In pig and poultry breeding, the objective is to improve the performance of crossbred production animals, while selection takes place in the purebred parent lines. One way to achieve this is to use genomic prediction with a crossbred reference population. A crossbred reference population benefits from expressing the breeding goal trait but suffers from a lower genetic relatedness with the purebred selection candidates than a purebred reference population. Our aim was to investigate the benefit of using a crossbred reference population for genomic prediction of crossbred performance for: (1) different levels of relatedness between the crossbred reference population and purebred selection candidates, (2) different levels of the purebred-crossbred correlation, and (3) different reference population sizes. We simulated a crossbred breeding program with 0, 1 or 2 multiplication steps to generate the crossbreds, and compared the accuracy of genomic prediction of crossbred performance in one generation using either a purebred or a crossbred reference population. For each scenario, we investigated the empirical accuracy based on simulation and the predicted accuracy based on the estimated effective number of independent chromosome segments between the reference animals and selection candidates. When the purebred-crossbred correlation was 0.75, the accuracy was highest for a two-way crossbred reference population but similar for purebred and four-way crossbred reference populations, for all reference population sizes. When the purebred-crossbred correlation was 0.5, a purebred reference population always resulted in the lowest accuracy. Among the different crossbred reference populations, the accuracy was slightly lower when more multiplication steps were used to create the crossbreds. In general, the benefit of crossbred reference populations increased when the size of the reference population increased. All predicted accuracies overestimated their corresponding empirical accuracies, but the different scenarios were ranked accurately when the reference population was large. The benefit of a crossbred reference population becomes larger when the crossbred population is more related to the purebred selection candidates, when the purebred-crossbred correlation is lower, and when the reference population is larger. The purebred-crossbred correlation and reference population size interact with each other with respect to their impact on the accuracy of genomic estimated breeding values.

中文翻译：

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优化基因组参考种群以提高杂交性能

在猪和家禽育种中，目标是提高杂交生产动物的性能，而选择则在纯种母系中进行。实现此目的的一种方法是将基因组预测与杂交参考种群一起使用。杂种参考种群受益于表达育种目标性状，但与纯种选择候选者的遗传相关性比纯种参考种群低。我们的目的是调查使用杂交参考种群进行杂交性能的基因组预测的益处：（1）杂交参考种群和纯种选择候选者之间的相关性水平不同；（2）不同水平的纯种杂交相关性， （3）不同的参考人口规模。我们模拟了具有0、1或2个乘法步骤的杂种育种程序，以生成杂种，并比较了使用纯种或杂种参考种群的一代杂交性能的基因组预测准确性。对于每种情况，我们研究了基于模拟的经验准确性和基于参考动物和选择候选者之间独立染色体区段的估计有效数量的预测准确性。当纯种杂交的相关性为0.75时，对于所有参考种群大小，两向杂交参考种群的准确性最高，但对于纯种和四向杂交参考种群而言，准确性相似。当纯种杂种相关性为0.5时，纯种参考种群总是导致最低的准确性。在不同的杂交参考种群中，当使用更多的乘法步骤创建杂交品种时，准确性会稍低。通常，当参考群体的数量增加时，杂交参考群体的利益就会增加。所有预测的精度都高估了其相应的经验精度，但是当参考人口很大时，对不同的情景进行了准确排名。当杂种群体与纯种选择候选者之间的相关性更高，纯种与杂种的相关性较低以及参考群体较大时，杂种参考群体的收益就会更大。