Abstract The main purpose of the present study was to evaluate the accuracy of genomic predictions in two purebreds using three different ways for the reference population formation: (1) a separate purebred reference population (SI), (2) a combined reference population from two breeds (CO), and (3) use of crossbred data (CR). The effects of different reference population structure were compared under different marker densities, reference population sizes, divergence between breeds, and methods used for estimating marker effects. The results showed that at lower marker densities, the SI had the highest accuracy of breeding values. With the increase in the marker density, the use of the CO increased the accuracy relative to the SI in scenarios were generations since divergence was low. In the CO and CR, the BayesB method was more accurate than the rrBLUP, and decreasing the generations since divergence increased the accuracy of predictions at higher marker density. Increased population size, marker density, and genetic relationship between breeds and using the BayesB method retained accuracies higher after five generations. Interestingly, the CR had the lowest accuracy drop after five generations.

中文翻译：

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用于小群体基因组选择的组合、杂交和纯种参考群体的比较

摘要 本研究的主要目的是使用三种不同的参考种群形成方式评估两个纯种基因组预测的准确性：（1）单独的纯种参考种群（SI），（2）来自两个纯种的组合参考种群。品种 (CO)，以及 (3) 杂交数据 (CR) 的使用。在不同的标记密度、参考种群大小、品种之间的差异和用于估计标记效应的方法下，比较了不同参考种群结构的影响。结果表明，在较低的标记密度下，SI 具有最高的育种值准确度。随着标记密度的增加，CO 的使用增加了在场景中相对于 SI 的准确性，因为分歧很小。在 CO 和 CR 中，BayesB 方法比 rrBLUP 更准确，并且由于发散增加了在更高标记密度下预测的准确性，因此减少了代数。增加种群规模、标记密度和品种之间的遗传关系，并使用 BayesB 方法在五代后保持更高的准确度。有趣的是，CR 在五代之后的准确率下降最低。