BACKGROUND In livestock breeding, selection for some traits can be improved with direct selection for crossbred performance. However, genetic analyses with phenotypes from crossbred animals require methods for multibreed relationship matrices; especially when some animals are rotationally crossbred. Multiple methods for multibreed relationship matrices exist, but there is a lack of knowledge on how these methods compare for prediction of breeding values with phenotypes from rotationally crossbred animals. Therefore, the objective of this study was to compare models that use different multibreed relationship matrices in terms of ability to predict accurate and unbiased breeding values with phenotypes from two-way rotationally crossbred animals. METHODS We compared four methods for multibreed relationship matrices: numerator relationship matrices (NRM), García-Cortés and Toro's partial relationship matrices (GT), Strandén and Mäntysaari's approximation to the GT method (SM), and one NRM with metafounders (MF). The methods were compared using simulated data. We simulated two phenotypes; one with and one without dominance effects. Only crossbred animals were phenotyped and only purebred animals were genotyped. RESULTS The MF and GT methods were the most accurate and least biased methods for prediction of breeding values in rotationally crossbred animals. Without genomic information, all methods were almost equally accurate for prediction of breeding values in purebred animals; however, with genomic information, the MF and GT methods were the most accurate. The GT, MF, and SM methods were the least biased methods for prediction of breeding values in purebred animals. CONCLUSIONS For prediction of breeding values with phenotypes from rotationally crossbred animals, models using the MF method or the GT method were generally more accurate and less biased than models using the SM method or the NRM method.

中文翻译：

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在具有旋转杂交的系统中使用不同的多品种关系矩阵的动物模型的预测性能。

背景在畜牧育种中，一些性状的选择可以通过直接选择杂交性能来改进。然而，对杂交动物表型的遗传分析需要多品种关系矩阵的方法。尤其是当一些动物轮流杂交时。存在多种用于多品种关系矩阵的方法，但缺乏关于这些方法如何比较预测育种值与轮交杂交动物表型的知识。因此，本研究的目的是比较使用不同多品种关系矩阵的模型在预测准确和无偏的育种值与双向旋转杂交动物表型的能力方面。方法 我们比较了多品种关系矩阵的四种方法：分子关系矩阵 (NRM)、García-Cortés 和 Toro 的部分关系矩阵 (GT)、Strandén 和 Mäntysaari 对 GT 方法的近似 (SM)，以及一个具有元创始人 (MF) 的 NRM。使用模拟数据对这些方法进行了比较。我们模拟了两种表型；一种有支配效应，一种没有支配效应。仅对杂交动物进行表型分析，仅对纯种动物进行基因分型。结果 MF 和 GT 方法是预测轮交动物育种值最准确和偏差最小的方法。如果没有基因组信息，所有方法对于预测纯种动物的育种价值几乎同样准确；然而，对于基因组信息，MF 和 GT 方法是最准确的。GT，MF，和 SM 方法是预测纯种动物育种值的最小偏差方法。结论 对于轮交杂交动物表型的育种值预测，使用 MF 方法或 GT 方法的模型通常比使用 SM 方法或 NRM 方法的模型更准确且偏差更小。