General Combining Ability Model for Genomewide Selection in a Biparental Cross
General Combining Ability Model for Genomewide Selection in a Biparental Cross
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DOI：
10.2135/cropsci2013.11.0774
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发表时间：
2014-05-01
期刊：
影响因子：
2.3
通讯作者：
Bernardo, Rex
中科院分区：
文献类型：
--
作者：
Jacobson, Amy;Lian, Lian;Bernardo, Rex
在A/B双亲杂交中的全基因组选择是最有利的，如果它可以在杂交表型确定之前有效地进行。我们的目标是确定一般配合力（GCA）模型是否适用于A/B杂交的全基因组选择，并评估训练群体大小（N-GCA）、合并到训练群体中的杂交数（N-x）、连锁不平衡（r（2））和遗传力（h（2））对GCA模型预测精度的影响。GCA模型涉及将4至38个具有A和B作为亲本之一的玉米杂交组合汇集到A/B杂交的训练群体中，而相同背景（SB）模型涉及汇集随机近交系之间的杂交组合。在30个A/B试验群体中，采用一般配合力模型的平均选择反应（R）为测交籽粒产量0.19 Mg ha（-1），水分-6 g kg（-1），试验重量0.38 kg hL（-1）。这些R值与GCA模型是68至76%的相应R值与表型选择（PS）。SB模型的R值仅为PS模型R值的15 - 28%。用来自同一杂种优势群的随机杂交来增加训练群体的规模不如包括以A和B作为亲本之一的杂交来增加训练群体的规模重要。预测精度与h（2）r（2）root N-GCA和h（2）r（2）root N-x的相关性最高。我们的研究结果表明，一般配合力模型是常规有效的全基因组选择内A/B杂交，表型的杂交后代。
Genomewide selection within an A/B biparental cross is most advantageous if it could be effectively done before the cross is phenotyped. Our objectives were to determine if a general combining ability (GCA) model is useful for genomewide selection in an A/B cross, and to assess the influence of training population size (N-GCA), number of crosses pooled into the training population (N-x), linkage disequilibrium (r(2)), and heritability (h(2)) on the prediction accuracy with the GCA model. The GCA model involved pooling 4 to 38 maize crosses with A and B as one of the parents into the training population for an A/B cross, whereas the same background (SB) model involved pooling crosses between random inbreds. Across 30 A/B test populations, the mean response to selection (R) with the GCA model was 0.19 Mg ha(-1) for testcross grain yield, -6 g kg(-1) for moisture, and 0.38 kg hL(-1) for test weight. These R values with the GCA model were 68 to 76% of the corresponding R values with phenotypic selection (PS). The R values with the SB model were only 15 to 28% of the R values with PS. Increasing the size of the training population with random crosses from the same heterotic group was less important than including crosses with A and B as one of the parents. Prediction accuracy was most highly correlated with h(2)r(2) root N-GCA and h(2)r(2) root N-x. Our results indicated that the GCA model is routinely effective for genomewide selection within A/B crosses, before phenotyping the progeny in the cross.