Improving resistance to the European corn borer: a comprehensive study in elite maize using QTL mapping and genome-wide prediction
Improving resistance to the European corn borer: a comprehensive study in elite maize using QTL mapping and genome-wide prediction
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DOI：
10.1007/s00122-015-2477-1
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发表时间：
2015-05-01
影响因子：
5.4
通讯作者：
Schoen, Chris-Carolin
中科院分区：
文献类型：
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作者：
Foiada, Flavio;Westermeier, Peter;Schoen, Chris-Carolin
标记辅助选择（Marker-assisted selection，MAS）是一种有效的改良玉米抗欧洲玉米螟（European corn borer，ECB）性的方法。在这项研究中，我们调查了性能的全基因组为基础的选择，相对于选择的基础上，个别数量性状基因座（QTL），欧洲精英玉米抗ECB秸秆损害。2011年，用高密度单核苷酸多态性标记对三个相连的双亲群体（包括590个双单倍体（DH）系）进行基因分型，并在人工和自然侵染下进行表型分析。第二年，对195个DH系的子集进行了评估，作为系本身和测交。抗性是根据茎杆损伤等级、茎杆中的饲喂隧道数量和隧道长度来评估的。我们进行了个体和联合群体QTL分析，并将QTL模型的交叉验证预测能力与基因组最佳线性无偏预测（GBLUP）进行了比较。对于所有性状，GBLUP模型始终优于QTL模型，尽管检测到的QTL具有相当大的影响。对于秸秆损伤等级，GBLUP的预测能力超过0.70倍。基于DH系本身表现的模型训练可以有效预测测交试验中的断秆率。我们的结论是，从QTL为基础的进展到全基因组的方法时，可以大大提高MAS的效率ECB茎损伤抗性。随着欧洲优良玉米种质中天然ECB抗性的可用性，我们的研究结果为实施基于基因组的综合选择方法同时提高产量，成熟度和ECB抗性开辟了途径。
The efficiency of marker-assisted selection for native resistance to European corn borer stalk damage can be increased when progressing from a QTL-based towards a genome-wide approach.Marker-assisted selection (MAS) has been shown to be effective in improving resistance to the European corn borer (ECB) in maize. In this study, we investigated the performance of whole-genome-based selection, relative to selection based on individual quantitative trait loci (QTL), for resistance to ECB stalk damage in European elite maize. Three connected biparental populations, comprising 590 doubled haploid (DH) lines, were genotyped with high-density single nucleotide polymorphism markers and phenotyped under artificial and natural infestation in 2011. A subset of 195 DH lines was evaluated in the following year as lines per se and as testcrosses. Resistance was evaluated based on stalk damage ratings, the number of feeding tunnels in the stalk and tunnel length. We performed individual- and joint-population QTL analyses and compared the cross-validated predictive abilities of the QTL models with genomic best linear unbiased prediction (GBLUP). For all traits, the GBLUP model consistently outperformed the QTL model despite the detection of QTL with sizeable effects. For stalk damage rating, GBLUP's predictive ability exceeded at times 0.70. Model training based on DH line per se performance was efficient in predicting stalk breakage in testcrosses. We conclude that the efficiency of MAS for ECB stalk damage resistance can be increased considerably when progressing from a QTL-based towards a genome-wide approach. With the availability of native ECB resistance in elite European maize germplasm, our results open up avenues for the implementation of an integrated genome-based selection approach for the simultaneous improvement of yield, maturity and ECB resistance.