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利用GGE模型和混合线性模型方法对面包小麦基因型的晚熟α-淀粉酶活性进行遗传分析,并利用AMMI双标图进行稳定性分析。

Genetic analyses using GGE model and a mixed linear model approach, and stability analyses using AMMI bi-plot for late-maturity alpha-amylase activity in bread wheat genotypes.

作者信息

Rasul Golam, Glover Karl D, Krishnan Padmanaban G, Wu Jixiang, Berzonsky William A, Fofana Bourlaye

机构信息

Department of Plant Science, South Dakota State University, Brookings, SD, 57006, USA.

Dairy and Food Science Department, South Dakota State University, Brookings, SD, 57007, USA.

出版信息

Genetica. 2017 Jun;145(3):259-268. doi: 10.1007/s10709-017-9962-1. Epub 2017 Mar 17.

Abstract

Low falling number and discounting grain when it is downgraded in class are the consequences of excessive late-maturity α-amylase activity (LMAA) in bread wheat (Triticum aestivum L.). Grain expressing high LMAA produces poorer quality bread products. To effectively breed for low LMAA, it is necessary to understand what genes control it and how they are expressed, particularly when genotypes are grown in different environments. In this study, an International Collection (IC) of 18 spring wheat genotypes and another set of 15 spring wheat cultivars adapted to South Dakota (SD), USA were assessed to characterize the genetic component of LMAA over 5 and 13 environments, respectively. The data were analysed using a GGE model with a mixed linear model approach and stability analysis was presented using an AMMI bi-plot on R software. All estimated variance components and their proportions to the total phenotypic variance were highly significant for both sets of genotypes, which were validated by the AMMI model analysis. Broad-sense heritability for LMAA was higher in SD adapted cultivars (53%) compared to that in IC (49%). Significant genetic effects and stability analyses showed some genotypes, e.g. 'Lancer', 'Chester' and 'LoSprout' from IC, and 'Alsen', 'Traverse' and 'Forefront' from SD cultivars could be used as parents to develop new cultivars expressing low levels of LMAA. Stability analysis using an AMMI bi-plot revealed that 'Chester', 'Lancer' and 'Advance' were the most stable across environments, while in contrast, 'Kinsman', 'Lerma52' and 'Traverse' exhibited the lowest stability for LMAA across environments.

摘要

降落数值低以及谷物等级下降时被拒收是面包小麦(普通小麦)中晚期成熟α-淀粉酶活性(LMAA)过高的后果。表现出高LMAA的谷物制成的面包产品质量较差。为了有效地培育低LMAA的品种,有必要了解控制它的基因以及它们如何表达,特别是当基因型在不同环境中生长时。在本研究中,分别对18个春小麦基因型的国际收集品(IC)和另一组适应美国南达科他州(SD)的15个春小麦品种进行了评估,以分别在5个和13个环境中表征LMAA的遗传成分。使用混合线性模型方法的GGE模型分析数据,并使用R软件上的AMMI双标图进行稳定性分析。两组基因型的所有估计方差分量及其占总表型方差的比例均高度显著,这通过AMMI模型分析得到了验证。与IC中的广义遗传力(49%)相比,适应SD的品种中LMAA的广义遗传力更高(53%)。显著的遗传效应和稳定性分析表明,一些基因型,例如IC中的“Lancer”、“Chester”和“LoSprout”,以及SD品种中的“Alsen”、“Traverse”和“Forefront”,可作为亲本用于培育表达低水平LMAA的新品种。使用AMMI双标图的稳定性分析表明,“Chester”、“Lancer”和“Advance”在各环境中最稳定,而相比之下,“Kinsman”、“Lerma52”和“Traverse”在各环境中LMAA的稳定性最低。

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