Ohio Agriculture Research and Development Center, The Ohio State University, 1680 Madison Ave., Wooster, OH, 44691, USA.
University of Virginia Tech, 185 Ag Quad Lane, Blacksburg, VA, 24061, USA.
Theor Appl Genet. 2016 Sep;129(9):1697-710. doi: 10.1007/s00122-016-2733-z. Epub 2016 Jun 4.
Based on the estimates of accuracy, genomic selection would be useful for selecting for improved trait values and trait stability for agronomic and quality traits in wheat. Trait values and trait stability estimated by two methods were generally independent indicating a breeder could select for both simultaneously. Genomic selection (GS) is a new marker-assisted selection tool for breeders to achieve higher genetic gain faster and cheaper. Breeders face challenges posed by genotype by environment interaction (GEI) pattern and selecting for trait stability. Obtaining trait stability is costly, as it requires data from multiple environments. There are few studies that evaluate the efficacy of GS for predicting trait stability. A soft winter wheat population of 273 lines was genotyped with 90 K single nucleotide polymorphism markers and phenotyped for four agronomic and seven quality traits. Additive main effect and multiplicative interaction (AMMI) model and Eberhart and Russell regression (ERR) were used to estimate trait stability. Significant GEI variation was observed and stable lines were identified for all traits in this study. The accuracy of GS ranged from 0.33 to 0.67 for most traits and trait stability. Accuracy of trait stability was greater than trait itself for yield (0.44 using AMMI versus 0.33) and heading date (0.65 using ERR versus 0.56). The opposite trend was observed for the other traits. GS did not predict the stability of the quality traits except for flour protein, lactic acid and softness equivalent. Significant GS accuracy for some trait stability indicated that stability was under genetic control for these traits. The magnitude of GS accuracies for all the traits and most of the trait stability index suggests the possibility of rapid selection for these trait and trait stability in wheat breeding.
基于准确性的估计,基因组选择将有助于选择提高小麦农艺和品质性状的性状值和性状稳定性。两种方法估计的性状值和性状稳定性通常是独立的,这表明育种者可以同时选择两者。基因组选择(GS)是一种新的标记辅助选择工具,可帮助育种者更快、更便宜地实现更高的遗传增益。育种者面临基因型与环境互作(GEI)模式和选择性状稳定性的挑战。获得性状稳定性是昂贵的,因为它需要来自多个环境的数据。很少有研究评估 GS 预测性状稳定性的效果。对 273 个系的软冬小麦群体进行了 90K 个单核苷酸多态性标记的基因型分析,并对四个农艺性状和七个品质性状进行了表型分析。采用加性主效应和乘法互作(AMMI)模型和 Eberhart 和 Russell 回归(ERR)来估计性状稳定性。在这项研究中,观察到了显著的 GEI 变异,并确定了所有性状的稳定系。GS 的准确性范围为大多数性状和性状稳定性的 0.33 到 0.67。在产量(使用 AMMI 为 0.44,使用 ERR 为 0.33)和抽穗期(使用 ERR 为 0.65,使用 ERR 为 0.56)方面,性状稳定性的准确性大于性状本身。对于其他性状,观察到相反的趋势。GS 不能预测品质性状的稳定性,除了面粉蛋白、乳酸和柔软度当量。一些性状稳定性的 GS 准确性显著表明,这些性状的稳定性受遗传控制。所有性状和大多数性状稳定性指数的 GS 准确性幅度表明,在小麦育种中,对这些性状和性状稳定性进行快速选择是可能的。