Genome-wide prediction for hybrids between parents with distinguished difference on exotic introgressions in Brassica napus

Abstract

Extensive exotic introgression could significantly enlarge the genetic distance of hybrid parental populations to promote strong heterosis. The goal of this study was to investigate whether genome-wide prediction can support pre-breeding in populations with exotic introgressions. We evaluated seed yield, seed yield related traits and seed quality traits of 363 hybrids of Brassica napus (AACC) derived from two parental populations divergent on massive exotic introgression of related species in three environments. The hybrids presented strong heterosis on seed yield, which was much higher than other investigated traits. Five genomic best linear unbiased prediction models considering the exotic introgression and different marker effects (additive, dominance, and epistatic effects) were constructed to test the prediction ability for different traits of the hybrids. The analysis showed that the trait complexity, exotic introgression, genetic relationship between the training set and testing set, training set size, and environments affected the prediction ability. The models with best prediction ability for different traits varied. However, relatively high prediction ability (e.g., 0.728 for seed yield) was also observed when the simplest models were used, excluding the effects of the special exotic introgression and epistasis effect by 5-fold cross validation, which would simplify the prediction for the trait with complex architecture for hybrids with exotic introgression. The results provide novel insights and strategies for genome-wide prediction of hybrids between genetically distinct parent groups with exotic introgressions.