The vast majority of genetic diseases are complex traits, conditioned by multiple genetic and environmental factors. Yet our understanding of the genetics underlying such traits in humans remains extremely limited, due largely to the statistical complexity of inferring the effects of allelic variants in a genetically diverse population. Novel tools for the dissection of the genetic architecture of complex traits, therefore, can be most effectively developed in model organisms, where the contribution of individual alleles can be quantitatively determined in controlled genetic backgrounds. We have previously established the yeast Saccharomyces cerevisiae as a model for complex traits by unravelling complex genetic architectures that govern quantitative phenotypes in this organism. We achieved this by pioneering approaches that have revealed crucial information about the complexity of the underlying genetics. Here we propose to advance to the next level of complex trait dissection by developing systematic, genome-wide technologies that aim to identify all of the variants underlying a complex trait in a single step. In particular, we will investigate traits involved in mitochondrial function, which are both clinically relevant and highly conserved in yeast. Our combination of genomic technologies will allow us to: 1) systematically detect, with maximal sensitivity, the majority of genetic variants (coding and non-coding) that condition these traits; 2) quantify the contributions of these variants and their interactions; and 3) evaluate the strengths and limitations of current methods for dissecting complex traits. Taken together, our research will yield fundamental insights into the genetic complexity of multifactorial traits, providing valuable lessons and establishing novel genomic tools that will facilitate the investigation of complex diseases.