Department of Agronomy and Plant Genetics, University of Minnesota, 411 Borlaug Hall, 1991 Upper Buford Circle, Saint Paul, MN 55108, USA.
Theor Appl Genet. 2013 Jan;126(1):13-22. doi: 10.1007/s00122-012-1955-y. Epub 2012 Aug 11.
Maize (Zea mays L.) breeders evaluate many single-cross hybrids each year in multiple environments. Our objective was to determine the usefulness of genomewide predictions, based on marker effects from maize single-cross data, for identifying the best untested single crosses and the best inbreds within a biparental cross. We considered 479 experimental maize single crosses between 59 Iowa Stiff Stalk Synthetic (BSSS) inbreds and 44 non-BSSS inbreds. The single crosses were evaluated in multilocation experiments from 2001 to 2009 and the BSSS and non-BSSS inbreds had genotypic data for 669 single nucleotide polymorphism (SNP) markers. Single-cross performance was predicted by a previous best linear unbiased prediction (BLUP) approach that utilized marker-based relatedness and information on relatives, and from genomewide marker effects calculated by ridge-regression BLUP (RR-BLUP). With BLUP, the mean prediction accuracy (r(MG)) of single-cross performance was 0.87 for grain yield, 0.90 for grain moisture, 0.69 for stalk lodging, and 0.84 for root lodging. The BLUP and RR-BLUP models did not lead to r(MG) values that differed significantly. We then used the RR-BLUP model, developed from single-cross data, to predict the performance of testcrosses within 14 biparental populations. The r(MG) values within each testcross population were generally low and were often negative. These results were obtained despite the above-average level of linkage disequilibrium, i.e., r(2) between adjacent markers of 0.35 in the BSSS inbreds and 0.26 in the non-BSSS inbreds. Overall, our results suggested that genomewide marker effects estimated from maize single crosses are not advantageous (cofmpared with BLUP) for predicting single-cross performance and have erratic usefulness for predicting testcross performance within a biparental cross.
玉米（Zea mays L.）育种家每年在多个环境中评估许多单交种。我们的目标是确定基于玉米单交数据的标记效应的全基因组预测在识别最佳未测试的单交种和双亲杂交中的最佳自交系方面的有用性。我们考虑了 59 个爱荷华硬秆合成群体（BSSS）自交系和 44 个非 BSSS 自交系之间的 479 个实验性玉米单交种。这些单交种在 2001 年至 2009 年的多点试验中进行了评估，BSSS 和非 BSSS 自交系具有 669 个单核苷酸多态性（SNP）标记的基因型数据。单交种的表现通过先前的最佳线性无偏预测（BLUP）方法进行预测，该方法利用了基于标记的亲缘关系和亲属信息，以及通过基于岭回归的 BLUP（RR-BLUP）计算的全基因组标记效应。通过 BLUP，单交种产量的平均预测准确性（r（MG））为 0.87，籽粒水分含量为 0.90，茎倒伏为 0.69，根倒伏为 0.84。BLUP 和 RR-BLUP 模型并没有导致 r（MG）值显著不同。然后，我们使用 RR-BLUP 模型，该模型是从单交种数据中开发的，来预测 14 个双亲杂交群体内的测验种的表现。每个测验种群体内的 r（MG）值通常较低，并且经常为负值。尽管存在平均以上水平的连锁不平衡，即 BSSS 自交系中相邻标记之间的 r（2）为 0.35，非 BSSS 自交系中为 0.26，但仍获得了这些结果。总体而言，我们的结果表明，从玉米单交种中估计的全基因组标记效应在预测单交种表现方面没有优势（与 BLUP 相比），并且在预测双亲杂交中的测验种表现方面具有不稳定的有用性。
