Our broader aims include identifying genes harboring functional variation that contributes to variation in critical saprophytic and pathogenic fitness traits within Fusarium graminearum (Fg) populations to provide targets for pathogen management and control, and toxin reduction. Specific goals include performing genome-wide association studies (GWAS) to find the genetic basis of these pathogen traits by scanning tag single nucleotide polymorphisms (SNPs) throughout the Fg genome generated by genotyping-by-sequencing (GBS). We are collecting trait data in laboratory experiments as well as more laborious greenhouse head inoculation experiments. We have genotyped nearly 600 Fg isolates from several geographical regions in the Americas, including the Upper Midwest, New York, and Louisiana in the U.S. as well as Uruguay. These samples include isolates from the 3-ADON, 15-ADON, NX-2, and NIV toxin chemotypes. To make this work feasible, we have focused on a subset of ~150 of our isolates for phenotyping and subsequent GWAS analyses. In this subset, we have attempted to preserve the diversity of the larger sample and avoid choosing genetically similar isolates. So far, these isolates have been phenotyped for the saprophytic traits of ascospore discharge rate and mycelial growth rate at three temperatures. We screened for statistical associations between the traits and SNPs, implementing a mixed linear model that accounts for the known population structure of Fg populations as well as cryptic relationships between isolates from the same populations. While our GBS markers provide genotypes at tens of thousands of SNPs densely distributed throughout the Fg genome, most SNPs are missing some genotype data. We performed imputation to infer the allele state at missing genotypes, then filtered the SNPs to exclude low frequency variants for which power to detect a robust association is low. This left us with ~6,000 SNPs for the GWAS scan. Due to the correction for strong population structure in our diverse sample, the significance of our top associations remains moderate. For ascospore discharge, we identify a handful of strong candidate loci where the model predicts about half will be true positives. Acknowledgement and Disclaimer: This material is based upon work supported by the U.S. Department of Agriculture, under Agreement Nos. 59-0206-1-113 and 59-0206-6-002. This is a cooperative project with the U.S. Wheat & Barley Scab Initiative. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the authors and do not necessarily reflect the view of the U.S. Department of Agriculture.