Genome-Enabled Estimates of Additive and Nonadditive Genetic Variances and Prediction of Apple Phenotypes Across Environments.
The nonadditive genetic effects may have an important contribution to total genetic variation of phenotypes, so estimates of both the additive and nonadditive effects are desirable for breeding and selection purposes. Our main objectives were to: estimate additive, dominance and epistatic variances of apple (Malus × domestica Borkh.) phenotypes using relationship matrices constructed from genome-wide dense single nucleotide polymorphism (SNP) markers; and compare the accuracy of genomic predictions using genomic best linear unbiased prediction models with or without including nonadditive genetic effects. A set of 247 clonally replicated individuals was assessed for six fruit quality traits at two sites, and also genotyped using an Illumina 8K SNP array. Across several fruit quality traits, the additive, dominance, and epistatic effects contributed about 30%, 16%, and 19%, respectively, to the total phenotypic variance. Models ignoring nonadditive components yielded upwardly biased estimates of additive variance (heritability) for all traits in this study. The accuracy of genomic predicted genetic values (GEGV) varied from about 0.15 to 0.35 for various traits, and these were almost identical for models with or without including nonadditive effects. However, models including nonadditive genetic effects further reduced the bias of GEGV. Between-site genotypic correlations were high (>0.85) for all traits, and genotype-site interaction accounted for <10% of the phenotypic variability. The accuracy of prediction, when the validation set was present only at one site, was generally similar for both sites, and varied from about 0.50 to 0.85. The prediction accuracies were strongly influenced by trait heritability, and genetic relatedness between the training and validation families.
The New Zealand Institute for Plant & Food Research Limited, Hawke's Bay Research Center, Havelock North, 4130 New Zealand Satish.Kumar@plantandfood.co.nz.
Satish
S
Kumar
The New Zealand Institute for Plant & Food Research Limited, Hawke's Bay Research Center, Havelock North, 4130 New Zealand.
Claire
C
Molloy
Agronomy Department, University of Florida, Gainesville, Florida 32611.
Patricio
P
Muñoz
AgriBio Center, La Trobe University, Bundoora, Victoria 3083, Australia.
Hans
H
Daetwyler
Plant & Food Research, Palmerston North Research Center, Palmerston North, 4442, New Zealand.
David
D
Chagné
The New Zealand Institute for Plant & Food Research Limited, Hawke's Bay Research Center, Havelock North, 4130 New Zealand.
Richard
R
Volz
D000465:Algorithms; D001947:Breeding; D004777:Environment; D019143:Evolution, Molecular; D059647:Gene-Environment Interaction; D014644:Genetic Variation; D005828:Genetics, Population; D018745:Genome, Plant; D023281:Genomics; D040582:Inheritance Patterns; D027845:Malus / Q000235:genetics*; D008957:Models, Genetic; D010375:Pedigree; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D015203:Reproducibility of Results; D012641:Selection, Genetic
GBLUP; Malus × domestica; apple breeding; genomic prediction; heritability