College of Food, Ag & Nat Res Sci
Twin Cities
Genomic selection has been rapidly accepted as a routine application in animal and plant breeding and has been applied to predict human phenotypes. However, current methods for genomic selection mostly use structural genomic information represented by the analysis of single SNP markers covering the genome, leaving functional genomic information largely unused. These researchers have developed multi-allelic haplotype methods to integrate functional and structural genomic information for genomic selection, developed a computing pipeline to implement these methods, and obtained encouraging results. This methodology requires large-capacity computational resources due to the need to compute large matrices, iterative solutions, and extensive validation studies that each consist of a number of repeats. The researchers are continuing with this work with more complicated models.
This group's research was featured on the MSI website in September 2016: Panda Genomics.