A component of the CFANS Agroinformatics Initiative, SBC scientists and Minnesota Supercomputing Institute partners are developing informatic approaches to visualize and interpret evolutionary patterns of plant disease resistance genes among species comprising two important plant families: the Rosaceae (apple, pear, peach, plum, strawberry and rose) and the Solanaceae (potato, tomato, eggplant, pepper and tobacco). The data analysis tools being developed allow the automated mining of whole genome sequences to discover sets of genes likely involved in pathogen detection, assignment of these genes into an innovative phylogenetic frameworks to reveal patterns of divergence and adaptation across species, and interpretation of evolutionary patterns to discover gene lineages important for crop improvement. Paired with research approaches to sequence disease resistance genes from genebank collections of crop wild relatives, the informatics frameworks will allow efficient use of plant genetic resources to enhance crop disease resistance, improve food security, and reduce chemical inputs for crop production. Specific targets for crop improvement include apple scab, rose black spot, and potato late blight. This research is supported by the MnDRIVE Global Food Ventures.