Description of current research:

My focus with USDA is on developing methods to use DNA markers in public sector breeding. The ongoing declines in the costs of marker development and deployment make feasible the genotyping at high density of many, if not all, breeding lines, even for small public breeding programs. I work on statistical methods to analyze the data with the goal of improving selection decisions. At the moment, I am particularly interested in “genomic selection,” which couples the power and relevance of large plant breeding populations with high density, highly multiplexed marker technology to improve quantitative traits. Applying new statistical methods to the hundreds of thousands of detectable polymorphisms, genomic selection simultaneously estimates effects for all markers, allowing it to capture even the many small effects determining quantitative traits. Thus, genomic selection can accurately predict agronomic performance on the basis of marker data alone. We think genomic selection will dramatically change plant breeding practices in the near future. I am also interested in using association genetics within breeding. Common associations across multiple small programs can indeed leverage each program’s phenotyping efforts into more accurate estimates of marker effects. We are investigating using multi-locus marker segments, or haplotype blocks, rather than single markers, for QTL identification.