Animal Breeding and Genomics Centre, Wageningen University, 6700 AH Wageningen, the Netherlands.
J Dairy Sci. 2011 Jan;94(1):431-41. doi: 10.3168/jds.2009-2840.
Genomic selection (GS) permits accurate breeding values to be obtained for young animals, shortening the generation interval and accelerating the genetic gain, thereby leading to reduced costs for proven bulls. Genotyping a large number of animals using high-density single nucleotide polymorphism marker arrays is nevertheless expensive, and therefore, a method to reduce the costs of GS is desired. The aim of this study was to investigate an influence of enlarging the reference population, with either genotyped animals or individuals with predicted genotypes, on the accuracy of genomic estimated breeding values. A dairy cattle population was simulated in which proven bulls with 100 daughters were used as a reference population for GS. Phenotypic records were simulated for bulls with heritability equal to the reliability of daughter yield deviations based on 100 daughters. The simulated traits represented heritabilities at the level of individual daughter performance of 0.3, 0.05, and 0.01. Three scenarios were considered in which (1) the reference population consisted of 1,000 genotyped animals, (2) 1,000 ungenotyped animals were added to the reference population, and (3) the 1,000 animals added in scenario 2 were genotyped in addition to the 1,000 animals from scenario 1. Genotypes for ungenotyped animals were predicted with an average accuracy of 0.58. Additionally, an adjustment of the diagonal elements of the G matrix was proposed for animals with predicted genotypes. The accuracy of genomic estimated breeding values for juvenile animals was the highest for the scenario with 2,000 genotyped animals, being 0.90, 0.79, and 0.60 for the heritabilities of 0.3, 0.05, and 0.01, respectively. Accuracies did not differ significantly between the scenario with 1,000 genotyped animals only and the scenario in which 1,000 ungenotyped animals were added and the adjustment of the G matrix was applied. The absence of significant increase in the accuracy of genomic estimated breeding values was attributed to the low accuracy of predicted genotypes. Although the differences were not significant, the difference between scenario 1 and 2 increased with decreasing heritability. Without the adjustment of the diagonal elements of the G matrix, accuracy decreased. Results suggest that inclusion of ungenotyped animals is only expected to enhance the accuracy of GS when the unknown genotypes can be predicted with high accuracy.
基因组选择 (GS) 可以为年轻动物获得准确的育种值,缩短世代间隔,加速遗传增益,从而降低经过验证的公牛的成本。然而,使用高密度单核苷酸多态性标记阵列对大量动物进行基因分型非常昂贵,因此,需要一种降低 GS 成本的方法。本研究旨在探讨扩大参考群体,无论是通过基因分型动物还是通过预测基因型的个体,对基因组估计育种值准确性的影响。模拟了一个奶牛群体,其中使用具有 100 头女儿的经过验证的公牛作为 GS 的参考群体。根据 100 头女儿的产量偏差可靠性模拟了公牛的表型记录。模拟性状的遗传力水平为个体女儿表现的 0.3、0.05 和 0.01。考虑了三种情况:(1)参考群体由 1000 只基因分型动物组成,(2)在参考群体中添加 1000 只未基因分型动物,(3)除了情况 1 中的 1000 只动物外,情况 2 中的 1000 只动物还进行了基因分型。未基因分型动物的基因型预测平均准确率为 0.58。此外,还提出了一种针对预测基因型动物的 G 矩阵对角元素的调整方法。对于幼年动物,基因组估计育种值的准确性最高,遗传力分别为 0.3、0.05 和 0.01 的情况下,准确性分别为 0.90、0.79 和 0.60。只有 1000 只基因分型动物的情况与添加 1000 只未基因分型动物且应用 G 矩阵调整的情况之间的准确性没有显著差异。基因组估计育种值准确性没有显著增加归因于预测基因型的准确性较低。尽管差异不显著,但随着遗传力的降低,方案 1 和方案 2 之间的差异增加。如果不调整 G 矩阵的对角元素,准确性会降低。结果表明,只有当未知基因型可以高精度预测时,包含未基因分型动物才有望提高 GS 的准确性。