The Dohne Merino sheep was introduced to Australia from South Africa in the 1990s. It was primarily used in crosses with the Merino breed sheep to improve on attributes such as reproduction and carcass composition. Since then, this breed has continued to expand in Australia but the number of genotyped and phenotyped purebred individuals remains low, calling into question the accuracy of genomic selection. The Australian Merino, on the other hand, has a substantial reference population in a separate genomic evaluation (MERINOSELECT). Combining these resources could fast track the impact of genomic selection on the smaller breed, but the efficacy of this needs to be investigated. This study was based on a dataset of 53,663 genotypes and more than 2 million phenotypes. Its main objectives were (1) to characterize the genetic structure of Merino and Dohne Merino breeds, (2) to investigate the utility of combining their evaluations in terms of quality of predictions, and (3) to compare several methods of genetic grouping. We used the ‘LR-method’ (Linear Regression) for these assessments. We found very low Fst values (below 0.048) between the different Merino lines and Dohne breed considered in our study, indicating very low genetic differentiation. Principal component analysis revealed three distinct groups, identified as purebred Merino, purebred Dohne, and crossbred animals. Considering the whole population in the reference led to the best quality of predictions and the largest increase in accuracy (from ‘LR-method’) from pedigree to genomic-based evaluations: 0.18, 0.14 and 0.16 for yearling fibre diameter (YFD), yearling greasy fleece weight (YGFW) and yearling liveweight (YWT), respectively. Combined genomic evaluations showed higher accuracies than the evaluation based on the Dohne reference only (accuracies increased by 0.16, 0.06 and 0.07 for YFD, YGFW, and YWT, respectively). For the combined genomic evaluations, metafounder models were more accurate than Unknown Parent Groups models (accuracies increased by 0.04, 0.04 and 0.06 for YFD, YGFW and YWT, respectively). We found promising results for the future transition of the Dohne breed from pedigree to genomic selection. A combined genomic evaluation, with the MERINOSELECT evaluation in addition to using metafounders, is expected to enhance the quality of genomic predictions for the Dohne Merino breed.

中文翻译：

---

澳大利亚美利奴绵羊和多恩美利奴绵羊种群的联合基因组评估


Dohne 美利奴羊于 20 世纪 90 年代从南非引入澳大利亚。它主要用于与美利奴羊杂交，以改善繁殖和胴体成分等属性。从那时起，该品种在澳大利亚继续扩大，但基因分型和表型纯种个体的数量仍然很低，这使人们对基因组选择的准确性产生了疑问。另一方面，澳大利亚美利奴羊在单独的基因组评估 (MERINOSELECT) 中拥有大量参考群体。结合这些资源可以快速追踪基因组选择对较小品种的影响，但其有效性需要研究。这项研究基于 53,663 个基因型和超过 200 万个表型的数据集。其主要目标是（1）描述美利奴和多恩美利奴品种的遗传结构特征，（2）研究在预测质量方面将其评估相结合的效用，以及（3）比较几种遗传分组方法。我们使用“LR 方法”（线性回归）进行这些评估。我们发现我们研究中考虑的不同美利奴品种和 Dohne 品种之间的 Fst 值非常低（低于 0.048），表明遗传分化非常低。主成分分析揭示了三个不同的群体，分别是纯种美利奴动物、纯种多恩动物和杂交动物。考虑到参考文献中的整个种群，从谱系到基于基因组的评估，预测质量最高，准确度（从“LR 方法”）得到最大提高：一岁鸽纤维直径 (YFD)、一岁鸽为 0.18、0.14 和 0.16分别为油腻羊毛重量 (YGFW) 和一岁活重 (YWT)。 组合基因组评估显示出比仅基于 Dohne 参考的评估更高的准确性（YFD、YGFW 和 YWT 的准确性分别增加了 0.16、0.06 和 0.07）。对于组合基因组评估，metaFounder 模型比 Unknown Parent Groups 模型更准确（YFD、YGFW 和 YWT 的准确度分别增加了 0.04、0.04 和 0.06）。我们为 Dohne 品种未来从谱系选择到基因组选择的转变找到了有希望的结果。除了使用元创建者之外，结合基因组评估与 MERINOSELECT 评估预计将提高 Dohne 美利奴品种基因组预测的质量。