Department of Genetics and Biotechnology, Faculty of Agricultural Sciences, Aarhus University, Tjele, Denmark.
J Anim Breed Genet. 2010 Dec;127(6):423-32. doi: 10.1111/j.1439-0388.2010.00878.x.
This study compared genomic predictions using conventional estimated breeding values (EBV) and daughter yield deviations (DYD) as response variables based on simulated data. Eight scenarios were simulated in regard to heritability (0.05 and 0.30), number of daughters per sire (30, 100, and unequal numbers with an average of 100 per sire) and numbers of genotyped sires (all or half of sires were genotyped). The simulated genome had a length of 1200 cM with 15,000 equally spaced Single-nucleotide polymorphism (SNP) markers and 500 randomly distributed Quantitative trait locus (QTL). In the simulated scenarios, the EBV approach was as effective as or slightly better than the DYD approach at predicting breeding value, dependent on simulated scenarios and statistical models. Applying a Bayesian common prior model (the same prior distribution of marker effect variance) and a linear mixed model (GBLUP), the EBV and DYD approaches provided similar genomic estimated breeding value (GEBV) reliabilities, except for scenarios with unequal numbers of daughters and half of sires without genotype, for which the EBV approach was superior to the DYD approach (by 1.2 and 2.4%). Using a Bayesian mixture prior model (mixture prior distribution of marker effect variance), the EBV approach resulted in slightly higher reliabilities of GEBV than the DYD approach (by 0.3-3.6% with an average of 1.9%), and more obvious in scenarios with low heritability, small or unequal numbers of daughters, and half of sires without genotype. Moreover, the results showed that the correlation between GEBV and conventional parent average (PA) was lower (corresponding to a relatively larger gain by including PA) when using the DYD approach than when using the EBV approach. Consequently, the two approaches led to similar reliability of an index combining GEBV and PA in most scenarios. These results indicate that EBV can be used as an alternative response variable for genomic prediction.
本研究比较了基于模拟数据，以常规估计育种值（EBV）和女儿产量偏差（DYD）作为响应变量的基因组预测。在 8 种模拟方案中，遗传力（0.05 和 0.30）、每个父本的女儿数量（30、100 和不相等数量，平均每个父本 100 个）和被基因分型的父本数量（所有或一半的父本被基因分型）都有所不同。模拟基因组的长度为 1200cM，有 15000 个等距的单核苷酸多态性（SNP）标记和 500 个随机分布的数量性状基因座（QTL）。在模拟场景中，EBV 方法在预测育种值方面与 DYD 方法一样有效，或者稍微更好，这取决于模拟场景和统计模型。应用贝叶斯共同先验模型（标记效应方差的相同先验分布）和线性混合模型（GBLUP），EBV 和 DYD 方法提供了相似的基因组估计育种值（GEBV）可靠性，除了女儿数量不等和一半没有基因型的父本的情况外，EBV 方法优于 DYD 方法（高 1.2 和 2.4%）。使用贝叶斯混合先验模型（标记效应方差的混合先验分布），EBV 方法导致 GEBV 的可靠性略高于 DYD 方法（平均高 0.3-3.6%，平均高 1.9%），在遗传力低、女儿数量小或不等、一半父本没有基因型的情况下更为明显。此外，结果表明，当使用 DYD 方法时，GEBV 与常规亲本平均值（PA）之间的相关性较低（通过包含 PA 获得的增益相应较大），而当使用 EBV 方法时，GEBV 与 PA 之间的相关性较高。因此，在大多数情况下，这两种方法导致 GEBV 和 PA 组合指数的可靠性相似。这些结果表明，EBV 可以用作基因组预测的替代响应变量。
