurately estimate different sources of heritable variation for 46 quantitative traits and to detect underlying loci with high statistical power. We find that the detected loci explain nearly the entire additive contribution to heritable variation for the traits studied. We also show that the contribution to heritability of gene-gene interactions varies among traits, from near zero to approximately 50%. Detected two-locus interactions explain only a minority of this contribution.

Next, we describe theoretical work demonstrating the limits of association mapping in yeast, and various crossing strategies to overcome these limits. We demonstrate that the joint analysis of 17 crosses, covering the yeast species diversity, is highly powered to detect genetic variants underlying phenotypic variation and will provide gene-level or higher mapping resolution for all but the smallest effect QTL. Finally, we present a quantitative comparison of short read based RNA quantification to 2-channel expression microarrays and quantitative PCR assays. We characterize the weaknesses of short read RNA quantification for low-abundance transcripts and the prospects or using RNA-seq to quantify transcript abundance in large yeast segregant populations.