Increased accuracy of artificial selection by using the realized relationship matrix
Increased accuracy of artificial selection by using the realized relationship matrix
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DOI：
10.1017/s0016672308009981
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发表时间：
2009-02-01
影响因子：
1.5
通讯作者：
Goddard, M. E.
中科院分区：
文献类型：
--
作者：
Hayes, B. J.;Visscher, P. M.;Goddard, M. E.
密集标记基因型允许构建个体之间的实现关系矩阵，其中元件是成对或个体之间通过血统（IBD）相同的基因组的实现比例。在本文中，我们证明，通过取代平均关系矩阵来自系谱与实现的关系矩阵中的最佳线性无偏预测（BLUP）的育种值，育种值的准确性可以大大提高，特别是对个人没有自己的表型。我们进一步证明，这种方法的预测育种值是完全等同于基因组选择方法，其中的数量性状基因座（QTL）的影响，有助于性状的变化被假定为正态分布。使用BLUP方程中的实现关系矩阵预测的育种值的准确性可以确定性地预测已知的家庭关系，例如半同胞。确定性方法使用控制表型的独立分离基因座的有效数量，这取决于家族关系的类型和基因组的长度。预测育种值的准确性取决于有效位点的数量、家系关系和表型记录的数量。确定性预测表明，育种值的准确性可以接近统一，如果足够的亲属基因型和表型。例如，当对每个家系1000个全同胞进行基因分型和表型分析时，该性状的遗传力为0.5，则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。仿真结果验证了上述结论。一个确定性的预测也来自随机交配群体，其中有效的人口规模是决定独立分离位点的有效数量的关键参数。如果有效群体规模很大，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未表型个体的育种值。如果性状的遗传力为0.3，N-e = 1000，则需要大约5750个具有基因型和表型的个体才能以0.7的精度预测同一群体中未表型个体的GEBV。
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 (I BD) between pairs or 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 predictedgenomic 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 = 1000, approximately 5750 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.