Beukert Ulrike, Thorwarth Patrick, Zhao Yusheng, Longin C Friedrich H, Serfling Albrecht, Ordon Frank, Reif Jochen C
Institute for Resistance Research and Stress Tolerance, Julius Kuehn-Institute (JKI) - Federal Research Centre for Cultivated Plants, Quedlinburg, Germany.
State Plant Breeding Institute, University of Hohenheim, Stuttgart, Germany.
Front Plant Sci. 2020 Oct 28;11:594113. doi: 10.3389/fpls.2020.594113. eCollection 2020.
Improving leaf rust and stripe rust resistance is a central goal in wheat breeding. The objectives of this study were to (1) elucidate the genetic basis of leaf rust and stripe rust resistance in a hybrid wheat population, (2) compare the findings using a previously published hybrid wheat data set, and (3) contrast the prediction accuracy with those of genome-wide prediction. The hybrid wheat population included 1,744 single crosses from 236 parental lines. The genotypes were fingerprinted using a 15k SNP array and evaluated for leaf rust and stripe rust resistance in multi-location field trials. We observed a high congruency of putative quantitative trait loci (QTL) for leaf rust resistance between both populations. This was not the case for stripe rust resistance. Accordingly, prediction accuracy of the detected QTL was moderate for leaf rust but low for stripe rust resistance. Genome-wide selection increased the prediction accuracy slightly for stripe rust albeit at a low level but not for leaf rust. Thus, our findings suggest that marker-assisted selection seems to be a robust and efficient tool to improve leaf rust resistance in European wheat hybrids.
提高叶锈病和条锈病抗性是小麦育种的核心目标。本研究的目的是：（1）阐明一个杂交小麦群体中叶锈病和条锈病抗性的遗传基础；（2）使用先前发表的杂交小麦数据集比较研究结果；（3）将预测准确性与全基因组预测的准确性进行对比。该杂交小麦群体包括来自236个亲本系的1744个单交组合。利用一个15k SNP芯片对基因型进行指纹识别，并在多地点田间试验中对叶锈病和条锈病抗性进行评估。我们观察到两个群体之间叶锈病抗性的假定数量性状位点（QTL）高度一致。条锈病抗性则并非如此。因此，检测到的QTL对叶锈病的预测准确性中等，但对条锈病抗性的预测准确性较低。全基因组选择对条锈病的预测准确性略有提高，尽管水平较低，但对叶锈病没有提高。因此，我们的研究结果表明，标记辅助选择似乎是提高欧洲小麦杂交种叶锈病抗性的一种可靠且有效的工具。
