Abstract
Plantation‐grown trees have to cope with an increasing pressure of pest and disease in the context of climate change, and breeding approaches using genomics may offer efficient and flexible tools to face this pressure. In the present study, we targeted genetic improvement of resistance of an introduced conifer species in Canada, Norway spruce (Picea abies (L.) Karst.), to the native white pine weevil (Pissodes strobi Peck). We developed single‐ and multi‐trait genomic selection (GS) models and selection indices considering the relationships between weevil resistance, intrinsic wood quality, and growth traits. Weevil resistance, acoustic velocity as a proxy for mechanical wood stiffness, and average wood density showed moderate‐to‐high heritability and low genotype‐by‐environment interactions. Weevil resistance was genetically positively correlated with tree height, height‐to‐diameter at breast height (DBH) ratio, and acoustic velocity. The accuracy of the different GS models tested (GBLUP, threshold GBLUP, Bayesian ridge regression, BayesCπ) was high and did not differ among each other. Multi‐trait models performed similarly as single‐trait models when all trees were phenotyped. However, when weevil attack data were not available for all trees, weevil resistance was more accurately predicted by integrating genetically correlated growth traits into multi‐trait GS models. A GS index that corresponded to the breeders’ priorities achieved near maximum gains for weevil resistance, acoustic velocity, and height growth, but a small decrease for DBH. The results of this study indicate that it is possible to breed for high‐quality, weevil‐resistant Norway spruce reforestation stock with high accuracy achieved from single‐trait or multi‐trait GS.
Highlights
Trees are long‐lived stationary organisms that have to withstand pests and diseases during their lifetime
Our results suggest that accelerated breeding of resistant seed stock through genomic selection tools will result in taller trees, either because the leaders of resistant trees will be less affected by attacks, or because alleles underlying growth genes will be simultaneously favored
We investigated the genetic control of weevil resistance and its relationship with wood and growth traits in Norway spruce as an exotic plantation species
Summary
Trees are long‐lived stationary organisms that have to withstand pests and diseases during their lifetime. Multivariate genomic selection models can improve the accu‐ racy of predictions by taking advantage of the genetic correlations between traits (Calus & Veerkamp, 2011) This ability is especially advantageous for prediction of traits that are costly or difficult to measure by conventional means on a large number of candidate trees, such as weevil resistance or wood quality, by using available correlated indicator traits. Given the observed positive genetic correlations between weevil resistance and height growth (Mottet et al, 2015), and the possible correlations with wood quality traits, multi‐trait GS models could improve the accuracy of predictions for traits that are difficult and expensive to assess on a large number of trees. Our objectives were to (a) better un‐ derstand the genetic relationships between weevil attack and other growth and wood traits, in particular intrinsic wood quality traits; (b) evaluate the performance of different single‐trait genomic selection models, especially for weevil resistance; (c) test the performance of multi‐trait genomic selection models for predicting a target trait (weevil resistance or wood quality) when coupled with genetically correlated indicator traits (e.g., height growth); and (d) develop multi‐ trait genomic selection indices for the production of high‐quality and weevil‐resistant seedling stock in Norway spruce
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