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. Genomewide 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.