Institute of Plant Breeding, Seed Science and Population Genetics, University of Hohenheim, 70593 Stuttgart, Germany.
Theor Appl Genet. 2010 Jan;120(2):451-61. doi: 10.1007/s00122-009-1208-x. Epub 2009 Nov 15.
The identification of superior hybrids is important for the success of a hybrid breeding program. However, field evaluation of all possible crosses among inbred lines requires extremely large resources. Therefore, efforts have been made to predict hybrid performance (HP) by using field data of related genotypes and molecular markers. In the present study, the main objective was to assess the usefulness of pedigree information in combination with the covariance between general combining ability (GCA) and per se performance of parental lines for HP prediction. In addition, we compared the prediction efficiency of AFLP and SSR marker data, estimated marker effects separately for reciprocal allelic configurations (among heterotic groups) of heterozygous marker loci in hybrids, and imputed missing AFLP marker data for marker-based HP prediction. Unbalanced field data of 400 maize dent x flint hybrids from 9 factorials and of 79 inbred parents were subjected to joint analyses with mixed linear models. The inbreds were genotyped with 910 AFLP and 256 SSR markers. Efficiency of prediction (R (2)) was estimated by cross-validation for hybrids having no or one parent evaluated in testcrosses. Best linear unbiased prediction of GCA and specific combining ability resulted in the highest efficiencies for HP prediction for both traits (R (2) = 0.6-0.9), if pedigree and line per se data were used. However, without such data, HP for grain yield was more efficiently predicted using molecular markers. The additional modifications of the marker-based approaches had no clear effect. Our study showed the high potential of joint analyses of hybrids and parental inbred lines for the prediction of performance of untested hybrids.
优良杂种的鉴定对于杂种选育计划的成功至关重要。然而，评估自交系之间所有可能的杂交需要大量的资源。因此，人们努力利用相关基因型和分子标记的田间数据来预测杂种表现（HP）。本研究的主要目的是评估系谱信息与一般配合力（GCA）和亲本系自身表现之间的协方差相结合在 HP 预测中的有用性。此外，我们比较了 AFLP 和 SSR 标记数据的预测效率，分别估计杂种中杂合标记位点的正反交等位基因构型（杂种优势群内）的标记效应，并对基于标记的 HP 预测进行缺失 AFLP 标记数据的插补。9 个析因的 400 个玉米马齿型×硬质型杂种和 79 个自交系的不平衡田间数据用混合线性模型进行联合分析。自交系用 910 个 AFLP 和 256 个 SSR 标记进行基因型分析。对于在测验交中没有或只有一个亲本评估的杂种，通过交叉验证估计预测效率（R (2)）。如果使用系谱和系自身数据，预测 GCA 和特殊配合力的最佳线性无偏预测对两种性状的 HP 预测具有最高的效率（R (2) = 0.6-0.9）。然而，如果没有这些数据，使用分子标记可以更有效地预测籽粒产量的 HP。基于标记的方法的附加改进没有明显的效果。我们的研究表明，杂种和自交系亲本的联合分析在预测未测试杂种的表现方面具有很高的潜力。
