Professor Yang Da

CFANS Animal Science
College of Food, Ag & Nat Res Sci
Twin Cities
Project Title: 
Genomic Selection Using Functional and Structural Genomic Information

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 computer package to implement these methods, and obtained encouraging results for predicting phenotypes in humans and swine. However, this methodology requires large-capacity computational resources due to the need to compute large matrices, iterative solutions, and extensive validation studies (each consists of a number of repeats). The researchers are continuing with this work on an expanded scale by adding new and larger datasets.

This research was featured on the MSI website in September 2016: Panda Genomics.

Project Investigators

Cheng Bian
Professor Yang Da
John Garbe
Zuoxiang Liang
Dzianis Prakapenka
 
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