Prediction of hybrid performance in maize using molecular markers and joint analyses of hybrids and parental inbreds
Prediction of hybrid performance in maize using molecular markers and joint analyses of hybrids and parental inbreds
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DOI：
10.1007/s00122-009-1208-x
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发表时间：
2010-01-01
影响因子：
5.4
通讯作者：
Frisch, Matthias
中科院分区：
文献类型：
--
作者：
Schrag, Tobias A.;Moehring, Jens;Frisch, Matthias
上级杂种的鉴定对于杂种育种计划的成功是重要的。然而，对所有可能的自交系杂交的田间评价需要非常大的资源。因此，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）已经做出了努力。在本研究中，主要目的是评估的有用性的系谱信息结合一般配合力（GCA）和本身的性能的亲本系HP预测之间的协方差。此外，我们比较了AFLP和SSR标记数据的预测效率，估计标记效应分别为倒数等位基因配置（杂优势群之间）的杂合标记位点的杂交种，并插补缺失的AFLP标记数据标记为基础的HP预测。对9个单位的400个玉米杂交种和79个自交系亲本的不平衡田间资料进行了混合线性模型的联合分析。利用910个AFLP标记和256个SSR标记对供试自交系进行了基因分型。预测效率（R（2））估计交叉验证杂交没有或一个测试杂交评估的父母。用系谱和品系本身资料进行HP预测时，一般配合力和特殊配合力的最佳线性无偏预测效率最高（R（2）= 0.6-0.9）。然而，如果没有这样的数据，HP的粮食产量更有效地预测使用分子标记。对基于标记的方法的进一步修改没有明显的效果。我们的研究表明，高潜力的联合分析的杂交种和亲本自交系的性能预测未经测试的杂交种。
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.