Toward Genomic Selection in Blueberry

Blueberries (Vaccinium sp.) are an economically important small fruit for the U.S., with 280.8 million pounds harvested for fresh production ($781.8 million) in 2012. U.S. production has increased an average of 20% every two years since 2008, while acreage has increased by nearly 75% between 2005 and 2012. These figures are expected to be maintained in the future as expansion moves into many non-traditional production areas. All cultivated blueberry species are autopolyploid and currently blueberry breeding programs rely on phenotypic recurrent selection, with cultivar development times often over 15 years. Although molecular breeding techniques are just now being adopted in blueberry, further advances could be made with the application of genome-wide selection (GWS). GWS has revolutionized diploid animal and plant breeding, with the potential to decrease the development time of new improved genotypes by up to 50%. However, the theoretical knowledge and computational infrastructure to account for double reduction and dosage in outbred autopolyploid populations remains a challenge to implementation of GWS. Our objective is to implement GWS in autotetraploid species, using blueberry as a model. We have created an R package that can calculate the numerator relationship matrix accounting for double reduction (k) when pedigree information is used and that accounts for dosage when markers are used. We have tested different k coefficients using the package in the entire University of Florida blueberry breeding pedigree that dates to 1909. Results regarding the use of the package and the next steps toward implementing GWS will be discussed.