Genome-wide association studies (GWAS) have developed into a powerful and ubiquitous tool for the investigation of complex traits. In large part, this was fueled by advances in genomic technology, enabling us to examine genome-wide genetic variants across diverse genetic materials. The development of the mixed model framework for GWAS dramatically reduced the number of false positives compared with naïve methods. Building on this foundation, many methods have since been developed to increase computational speed or improve statistical power in GWAS. These methods have allowed the detection of genomic variants associated with either traditional agronomic phenotypes or biochemical and molecular phenotypes. In turn, these associations enable applications in gene cloning and in accelerated crop breeding through marker assisted selection or genetic engineering. Current topics of investigation include rare-variant analysis, synthetic associations, optimizing the choice of GWAS model, and utilizing GWAS results to advance knowledge of biological processes. Ongoing research in these areas will facilitate further advances in GWAS methods and their applications.