How does naturally genetic variation modulate cell biological traits relevant to human disease? Many common diseases, ranging from autism to obesity, are influenced by multiple sequence variants. Genome-wide association (GWA) studies are yielding more and more human disease risk factors, but how these genetic variants act collectively to confer disease risk remains unclear. In many cases the identified genetic variants only explain a small fraction of the disease risk heritability. Yet, the promise of personalized medicine hinges on whether we can account for the effect of an individual's genetic makeup. Due to its genetic pliability the budding yeast S. cerevisiae is an ideal model system to investigate the genomic architecture of complex traits. Prof. Leonid Kruglyak and his lab have previously used two divergent S. cerevisiae isolates to map the genetic variation mediating various phenotypes, including differences in gene expression. However, these two strains only represent a minute fraction of the S. cerevisiae species-wide genetic and phenotypic variance. I am developing a method that will allow me to generate large mapping populations of individual segregants starting from any two divergent S. cerevisiae isolates. This approach will enable me to investigate how genetic variation modulates a core MAPK signaling cascade, the HOG high osmolarity signaling pathway. The HOG MAPK cascade is highly conserved, with its human counterpart playing a key role in various cancers and its equivalents controlling virulence in several pathogenic fungi. Yet, how genetic variation influences HOG pathway activity is unknown. I will identify sequence variants that alter HOG pathway activity and will then characterize how signaling is altered specifically. The approaches I will develop to measure HOG signaling could later be applied to the study of other MAPK signaling pathways. The virulence of the pathogenic fungus Cryptococcus neoformans is governed by several complex traits. Intriguingly, HOG pathway activity is required for full virulence of this fungus. I will idntify the genetic variations that modulate virulence attributes of C. neoformans. In particular, I will characterize the genetic contributions to melanin production, capsule size and organ-specific infectivity. These analyses could be extended to additional medically relevant properties of this pathogen and will aid the study of other pathogenic fungi. Aim 1: To develop methodology to rapidly extend quantitative trait loci (QTL) mapping to additional S. cerevisiae isolates. Aim 2: T characterize the effect of genetic variation on MAPK signaling. Aim 3: To identify QTL modulating virulence of C. neoformans.