Jeff Endelman, associate professor and extension specialist in the Department of Plant and Agroecosystem Sciences, received USDA-NIFA funding for his project Partnership: Optimization of mate allocation with genomic identity-by-descent probabilities through AFRI’s Plant Breeding for Agricultural Production program. It was among 16 projects sharing $8.6 million.

Project summary (from CRIS website): The development of new plant varieties through breeding is a powerful approach to increasing both the quantity and quality of food. Plant breeders are increasingly adopting genomic selection methods, which use DNA sequence and historical trait data to make statistical predictions. Because of its rapid breeding cycle, one of the potential pitfalls with genomic selection is an accelerated loss of genetic diversity. For specialty and forage crops, this loss of diversity can be controlled by limiting the inbreeding rate. Experience from decades of animal breeding and plant breeding simulations indicates 1% inbreeding is optimal.This project will develop new methods and software to overcome the main technical obstacle to realizing this selection methodology in our target crops of potato and blueberry. Because these crops contain four sets of chromosomes, instead of two sets like animals and many plants, the calculation of genomic inbreeding from genetic marker data is more complicated. Computer simulations will be used to validate our software and predict its impact on genetic improvement and diversity after 20 years. The new tools will be adopted in our breeding programs at the Universities of Wisconsin and Florida, and we expect other plant breeding programs will follow our lead.