The application of whole-genome sequencing (WGS) to the risk assessment of foodborne pathogens is a key challenge. WGS offers the highest level of strain discrimination for more precise hazard identification, hazard characterization, and exposure assessment, leading to deeper risk characterization. Genome-wide association studies represent today powerful tools for the identification of associations between genomic elements and microbial phenotypic properties. Other cutting-edge tools include machine learning or statistical methods to characterize phenotype distribution on a phylogenetic tree. A panorama of the available methods is presented as well as the specific issues associated with the application of these methods to phenotypes of interest for risk assessment.