2017 ASHS Annual Conference

New parents and candidate cultivars can be identified by modelling performance information as allelic effects at known individual large-effect loci influencing traits (QTLs) and genome-wide small-effect loci (genetic background). Typically, marker-assisted breeding targets QTLs while genomic selection targets the genetic background. However, interaction between variable environmental and genetic effects (G×E) might influence selection accuracy of these approaches for commercial deployment. On one hand, if factors that predict G×E patterns can be identified, candidate cultivars might be targeted to specific environments, while on the other, unaccounted-for G×E will compromise selection response. Typically, G×E in horticulture is studied using multi-environment trials (METs) of clonally replicated individuals across locations. However, METs are expensive for fruit trees, particularly due to the size of the experimental unit and the long juvenile period. Here we outline a RosBREED-led international collaboration to extend genomic selection methods to study G×E. Single nucleotide polymorphism (SNP) array data on individuals assessed for sweetness in multiple environments are used to model replication of QTLs and genetic background effects across these environments. This new approach allows historical data to be combined to study stability of these genetic effects over various environments without the need for clonal replication and is demonstrated using sweet cherry fruit maturity data collected in the U.S. and Europe across two years and peach sweetness data collected at three locations in the U.S. across two years. We encourage others to contribute data to this international collaborative effort as additional individuals, locations, years, and growing and fruiting conditions will improve the generality and accuracy of predictions.