Treehouse Forest Research LLC, Check, VA 24072, USA.
Department of Animal and Dairy Science, University of Georgia, Athens, GA 30602, USA.
G3 (Bethesda). 2022 Aug 25;12(9). doi: 10.1093/g3journal/jkac180.
Genetic groups have been widely adopted in tree breeding to account for provenance effects within pedigree-derived relationship matrices. However, provenances or genetic groups have not yet been incorporated into single-step genomic BLUP ("HBLUP") analyses of tree populations. To quantify the impact of accounting for population structure in Eucalyptus globulus, we used HBLUP to compare breeding value predictions from models excluding base population effects and models including either fixed genetic groups or the marker-derived proxies, also known as metafounders. Full-sib families from 2 separate breeding populations were evaluated across 13 sites in the "Green Triangle" region of Australia. Gamma matrices (Γ) describing similarities among metafounders reflected the geographic distribution of populations and the origins of 2 land races were identified. Diagonal elements of Γ provided population diversity or allelic covariation estimates between 0.24 and 0.56. Genetic group solutions were strongly correlated with metafounder solutions across models and metafounder effects influenced the genetic solutions of base population parents. The accuracy, stability, dispersion, and bias of model solutions were compared using the linear regression method. Addition of genomic information increased accuracy from 0.41 to 0.47 and stability from 0.68 to 0.71, while increasing bias slightly. Dispersion was within 0.10 of the ideal value (1.0) for all models. Although inclusion of metafounders did not strongly affect accuracy or stability and had mixed effects on bias, we nevertheless recommend the incorporation of metafounders in prediction models to represent the hierarchical genetic population structure of recently domesticated populations.
遗传群已被广泛应用于树木育种中，以解释谱系衍生关系矩阵中的起源效应。然而，起源或遗传群尚未被纳入树木群体的一步法基因组 BLUP（“HBLUP”）分析中。为了量化在桉树中考虑群体结构的影响，我们使用 HBLUP 比较了排除基础群体效应的模型和包括固定遗传群或标记衍生代理（也称为元发现者）的模型的育种值预测。来自 2 个独立育种群体的全同胞家系在澳大利亚“绿三角”地区的 13 个地点进行了评估。描述元发现者之间相似性的伽马矩阵（Γ）反映了群体的地理分布，确定了 2 个地方品种的起源。Γ 的对角元素提供了种群多样性或等位基因协方差的估计值，范围在 0.24 到 0.56 之间。遗传群解决方案在模型之间与元发现者解决方案强烈相关，并且元发现者效应影响了基础群体亲本的遗传解决方案。使用线性回归方法比较了模型解决方案的准确性、稳定性、分散性和偏差。添加基因组信息将准确性从 0.41 提高到 0.47，稳定性从 0.68 提高到 0.71，同时略微增加了偏差。对于所有模型，分散度都在理想值（1.0）的 0.10 以内。尽管包含元发现者并没有强烈影响准确性或稳定性，并且对偏差有混合影响，但我们仍然建议在预测模型中包含元发现者，以代表最近驯化的群体的分层遗传群体结构。
