Project Summary The fungal pathogen Cryptococcus neoformans is estimated to cause disease in more than 1,000,000 people worldwide every year, resulting in greater than 600,000 deaths. However, not all Cryptococcus isolates cause lethal infections; some are relatively benign while others are hypervir- ulent. Differences in pathogenicity are often correlated with variation in speci?c morphological and physiological features such as the ability to grow at high temperatures, the size of the pro- tective polysaccharide capsule surrounding the yeast cell, or resistance to antifungal drugs. In order to develop better ways to prevent and treat cryptococcal disease we need to understand the underlying genetic differences that lead to changes in virulence and virulence-related traits. We also need to understand the frequency and distribution of these genetic differences in different parts of the world. To tackle these problems, the proposed research will use a combination of experimental and statistical approaches to dissect the causal genetic basis of variation in virulence and virulence- related traits. In Aim 1 we will employ a statistical technique called Quantitative Trait Locus (QTL) mapping, that exploits genotypic and phenotypic differences among offspring derived from genetic crosses to identify regions of the genome (loci) and DNA changes (alleles) that con- tribute to differences in virulence traits. We will validate the contributions of the loci identi?ed in this manner using gene replacements and related techniques. In Aim 2 we will subject ge- netically diverse populations of Cryptococcus to selection in animal hosts. Following selection, pooled whole genome sequencing will be used to identify loci and alleles that are favored during infection. This technique provides an unbiased approach for discovering loci that contribute to virulence, and will both complement and extend the results of Aim 1. In Aim 3 we will frame our ?ndings in the context of natural populations of Cryptococcus by studying the frequency and geo- graphic distributions of virulence alleles identi?ed in Aims 1 and 2. This aim will employ a large, global sample of Cryptococcus strains isolated from both clinical settings and the natural environ- ment. This information will be used to carry out Genome-Wide Association (GWAS) mapping of virulence traits and to identify regions of the world where there are higher frequencies of virulent genotypes or where there is potential for increased virulence through recombination.