Hayes B J, Visscher P M, Goddard M E
Biosciences Research Division, Department of Primary Industries Victoria, 1 Park Drive, Bundoora 3083, Australia.
Genet Res (Camb). 2009 Feb;91(1):47-60. doi: 10.1017/S0016672308009981.
Dense marker genotypes allow the construction of the realized relationship matrix between individuals, with elements the realized proportion of the genome that is identical by descent (IBD) between pairs of individuals. In this paper, we demonstrate that by replacing the average relationship matrix derived from pedigree with the realized relationship matrix in best linear unbiased prediction (BLUP) of breeding values, the accuracy of the breeding values can be substantially increased, especially for individuals with no phenotype of their own. We further demonstrate that this method of predicting breeding values is exactly equivalent to the genomic selection methodology where the effects of quantitative trait loci (QTLs) contributing to variation in the trait are assumed to be normally distributed. The accuracy of breeding values predicted using the realized relationship matrix in the BLUP equations can be deterministically predicted for known family relationships, for example half sibs. The deterministic method uses the effective number of independently segregating loci controlling the phenotype that depends on the type of family relationship and the length of the genome. The accuracy of predicted breeding values depends on this number of effective loci, the family relationship and the number of phenotypic records. The deterministic prediction demonstrates that the accuracy of breeding values can approach unity if enough relatives are genotyped and phenotyped. For example, when 1000 full sibs per family were genotyped and phenotyped, and the heritability of the trait was 0.5, the reliability of predicted genomic breeding values (GEBVs) for individuals in the same full sib family without phenotypes was 0.82. These results were verified by simulation. A deterministic prediction was also derived for random mating populations, where the effective population size is the key parameter determining the effective number of independently segregating loci. If the effective population size is large, a very large number of individuals must be genotyped and phenotyped in order to accurately predict breeding values for unphenotyped individuals from the same population. If the heritability of the trait is 0.3, and N(e)=100, approximately 12474 individuals with genotypes and phenotypes are required in order to predict GEBVs of un-phenotyped individuals in the same population with an accuracy of 0.7 [corrected].
高密度标记基因型能够构建个体间的实现关系矩阵，其元素为个体对之间通过家系遗传相同（IBD）的基因组实现比例。在本文中，我们证明，在育种值的最佳线性无偏预测（BLUP）中，用实现关系矩阵替代从系谱得出的平均关系矩阵，可大幅提高育种值的准确性，特别是对于没有自身表型的个体。我们进一步证明，这种预测育种值的方法与基因组选择方法完全等效，在基因组选择方法中，假定影响性状变异的数量性状位点（QTL）的效应呈正态分布。对于已知的家系关系，例如半同胞，可确定性地预测在BLUP方程中使用实现关系矩阵预测的育种值的准确性。确定性方法使用控制表型的独立分离位点的有效数量，该数量取决于家系关系类型和基因组长度。预测育种值的准确性取决于有效位点数、家系关系和表型记录数。确定性预测表明，如果对足够多的亲属进行基因分型和表型分型，育种值的准确性可接近1。例如，当每个家系对1000个全同胞进行基因分型和表型分型，且性状的遗传力为0.5时，同一全同胞家系中无表型个体的预测基因组育种值（GEBV）的可靠性为0.82。这些结果通过模拟得到验证。还针对随机交配群体推导了确定性预测，其中有效群体大小是决定独立分离位点有效数量的关键参数。如果有效群体大小很大，则必须对非常大量的个体进行基因分型和表型分型，以便准确预测来自同一群体的无表型个体的育种值。如果性状的遗传力为0.3，且N(e)=100，则大约需要12474个具有基因型和表型的个体，以便以0.7的准确性预测同一群体中无表型个体的GEBV [已校正] 。
