Genomewide selection for fruit quality traits in apple: breeding insights gained from prediction and postdiction

Abstract

Many fruit quality traits in apple (Malus domestica Borkh.) are controlled by multiple small-effect quantitative trait loci (QTLs). Genomewide selection (genomic selection) might be an effective breeding approach for highly quantitative traits in woody perennial crops with long generation times like apple. The goal of this study was to determine if genomewide prediction is an effective breeding approach for fruit quality traits in an apple scion breeding program. Representative apple scion breeding germplasm (nindividuals = 955), high-quality single nucleotide polymorphism (SNP) data (nSNPs = 977), and breeding program fruit quality trait data at harvest were analyzed. Breeding parents ‘Honeycrisp’ and ‘Minneiska’ were highly represented. Moderate to high predictive abilities were observed for most fruit quality traits at harvest. For example, when 25% random subsets of the germplasm set were used as training sets, mean predictive abilities ranged from 0.35 to 0.54 across traits. Trait, training and test sets, family size for within family prediction, and number of SNPs per chromosome affected model predictive ability. Inclusion of large-effect QTLs as fixed effects resulted in higher predictive abilities for some traits (e.g., percent red overcolor). Postdiction (i.e., retrospective) analyses demonstrated the impact of culling threshold on selection decisions. The results of this study demonstrate that genomewide selection is a useful breeding approach for certain fruit quality traits in apple.

Mapping QTLs for blight resistance and morpho-phenological traits in inter-species hybrid families of chestnut (Castanea spp.)

“…An alternative approach is to apply genomic selection. Application of genomic selection is being investigated in breeding programs of woody perennial species including chestnut ( Westbrook et al., 2020 ), fruit trees and bushes ( Roth et al., 2020 ; Ferrão et al., 2021 ; Kostick et al., 2023 ; Sun et al., 2024 ), and other tropical fruit and plantation tree species ( Seyum et al., 2022 ). It is evident that efficient genomic selection needs a relatively large training population using comparable criteria for phenotyping and having a similar genetic background to the trees under selection.…”

Integrative multi-environmental genomic prediction in apple

“…The interaction between markers and environments provides a mathematical representation of the natural phenomenon of genotype-by-environment interaction, which results from the variability in the genotype performance ranking across different environmental conditions. Despite numerous reports of successful phenotypic performance prediction using molecular markers in perennial crops such as apple (Kostick et al, 2023; Kumar et al, 2012; Migicovsky et al, 2016; Muranty et al, 2015), genotype-by-environment interaction has been often overlooked in genomic prediction of apple traits.…”