Comparison between genomic predictions using daughter yield deviation and conventional estimated breeding value as response variables
Comparison between genomic predictions using daughter yield deviation and conventional estimated breeding value as response variables
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DOI：
10.1111/j.1439-0388.2010.00878.x
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发表时间：
2010-12-01
影响因子：
2.6
通讯作者：
Su, G.
中科院分区：
文献类型：
--
作者：
Guo, G.;Lund, M. S.;Su, G.
本研究比较了基于模拟数据使用传统估计育种值（EBV）和子代产量偏差（DYD）作为响应变量的基因组预测。8个方案进行了模拟遗传力（0.05和0.30），每头公牛的女儿数（30，100，平均每头公牛100个不等的数字）和基因型公牛（所有或一半的公牛基因型）的数量。模拟的基因组长度为1200 cM，包含15 000个等间距的单核苷酸多态性（SNP）标记和500个随机分布的数量性状位点（QTL）。在模拟的情况下，EBV的方法是有效的，或略优于DYD的方法在预测育种值，依赖于模拟的情况和统计模型。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方法提供了类似的基因组估计育种值（GEBV）的可靠性，除了不相等的女儿和一半的父亲没有基因型的情况下，EBV方法是上级DYD方法（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（0.3-3.6%，平均为1.9%），并且在遗传力低，女儿数量少或不相等以及一半的父亲没有基因型的情况下更明显。此外，结果表明，GEBV和传统的父母平均值（PA）之间的相关性较低（对应于一个相对较大的增益，包括PA）时，使用DYD的方法比使用EBV的方法。因此，在大多数情况下，这两种方法导致类似的可靠性的指数相结合的GEBV和PA。这些结果表明，EBV可以用作基因组预测的替代响应变量。
P>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.