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Prediction of hybrid performance in maize using molecular markers and joint analyses of hybrids and parental inbreds

机译:利用分子标记预测玉米杂种表现并进行杂种与亲本自交的联合分析

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摘要

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 × 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. Communicated by A. Charcosset.
机译:优良杂种的鉴定对于杂种育种计划的成功至关重要。但是,对自交系间所有可能杂交的现场评估需要极大的资源。因此,已经努力通过使用相关基因型和分子标记物的田间数据来预测杂种表现(HP)。在本研究中,主要目的是评估谱系信息的有用性,并结合一般结合能力(GCA)和亲本系本身表现对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,分别估计了杂种标记位点在杂种中的等位基因构型(在杂合基团中)的标记效应,以及估算的缺失AFLP标记数据用于基于标记的HP预测。使用混合线性模型对来自9个阶乘因子的400个玉米dent×火石杂种和79个近交亲本的不平衡田间数据进行了联合分析。用910 AFLP和256 SSR标记对近交系进行基因分型。通过交叉验证,对没有或一个亲本在测交中评估的杂种进行交叉验证,以评估预测效率(R 2 )。如果使用谱系和品系本身的数据,则对GCA的最佳线性无偏预测和特定的结合能力可使HP对这两个性状的预测效率最高(R 2 = 0.6-0.9)。但是,如果没有此类数据,则使用分子标记可以更有效地预测谷物产量的HP。基于标记的方法的其他修改没有明显的效果。我们的研究表明,对杂种和亲本近交系进行联合分析对于预测未经测试的杂种的性能具有很高的潜力。由A. Charcosset沟通。

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