Abstract

BackgroundGenomic selection (GS) or genomic prediction is considered as a promising approach to accelerate tree breeding and increase genetic gain by shortening breeding cycle, but the efforts to develop routines for operational breeding are so far limited. We investigated the predictive ability (PA) of GS based on 484 progeny trees from 62 half-sib families in Norway spruce (Picea abies (L.) Karst.) for wood density, modulus of elasticity (MOE) and microfibril angle (MFA) measured with SilviScan, as well as for measurements on standing trees by Pilodyn and Hitman instruments.ResultsGS predictive abilities were comparable with those based on pedigree-based prediction. Marker-based PAs were generally 25–30% higher for traits density, MFA and MOE measured with SilviScan than for their respective standing tree-based method which measured with Pilodyn and Hitman. Prediction accuracy (PC) of the standing tree-based methods were similar or even higher than increment core-based method. 78–95% of the maximal PAs of density, MFA and MOE obtained from coring to the pith at high age were reached by using data possible to obtain by drilling 3–5 rings towards the pith at tree age 10–12.ConclusionsThis study indicates standing tree-based measurements is a cost-effective alternative method for GS. PA of GS methods were comparable with those pedigree-based prediction. The highest PAs were reached with at least 80–90% of the dataset used as training set. Selection for trait density could be conducted at an earlier age than for MFA and MOE. Operational breeding can also be optimized by training the model at an earlier age or using 3 to 5 outermost rings at tree age 10 to 12 years, thereby shortening the cycle and reducing the impact on the tree.

Highlights

  • Genomic selection (GS) or genomic prediction is considered as a promising approach to accelerate tree breeding and increase genetic gain by shortening breeding cycle, but the efforts to develop routines for operational breeding are so far limited

  • Marker-based predictive ability (PA) and Prediction accuracy (PC) between increment core-based and standing-base wood quality traits The marker-based PAs were generally 25–30% higher for traits density, microfibril angle (MFA) and modulus of elasticity (MOE) measured with SilviScan than for their respective standing tree-based method which measured with Pilodyn and Hitman

  • 1) In comparison with phenotypic selection, Genomic selection methods showed similar to higher prediction abilities (PAs) for both increment coreand standing tree-based phenotyping methods

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Summary

Introduction

Genomic selection (GS) or genomic prediction is considered as a promising approach to accelerate tree breeding and increase genetic gain by shortening breeding cycle, but the efforts to develop routines for operational breeding are so far limited. Norway spruce breeding cycle is approximately 25–30 years long, Genomic prediction using genome-wide dense markers or genomic selection (GS) was first introduced by Meuwissen [4]. The method modelling the effect of large numbers of DNA markers covering the entire genome and subsequently predict the genomic value of individuals that have been genotyped, but not phenotyped. As compared to the phenotypic mass selection based on a pedigree-based relationship matrix (A matrix), genomic prediction relies on constructing a marker-based relationship matrix (G matrix).

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