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结合遗传和多维度分析以确定与水分短缺耐受性相关的解释性性状,作为小麦育种中检测耐旱基因型的间接选择工具。

Combining Genetic and Multidimensional Analyses to Identify Interpretive Traits Related to Water Shortage Tolerance as an Indirect Selection Tool for Detecting Genotypes of Drought Tolerance in Wheat Breeding.

作者信息

Al-Ashkar Ibrahim, Al-Suhaibani Nasser, Abdella Kamel, Sallam Mohammed, Alotaibi Majed, Seleiman Mahmoud F

机构信息

Plant Production Department, College of Food and Agriculture Sciences, King Saud University, Riyadh 11451, Saudi Arabia.

Agronomy Department, Faculty of Agriculture, Al-Azhar University, Cairo 11651, Egypt.

出版信息

Plants (Basel). 2021 May 7;10(5):931. doi: 10.3390/plants10050931.

Abstract

Water shortages have direct adverse effects on wheat productivity and growth worldwide, vertically and horizontally. Productivity may be promoted using water shortage-tolerant wheat genotypes. High-throughput tools have supported plant breeders in increasing the rate of stability of the genetic gain of interpretive traits for wheat productivity through multidimensional technical methods. We used 27 agrophysiological interpretive traits for grain yield (GY) of 25 bread wheat genotypes under water shortage stress conditions for two seasons. Genetic parameters and multidimensional analyses were used to identify genetic and phenotypic variations of the wheat genotypes used, combining these strategies effectively to achieve a balance. Considerable high genotypic variations were observed for 27 traits. Eleven interpretive traits related to GY had combined high heritability ( > 60%) and genetic gain (>20%), compared to GY, which showed moderate values both for heritability (57.60%) and genetic gain (16.89%). It was determined that six out of eleven traits (dry leaf weight (DLW), canopy temperature (CT), relative water content (RWC), flag leaf area (FLA), green leaves area (GLA) and leaf area index (LAI)) loaded the highest onto PC1 and PC2 (with scores of >0.27), and five of them had a positive trend with GY, while the CT trait had a negative correlation determined by principal component analysis (PCA). Genetic parameters and multidimensional analyses (PCA, stepwise regression, and path coefficient) showed that CT, RWC, GLA, and LAI were the most important interpretive traits for GY. Selection based on these four interpretive traits might improve genetic gain for GY in environments that are vulnerable to water shortages. The membership index and clustering analysis based on these four traits were significantly correlated, with some deviation, and classified genotypes into five groups. Highly tolerant, tolerant, intermediate, sensitive and highly sensitive clusters represented six, eight, two, three and six genotypes, respectively. The conclusions drawn from the membership index and clustering analysis, signifying that there were clear separations between the water shortage tolerance groups, were confirmed through discriminant analysis. MANOVA indicated that there were considerable variations between the five water shortage tolerance groups. The tolerated genotypes (DHL02, DHL30, DHL26, Misr1, Pavone-76 and DHL08) can be recommended as interesting new genetic sources for water shortage-tolerant wheat breeding programs.

摘要

水资源短缺在全球范围内对小麦的生产力和生长产生直接的不利影响,无论是纵向还是横向。使用耐旱小麦基因型可以提高生产力。高通量工具通过多维技术方法,支持植物育种者提高小麦生产力解释性性状遗传增益的稳定性。我们在两个季节的缺水胁迫条件下,对25个面包小麦基因型的27个农艺生理解释性性状进行了谷物产量(GY)研究。利用遗传参数和多维分析来识别所使用小麦基因型的遗传和表型变异,有效地结合这些策略以实现平衡。观察到27个性状存在相当大的基因型变异。与GY相比,与GY相关的11个解释性性状具有较高的遗传力(>60%)和遗传增益(>20%),而GY的遗传力(57.60%)和遗传增益(16.89%)均为中等值。确定11个性状中的6个(干叶重(DLW)、冠层温度(CT)、相对含水量(RWC)、旗叶面积(FLA)、绿叶面积(GLA)和叶面积指数(LAI))在主成分1和主成分2上的载荷最高(得分>0.27),其中5个与GY呈正趋势,而通过主成分分析(PCA)确定CT性状与GY呈负相关。遗传参数和多维分析(PCA、逐步回归和通径系数)表明,CT、RWC、GLA和LAI是GY最重要的解释性性状。基于这四个解释性性状进行选择,可能会在易受缺水影响的环境中提高GY的遗传增益。基于这四个性状的隶属函数值和聚类分析显著相关,但存在一些偏差,并将基因型分为五组。高度耐受、耐受、中等、敏感和高度敏感聚类分别代表6个、8个、2个、3个和6个基因型。通过判别分析证实了隶属函数值和聚类分析得出的结论,即缺水耐受组之间存在明显的区分。多变量方差分析表明,五个缺水耐受组之间存在相当大的差异。耐受基因型(DHL02、DHL30、DHL26、Misr1、Pavone - 76和DHL08)可推荐作为耐旱小麦育种计划中有趣的新遗传资源。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8757/8148561/1dd59981b856/plants-10-00931-g001.jpg

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