Integrating Phenotypic Evaluation and SNP Marker-Based Genomic Analysis for the Identification of Drought-Tolerant Wheat Genotypes

Document Type : Research Paper

Authors

1 College of Agriculture, Shahid Bahonar University of Kerman, Kerman, Iran

2 , Research and Technology Institute of Plant Production, Afzalipour Research Institute, Shahid Bahonar University of Kerman, Kerman, Iran

3 Deparment of Plant Productin and Genetics, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, Iran

4 5Assistant Professor, Department of Water Engineering, Shahid Bahonar University of Kerman, Kerman, Iran

5 Department of Genetics and Plant Breeding, College of Agriculture, Tarbiat Modares University, Tehran, Iran

6 Department of Plant Production and Genetics, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, Iran

7 Department of Soil Sciences and Water Resources, College of Agriculture, University of Basrah, Iraq

8 , Research and Technology Institute of Plant Production (RTIPP), Afzalipour Research Institute, Shahid Bahonar University of Kerman, Kerman, Iran

9 Genebank Department, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany

10 Department of Biological and Environmental Sciences, College of Arts and Sciences, Qatar University, Doha, Qatar

Abstract

Objective: Drought is one of the abiotic stresses that reduces yield in agricultural crops, especially wheat in arid and semi-arid regions of the world. Evaluation of agronomic and physiological traits under drought stress conditions is useful for identifying traits affecting grain yield and drought-tolerant genotypes for use in breeding programs..
Methods: In this study, in order to evaluate grain yield potential and select drought-tolerant genotypes, 255 bread wheat genotypes were assessed under normal and drought stress conditions using a randomized complete block design with two replications at the Agricultural Research Farm of the RIPP, Shahid Bahonar University of Kerman. Genotyping was performed using a 90K single nucleotide polymorphism (SNP) array at the IPK, Germany. Data were analyzed using statistical methods including combined analysis of variance, correlation analysis, stepwise regression, and path analysis. In addition, stress tolerance indices and genomic estimated breeding values (GEBV) were estimated.
Findings: The results of combined analysis of variance showed significant differences among genotypes, environments, and genotype × environment interaction for most traits. Most yield-related traits showed a positive correlation with grain yield. Based on regression and path analysis, the number of grains per unit area and thousand-grain weight had major effects on grain yield. Furthermore, the prediction accuracy of genomic estimated breeding values ranged from 0.56 to 0.82, and narrow-sense heritability ranged from 0.09 to 0.42, indicating efficiency of genomic selection under drought stress conditions. Based on the STS, genotypes 9, 40, 53, 80, 92, 120, 132, 205, 253, and 255 were identified as the most drought-tolerant genotypes. The results of genomic estimated breeding values also showed that genotypes 187, 123, 262, 21, and 43 had the highest yield potential under stress conditions. A significant positive Spearman rank correlation was observed between STS- and GEBV-based rankings (ρ = 0.705, P < 0.001), indicating substantial agreement between phenotypic and genomic selection approaches.
Conclusion: In general, the number of grains per unit area, thousand-grain weight, and grain weight per plant were identified as the most important traits affecting grain yield under stress conditions. The results suggest that genomic selection complements rather than replaces phenotypic evaluation, and integrating both approaches can improve the accuracy of identifying drought-tolerant wheat genotypes

Keywords


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