Genomic Predictions With Nonadditive Effects Improved Estimates of Additive Effects and Predictions of Total Genetic Values in Pinus sylvestris - Calleja-Rodriguez, Ainhoa; Chen, ZhiQiang; Suontama, Mari; Pan, Jin; Wu, Harry X. (Frontiers in Plant Science, 2021)
Genomic selection study focusing on non-additive genetic effects of dominance and first order of epistatic effects, in a full-sib family population of 695 Scots pine (Pinus sylvestris L.) trees, was undertaken for growth and wood quality traits, using 6344 single nucleotide polymorphism markers (SNPs) generated by genotyping-by-sequencing (GBS). Genomic marker-based relationship matrices offer more effective modelling of non-additive genetic effects than pedigree-based models, thus increasing the knowledge on the relevance of dominance and epistatic variation in forest tree breeding. Genomic marker-based models were compared with pedigree-based models showing a considerable dominance and epistatic variation for growth traits. Non-additive genetic variation of epistatic nature (additive × additive) was detected for growth traits, wood density (DEN) and modulus of elasticity (MOEd) representing between 2.27% to 34.5% of the total phenotypic variance. Including dominance variance in pedigree-based Best Linear Unbiased Prediction (PBLUP) and epistatic variance in genomic-based Best Linear Unbiased Prediction (GBLUP) resulted in decreased narrow-sense heritability and increased broad-sense heritability for growth traits, DEN and MOEd. Higher genetic gains were reached with early genomic selection based on total genetic values, than with conventional pedigree selection for a selection intensity of 1%. This study indicates that non-additive genetic variance may have a significant role in the variation of selection traits of Scots pine, thus clonal deployment could be an attractive alternative for the species. Additionally confidence on the role of non-additive genetic effects in this breeding program should be pursued in the future, using also genomic selection.