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Analysis of non-additive genetic effects in Norway spruce

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Genetic variance includes both additive and non-additive components, and the latter can be partitioned into dominance and epistatic variance. Additive genetic variance has been the main source of genetic improvement in most tree breeding programs and the genetic gain achieved has mostly been deployed through open-pollinated seed orchards. However, non-additive effects could be exploited in alternative deployment programs and provide additional genetic gain. Thus, knowledge of non-additive effects is essential for constructing robust genetic models and evaluating vegetative deployment systems, particularly for clonal forestry. In this study, we used data drawn from seven Norway spruce full-sib and three half-sib clonal trials to test and compare different models partitioning genetic effects into additive, dominance, and epistatic components for height and diameter. Simpler models provided more robust estimates of additive and non-additive effects, whereas more complex models provided more detail and insight in performance at single sites and G × E patterns, but with less reliable estimates. In this study, we cannot clearly distinguish the size and importance of dominance and epistatic effects. However, the total non-additive effects seem to be substantial, being around 80–90% of the additive, and were of the magnitude required to consider clonal forestry as an alternative to current deployment systems. Additive correlations largely followed the expected patterns based on seed zones and late spring frost incidence. Clonal correlations were generally lower than the additive implying that G × E interactions were stronger for non-additive effects.

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The authors would like to thank Bo Karlsson and anonymous reviewers for their helpful comments on the manuscript and Aron Davidsson for the help with map development.

Data archiving statement

All raw data are archived in DATAPLAN® for access.


The study was financed by Södras forskningsstiftelse (the Södra Forest Owner Association Research Foundation).

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Correspondence to Mats Berlin.

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Communicated by F. Isik

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Table 12 Spacing, number of plants and replications, geographic location, climatic conditions, and assessments at all trials in each trial series used in this study
Table 13 Between-site common families and clones in parenthesis for the RS trial series
Table 14 Between-site common families and clones in parenthesis for the Zone56 trial series
Table 15 Between-site common families and clones in parenthesis for the Hsib trial series
Table 16 p values for the fixed effects, LogL, and Akaike’s information criterion (AIC) for H12 for each model in the RS trial series
Table 17 p values for the fixed effects, LogL, and Akaike’s information criterion (AIC) for H12 for each model in the Zone56 trial series
Table 18 Observed variance components and genetic parameters with standard errors in parenthesis of the best model (12) and the reference model (11) for H12 and each trial in the RS trial series
Table 19 Observed variance components and genetic parameters with standard errors in parenthesis of the best model (3) and the reference model (11) for H12 and each trial in the Zone56 trial series
Table 20 Additive (rA), family (rf), and clonal (rc) correlation estimates for H12 in the RS trial series for the best model (12) and the reference model (11). Standard errors are shown in parenthesis
Table 21 Additive (rA), family (rf), and clonal (rc) correlation estimates for D12 in the Zone56 trial series for the best model (3) and the reference model (11). Standard errors are shown in parenthesis

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Berlin, M., Jansson, G., Högberg, KA. et al. Analysis of non-additive genetic effects in Norway spruce. Tree Genetics & Genomes 15, 42 (2019).

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