Della Coletta, Rafael2023-05-122023-05-122023-03https://hdl.handle.net/11299/254128University of Minnesota Ph.D. dissertation. March 2023. Major: Plant and Microbial Biology. Advisor: Candice Hirsch. 1 computer file (PDF); x, 145 pages.Climate change is a major threat to global food security, as current plant varieties used by farmers may not adapt to new growing environments. To mitigate this problem, plant breeders must use all available tools to speed up the development and release of new climate-adapted varieties. In this dissertation, I discuss how the recent advances in crop genomics due to improvements in sequencing technology, genome assembly methods, and computational resources are revolutionizing plant breeding. Particularly, I argue that the analysis of the complete catalog of genetic variation of a crop can provide useful information for plant breeders. I demonstrate that modeling this pan-genome information can increase the accuracy of multi- environment genomic prediction models, a tool widely used by breeders to develop new plant varieties. I also show how utilizing prior information on genetic variants associated with certain phenotypes can help simulate traits that are more realistic and relevant for breeders using digital breeding, a tool where breeders can test many different experiments before deployment in their breeding programs. Finally, I developed a new tool that identifies genetic variants associated with specific environmental factors via network analysis of common datasets available to plant breeders.engenomic predictiongenomicsmaizenetworksplant breedingsimulationThesis or Dissertation