Plant Genome. 2017 Nov;10(3). doi: 10.3835/plantgenome2017.05.0038.
Grain yield and semolina quality traits are essential selection criteria in durum wheat breeding. However, high phenotypic screening costs limit selection to relatively few breeding lines in late generations. This selection paradigm confers relatively low selection efficiency due to the advancement of undesirable lines into expensive yield trials for grain yield and quality trait testing. Marker-aided selection can enhance selection efficiency, especially for traits that are difficult or costly to phenotype. The aim of this study was to identify major quality trait quantitative trait loci (QTL) for marker-assisted selection (MAS) and to explore potential application of genomic selection (GS) in a durum wheat breeding program. In this study, genome-wide association mapping was conducted for five quality traits using 1184 lines from the North Dakota State University (NDSU) durum wheat breeding program. Several QTL associated with test weight, semolina color, and gluten strength were identified. Genomic selection models were developed and forward prediction accuracies of 0.27 to 0.66 were obtained for the five quality traits. Our results show the potential for grain and semolina quality traits to be selected more efficiently through MAS and GS with further refinement. Considerable opportunity exists to extend these techniques to other traits such as grain yield and agronomic characteristics, further improving breeding efficiency in durum cultivar development.
籽粒产量和粗粉品质性状是硬粒小麦育种的重要选择标准。然而,高表型筛选成本限制了在后期世代中对相对较少的育种群进行选择。由于不良品系进入昂贵的产量试验进行籽粒产量和品质性状测试,这种选择范式导致相对较低的选择效率。标记辅助选择可以提高选择效率,特别是对于那些难以或昂贵表型的性状。本研究的目的是鉴定主要的粗粉品质性状数量性状位点(QTL),以便进行标记辅助选择(MAS),并探索基因组选择(GS)在硬粒小麦育种计划中的潜在应用。本研究利用北达科他州立大学(NDSU)硬粒小麦育种计划的 1184 个品系,对五个品质性状进行了全基因组关联作图。鉴定出了与容重、粗粉颜色和面筋强度相关的多个 QTL。建立了基因组选择模型,五个品质性状的正向预测准确率为 0.27 至 0.66。我们的研究结果表明,通过 MAS 和 GS 可以更有效地选择籽粒和粗粉品质性状,进一步改进硬粒小麦品种的选育效率。通过将这些技术扩展到其他性状,如籽粒产量和农艺性状,可以进一步提高硬粒小麦品种的选育效率。