RESULTS: Our results indicate that models incorporating population structure significantly reduce estimates of additive genetic variance, resulting in substantial reduction of narrow-sense heritability. However, these models considerably improve prediction accuracies. This was particularly significant for growth and solid-wood properties, which showed to have the highest population genetic differentiation (QST) among the studied traits. Additionally, although the pattern of correlations remained similar across the models, their magnitude was slightly lower for models that included population structure as a fixed effect. This suggests that selection, consistently performed within populations, might be less affected by unfavourable genetic correlations compared to mass selection conducted without pedigree restrictions.
CONCLUSIONS: We conclude that the results of models properly accounting for population structure are more accurate and less biased compared to those neglecting this effect. This might have practical implications for breeders and forest managers where, decisions based on imprecise selections can pose a high risk to economic efficiency.
结果:我们的结果表明,包含种群结构的模型显着降低了加性遗传变异的估计,导致狭义遗传力大幅降低。然而,这些模型大大提高了预测精度。这对生长和实木性能尤其重要,表明在所研究的性状中具有最高的群体遗传分化(QST)。此外,尽管模型之间的相关性模式仍然相似,对于将人口结构作为固定效应的模型,其幅度略低。这表明选择,在人群中一贯表现,与没有谱系限制的大量选择相比,可能受不利的遗传相关性影响较小。
结论:我们得出的结论是,与忽略这种影响的模型相比,适当考虑人口结构的模型的结果更准确,偏差更小。这可能会对育种者和森林管理者产生实际影响,基于不精确选择的决策可能会给经济效率带来高风险。