Department of Agricultural Sciences, University of Helsinki, Helsinki, Finland.
J Dairy Sci. 2013 Aug;96(8):5364-75. doi: 10.3168/jds.2012-6523. Epub 2013 Jun 13.
Different approaches of calculating genomic measures of relationship were explored and compared with pedigree relationships (A) within and across base breeds in a crossbreed population, using genotypes for 38,194 loci of 4,106 Nordic Red dairy cattle. Four genomic relationship matrices (G) were calculated using either observed allele frequencies (AF) across breeds or within-breed AF. The G matrices were compared separately when the AF were estimated in the observed and in the base population. Breedwise AF in the current and base population were estimated using linear regression models of individual genotypes on breed composition. Different G matrices were further used to predict direct estimated genomic values using a genomic BLUP model. Higher variability existed in the diagonal elements of G across breeds (standard deviation=0.06, on average) compared with A (0.01). The use of simple observed AF across base breeds to compute G increased coefficients for individuals in distantly related populations. Estimated breedwise AF reduced differences in coefficients similarly within and across populations. The variability of the current adjusted G matrix decreased from 0.055 to 0.035 when breedwise AF were estimated from the base breed population. The direct estimated genomic values and their validation reliabilities were, however, unaffected by AF used to compute G when estimated with a genomic BLUP model, due to inclusion of breed means in the model. In multibreed populations, G adjusted with breedwise AF from the founder population may provide more consistency among relationship coefficients between genotyped and ungenotyped individuals in an across-breed single-step evaluation.
探索了计算基因组亲缘关系度量的不同方法,并与杂种群体中系谱关系(A)进行了比较和比较,使用了 4106 头北欧红牛的 38194 个基因座的基因型。使用跨品种或品种内观察到的等位基因频率(AF)计算了四个基因组关系矩阵(G)。当在观察到的和基础群体中估计 AF 时,分别比较了 G 矩阵。使用个体基因型对品种组成的线性回归模型估计了当前和基础群体中的品种 AF。进一步使用不同的 G 矩阵使用基因组 BLUP 模型预测直接估计的基因组值。与 A(0.01)相比,跨品种的 G 对角线元素的变异性更高(平均值为 0.06)。使用跨基础品种简单观察到的 AF 来计算 G 增加了远距离相关群体中个体的系数。在同一和跨种群内,估计的品种 AF 同样降低了系数之间的差异。当从基础品种群体中估计品种 AF 时,当前调整后的 G 矩阵的变异性从 0.055 降低到 0.035。然而,由于模型中包含了品种均值,因此使用基因组 BLUP 模型估计的 G 时,直接估计的基因组值及其验证可靠性不受用于计算 G 的 AF 的影响。在多品种群体中,使用从基础品种群体中的品种 AF 调整的 G 可能会在跨品种单步评估中提供基因型和非基因型个体之间关系系数之间的更大一致性。