Animal Breeding and Genomics Centre, Wageningen UR Livestock Research, 8200 AB Lelystad, the Netherlands; Animal Breeding and Genomics Centre, Wageningen University, 6700 AH Wageningen, the Netherlands; Department of Genetics and Animal Breeding, Poznan University of Life Sciences, Wolynska 33, 60-637 Poznan, Poland.
Department of Genetics and Animal Breeding, Poznan University of Life Sciences, Wolynska 33, 60-637 Poznan, Poland.
J Dairy Sci. 2012 Sep;95(9):5412-5421. doi: 10.3168/jds.2012-5550.
Compared with traditional selection, the use of genomic information tends to increase the accuracy of estimated breeding values (EBV). The cause of this increase is, however, unknown. To explore this phenomenon, this study investigated whether the increase in accuracy when moving from traditional (AA) to genomic selection (GG) was mainly due to genotyping the reference population (GA) or the evaluated animals (AG). In it, a combined relationship matrix for simultaneous use of genotyped and ungenotyped animals was applied. A simulated data set reflected the dairy cattle population. Four differently designed (i.e., different average relationships within the reference population) small reference populations and 3 heritability levels were considered. The animals in the reference populations had high, moderate, low, and random (RND) relationships. The evaluated animals were juveniles. The small reference populations simulated difficult or expensive to measure traits (i.e., methane emission). The accuracy of selection was expressed as the reliability of (genomic) EBV and was predicted based on selection index theory using relationships. Connectedness between the reference populations and evaluated animals was calculated using the prediction error variance. Average (genomic) EBV reliabilities increased with heritability and with a decrease in the average relationship within the reference population. Reliabilities in AA and AG were lower than those in GG and were higher than those in GA (respectively, 0.039, 0.042, 0.052, and 0.048 for RND and a heritability of 0.01). Differences between AA and GA were small. Average connectedness with all animals in the reference population for all scenarios and reference populations ranged from 0.003 to 0.024; it was lowest when the animals were not genotyped (AA; e.g., 0.004 for RND) and highest when all the animals were genotyped (GG; e.g., 0.024 for RND). Differences present across designs of the reference populations were very small. Genomic relationships among animals in the reference population might be less important than those for the evaluated animals with no phenotypic observations. Thus, the main origin of the gain in accuracy when using genomic selection is due to genotyping the evaluated animals. However, genotyping only one group of animals will always yield less accurate estimates.
与传统选择相比,利用基因组信息往往会提高估计育种值(EBV)的准确性。然而,造成这种增加的原因尚不清楚。为了探究这一现象,本研究探讨了从传统选择(AA)转向基因组选择(GG)时,准确性的提高主要是由于参考群体(GA)还是评估动物(AG)的基因型检测所致。在研究中,应用了同时使用基因型和非基因型动物的综合关系矩阵。一个模拟数据集反映了奶牛群体。考虑了 4 种不同设计(即参考群体内平均关系不同)的小参考群体和 3 个遗传力水平。参考群体中的动物具有高、中、低和随机(RND)关系。评估动物为幼畜。小参考群体模拟了难以或昂贵的测量性状(即甲烷排放)。选择的准确性表示为(基因组)EBV 的可靠性,并基于使用关系的选择指数理论进行预测。参考群体和评估动物之间的连通性是通过预测误差方差来计算的。平均(基因组)EBV 可靠性随着遗传力的增加而增加,并且随着参考群体内平均关系的降低而增加。在 AA 和 AG 中的可靠性低于 GG 中的可靠性,并且高于 GA 中的可靠性(分别为 RND 和遗传力为 0.01 时为 0.039、0.042、0.052 和 0.048)。AA 与 GA 之间的差异很小。在所有情况下,所有参考群体中所有动物的平均连通性在所有场景和参考群体中范围从 0.003 到 0.024;当动物未基因型检测(AA;例如,RND 为 0.004)时最低,当所有动物均基因型检测(GG;例如,RND 为 0.024)时最高。参考群体设计之间存在的差异非常小。参考群体中动物之间的基因组关系可能不如具有无表型观察的评估动物的关系重要。因此,使用基因组选择时准确性提高的主要来源是由于对评估动物进行了基因型检测。然而,仅对一组动物进行基因型检测将始终产生不太准确的估计。