Integrating genomic additive relationship matrices improves the efficiency in diploid banana breeding

This study investigated if integrating molecular information into the clonal model could improve the partitioning of the variance components and yield more accurate estimates of genetic parameters and prediction accuracy of breeding values of 14 key traits in diploid banana. A set of 2,792 informative single nucleotide polymorphism markers were used to construct the genomic-based relationship matrices. We compared the partitioning of genetic variance into additive and non-additive components using the pedigree-based best linear unbiased prediction (P-BLUP) model, the genomic best linear unbiased prediction (G-BLUP) method, which integrates the genetic relationship established through molecular marker information and a combination of the P-BLUP and G-BLUP information, which sources to create a hybrid matrix that estimates hybrid best linear unbiased prediction (H-BLUP).