Accuracy of genomic prediction depends on the heritability of the trait, the size of the training set, the relationship of the candidates to the training set, and the $$\text {Min}(N_{\text {QTL}},M_e)$$ , where $$N_{\text {QTL}}$$ is the number of QTL and $$M_e$$ is the number of independently segregating chromosomal segments. Due to LD, the number $$Q_e$$ of independently segregating QTL (effective QTL) can be lower than $$\text {Min}(N_{\text {QTL}},M_e)$$ . In this paper, we show that $$Q_e$$ is inversely associated with the trait-specific genomic relationship of a candidate to the training set. This provides an explanation for the inverse association between $$Q_e$$ and the accuracy of prediction. To quantify the genomic relationship of a candidate to all members of the training set, we considered the $$k^2$$ statistic that has been previously used for this purpose. It quantifies how well the marker covariate vector of a candidate can be represented as a linear combination of the rows of the marker covariate matrix of the training set. In this paper, we used Bayesian regression to make this statistic trait specific and argue that the trait-specific genomic relationship of a candidate to the training set is inversely associated with $$Q_e$$ . Simulation was used to demonstrate the dependence of the trait-specific $$k^2$$ statistic on $$Q_e$$ , which is related to $$N_{\text {QTL}}$$ . The posterior distributions of the trait-specific $$k^2$$ statistic showed that the trait-specific genomic relationship between a candidate and the training set is inversely associated to $$Q_e$$ and $$N_{\text {QTL}}$$ . Further, we show that trait-specific genomic relationship between a candidate and the training set is directly related to the size of the training set.

中文翻译：

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关于 QTL 数量与候选者与训练集的性状特异性基因组关系之间的负相关。


基因组预测的准确性取决于性状的遗传性、训练集的大小、候选者与训练集的关系以及 $$\text {Min}（N_{\text {QTL}}，M_e）$$ ，其中 $$N_{text {QTL}}$$ 是 QTL 的数量，$$M_e$$ 是独立分离的染色体片段的数量。由于 LD，独立分离的 QTL（有效 QTL）的数量 $$Q_e$$ 可以低于 $$\text {Min}（N_{\text {QTL}}，M_e）$$。在本文中，我们表明 $$Q_e$$ 与候选者与训练集的性状特异性基因组关系呈负相关。这为$$Q_e$$和预测准确性之间的负关联提供了解释。为了量化候选人与训练集所有成员的基因组关系，我们考虑了以前用于此目的的 $$k^2$$ 统计量。它量化了候选项的标记协变量向量可以表示为训练集的标记协变量矩阵行的线性组合的程度。在本文中，我们使用贝叶斯回归使该统计特征具有特异性，并认为候选者与训练集的特征特异性基因组关系与 $$Q_e$$ 呈负相关。模拟用于证明特定于特征的 $$k^2$$ 统计数据对 $$Q_e$$ 的依赖性，这与 $$N_{\text {QTL}}$$ 有关。特征特异性 $$k^2$$ 统计量的后验分布表明，候选者与训练集之间的特征特异性基因组关系与 $$Q_e$$ 和 $$N_{\text {QTL}}$$ 呈负相关。此外，我们表明，候选者与训练集之间的特征特异性基因组关系与训练集的大小直接相关。