Onogi A, Ogino A, Komatsu T, Shoji N, Simizu K, Kurogi K, Yasumori T, Togashi K, Iwata H
Department of Agricultural and Environmental Biology, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo 113-8657, Japan.
J Anim Sci. 2014 May;92(5):1931-8. doi: 10.2527/jas.2014-7168.
The implementation of genomic selection for Japanese Black cattle, known for rich marbling of their meat, is now being explored. Although multiple-step methods are often adopted for dairy cattle, they present shortcomings such as bias and loss of information in addition to operational complexity. These can be avoided using single-step genomic BLUP (ssGBLUP) based on the relationship matrix H, which is constructed from the numerator relationship matrix (A) augmented by the genomic relationship matrix (G). This study assessed the use of ssGBLUP for 3 economically important traits in Japanese Black cattle. Three aspects of ssGBLUP that are important for practical use were examined specifically: the mixing proportions of blending G with A, selection of subsets of genotyped animals used for constructing H, and prediction ability for ungenotyped animals. Different mixing proportions were tested to assess the influence of these proportions on variance component estimation and prediction accuracy. For all traits, the highest or nearly highest accuracy was obtained when the adopted mixing proportion provided heritability closest to that inferred based on A. However, the accuracy did not increase greatly under adjustment of the mixing proportion, thereby suggesting that the influence of the mixing proportion on the accuracy was limited. Genotype data of influential bulls showed a greater contribution to accuracy than that of bulls that were less influential. Genotyping animals with phenotypic records increased the accuracy. It can be prioritized over genotyping bulls that are not influential on the population. These results are expected to present good guides to the future expansion of genotyped populations. Even for animals without genotype data but with genotyped sires, ssGBLUP provided more accurate prediction than BLUP did. For both phenotype and breeding value prediction, ssGBLUP provides more accurate prediction than BLUP, suggesting its usefulness in genomic selection in Japanese Black cattle.
日本黑牛以其丰富的大理石花纹肉而闻名,目前正在探索对其实施基因组选择。虽然奶牛通常采用多步方法,但这些方法除了操作复杂外,还存在偏差和信息丢失等缺点。使用基于关系矩阵H的单步基因组最佳线性无偏预测(ssGBLUP)可以避免这些问题,关系矩阵H由分子关系矩阵(A)通过基因组关系矩阵(G)扩充构建而成。本研究评估了ssGBLUP在日本黑牛三个重要经济性状上的应用。具体考察了ssGBLUP在实际应用中重要的三个方面:G与A的混合比例、用于构建H的基因分型动物子集的选择以及对未基因分型动物的预测能力。测试了不同的混合比例,以评估这些比例对方差成分估计和预测准确性的影响。对于所有性状,当采用的混合比例提供的遗传力最接近基于A推断的遗传力时,可获得最高或几乎最高的准确性。然而,在调整混合比例时,准确性并没有大幅提高,这表明混合比例对准确性的影响有限。有影响力的公牛的基因型数据对准确性的贡献大于影响力较小的公牛。对具有表型记录的动物进行基因分型提高了准确性。它可以优先于对群体没有影响力的公牛进行基因分型。这些结果有望为未来基因分型群体的扩大提供良好的指导。即使对于没有基因型数据但有基因分型父系的动物,ssGBLUP也比最佳线性无偏预测(BLUP)提供更准确的预测。对于表型和育种值预测,ssGBLUP都比BLUP提供更准确的预测,表明其在日本黑牛基因组选择中的有用性。