ABSTRACT Elucidating the underlying genetic causes of the awesome phenotypic diversity observed in natural populations is a major challenge in biology. Despite the importance of understanding the genetic basis of complex traits, we currently lack complete knowledge of the relevant genetic components. Genetic variation affecting the structure and copy number of chromosomal segments is an underappreciated component of the genetic architecture. In this proposal, we seek to obtain a species-wide view of structural variation (SV) and copy number variation (CNV) and how these contribute to the phenotypic landscape of natural populations. In order to accomplish this, we will take advantage of the genetic workhorse Saccharomyces cerevisiae, for which we have recently completed whole genome resequencing of 1,011 natural isolates, plus accompanying large scale phenotyping efforts. CNVs are frequent in our strain collection and have outsize phenotypic affects in the association tests we have so far completed. We propose to: Aim 1. Apply long read sequencing to better characterize the structural variation present in these strains and generate high quality de novo assemblies. In Aim 2, we will collect quantitative strain phenotypes over a large panel of environmental conditions, with a particular emphasis on conditions that we and others have found to be particularly sensitive to CNVs. We will also include molecular traits such as mRNA and protein abundance. We will then perform association testing with the variants discovered in Aim 1 in order to determine over an entire species the degree to which SVs and CNVs contribute to trait variation. Since association methods perform poorly for rare genetic variants, we will in Aim 3 use a diallel panel where controlled crosses allow us to better survey all variation present. Finally, in Aim 4 we will complement our work on naturally occurring variation by building libraries of engineered variants. We will create large dosage series pools of segmental amplifications and deletions to better understand their consequences across multiple genetic backgrounds. Our work will result in a more complete understanding of the complexities of the genotype-phenotype connection with respect to this important but understudied class of genetic variants.