Boerner Vinzent, Johnston David J, Tier Bruce
Animal Genetics and Breeding Unit, University of New England, Armidale, 2351, NSW, Australia.
Genet Sel Evol. 2014 Oct 24;46(1):61. doi: 10.1186/s12711-014-0061-9.
The major obstacles for the implementation of genomic selection in Australian beef cattle are the variety of breeds and in general, small numbers of genotyped and phenotyped individuals per breed. The Australian Beef Cooperative Research Center (Beef CRC) investigated these issues by deriving genomic prediction equations (PE) from a training set of animals that covers a range of breeds and crosses including Angus, Murray Grey, Shorthorn, Hereford, Brahman, Belmont Red, Santa Gertrudis and Tropical Composite. This paper presents accuracies of genomically estimated breeding values (GEBV) that were calculated from these PE in the commercial pure-breed beef cattle seed stock sector.
PE derived by the Beef CRC from multi-breed and pure-breed training populations were applied to genotyped Angus, Limousin and Brahman sires and young animals, but with no pure-breed Limousin in the training population. The accuracy of the resulting GEBV was assessed by their genetic correlation to their phenotypic target trait in a bi-variate REML approach that models GEBV as trait observations.
Accuracies of most GEBV for Angus and Brahman were between 0.1 and 0.4, with accuracies for abattoir carcass traits generally greater than for live animal body composition traits and reproduction traits. Estimated accuracies greater than 0.5 were only observed for Brahman abattoir carcass traits and for Angus carcass rib fat. Averaged across traits within breeds, accuracies of GEBV were highest when PE from the pooled across-breed training population were used. However, for the Angus and Brahman breeds the difference in accuracy from using pure-breed PE was small. For the Limousin breed no reasonable results could be achieved for any trait.
Although accuracies were generally low compared to published accuracies estimated within breeds, they are in line with those derived in other multi-breed populations. Thus PE developed by the Beef CRC can contribute to the implementation of genomic selection in Australian beef cattle breeding.
在澳大利亚肉牛中实施基因组选择的主要障碍是品种繁多，而且通常每个品种的基因分型和表型个体数量较少。澳大利亚肉牛合作研究中心（肉牛合作研究中心）通过从一组涵盖多个品种和杂交品种（包括安格斯牛、墨累灰牛、短角牛、赫里福德牛、婆罗门牛、贝尔蒙特红牛、圣格特鲁迪斯牛和热带杂交牛）的训练动物中推导基因组预测方程（PE）来研究这些问题。本文介绍了在商业纯种种公牛繁育部门中，根据这些预测方程计算出的基因组估计育种值（GEBV）的准确性。
肉牛合作研究中心从多品种和纯种训练群体中推导的预测方程被应用于基因分型的安格斯牛、利木赞牛和婆罗门牛的种公牛及幼畜，但训练群体中没有纯种利木赞牛。在双变量REML方法中，将GEBV作为性状观测值进行建模，通过GEBV与表型目标性状的遗传相关性来评估所得GEBV的准确性。
安格斯牛和婆罗门牛的大多数GEBV准确性在0.1至0.4之间，屠宰胴体性状的准确性通常高于活体动物体组成性状和繁殖性状。仅在婆罗门牛屠宰胴体性状和安格斯牛胴体肋脂肪上观察到估计准确性大于0.5。在品种内各性状上进行平均时，使用混合的跨品种训练群体的预测方程时，GEBV的准确性最高。然而，对于安格斯牛和婆罗门牛品种，使用纯种预测方程时准确性的差异较小。对于利木赞牛品种，任何性状都无法获得合理结果。
尽管与品种内估计的已发表准确性相比，准确性普遍较低，但它们与其他多品种群体得出的结果一致。因此，肉牛合作研究中心开发的预测方程有助于在澳大利亚肉牛育种中实施基因组选择。
