Institute of Animal Science, CZ 104 01 Praha 10-Uhrineves, Czech Republic.
J Sci Food Agric. 2010 Aug 30;90(11):1765-73. doi: 10.1002/jsfa.4041.
The evaluation of an animal is based on production records, adjusted for environmental effects, which gives a reliable estimation of its breeding value. Highly reliable daughter yield deviations are used as inputs for genetic marker evaluation. Genetic variability is explained by particular loci and background polygenes, both of which are described by the genomic breeding value selection index. Automated genotyping enables the determination of many single-nucleotide polymorphisms (SNPs) and can increase the reliability of evaluation of young animals (from 0.30 if only the pedigree value is used to 0.60 when the genomic breeding value is applied). However, the introduction of SNPs requires a mixed model with a large number of regressors, in turn requiring new algorithms for the best linear unbiased prediction and BayesB. Here, we discuss a method that uses a genomic relationship matrix to estimate the genomic breeding value of animals directly, without regressors. A one-step procedure evaluates both genotyped and ungenotyped animals at the same time, and produces one common ranking of all animals in a whole population. An augmented pedigree-genomic relationship matrix and the removal of prerequisites produce more accurate evaluations of all connected animals.
动物的评估基于生产记录，并针对环境影响进行了调整，从而可以可靠地估计其育种值。高度可靠的女儿产量偏差被用作遗传标记评估的输入。遗传变异由特定的基因座和背景多基因解释，这两者都由基因组育种值选择指数描述。自动化基因分型可以确定许多单核苷酸多态性（SNP），并可以提高对年轻动物的评估的可靠性（从仅使用系谱值时的 0.30 增加到应用基因组育种值时的 0.60）。但是，SNP 的引入需要具有大量回归量的混合模型，这反过来又需要用于最佳线性无偏预测和 BayesB 的新算法。在这里，我们讨论了一种使用基因组关系矩阵直接估计动物基因组育种值的方法，而无需回归量。一步法同时评估已分型和未分型的动物，并对整个群体中的所有动物进行一次共同排名。扩充的系谱基因组关系矩阵和消除前提条件可以更准确地评估所有相关动物。
