Genomic Selection: A New Approach in Blueberry Breeding

Worldwide blueberry production is rapidly growing due to both a rise in consumer demand and an expansion in available production area resulting from new low-chill cultivars. Currently, the University of Florida blueberry breeding program uses phenotypic recurrent selection to create new cultivars. This method focuses on overall population improvement by increasing the frequency of favorable alleles, and typically takes 10 to 15 years to release a new cultivar. To better meet the needs of an expanding industry the selection should be more efficient and the breeding cycle needs to be decreased. Genome-wide selection (GWS) has been used with great success in animal, crop, and forestry breeding programs for efficient and timely development of improved products. GWS is accomplished using best linear unbiased prediction (BLUP) to estimate breeding values and heritability of economically important traits and whole genome marker scans to develop prediction models for the traits based on genotype. One limitation of GWS in blueberries is that it is an autotetraploid, and BLUP assumes disomic inheritance. The objective of this study was to compare BLUP models assuming disomic inheritance to those of tetrasomic inheritance. To do this, a training population consisting of 2000 pedigree-linked seedlings were evaluated in 2014–15 for 10 economically important traits: yield, firmness, stem scar diameter, stem scar tear, fruit weight, fruit size, pH, Brix, flower bud density, and bloom earliness. Heritability and breeding values were estimated using ASReml software. The accuracy of these results were analyzed using the jack-knife procedure. Heritability estimates were the same between the two models. Breeding values and ranking differences were not significantly different between the two models. In conclusion, the diploid BLUP model can be an accurate tool to estimate breeding values and heritability in blueberry. The more easily derived BLUP model assuming disomic inheritance will allow for accurate selection of superior parents to increase genetic gains, while decreasing the selection time.