Volume 15, Issue 48 (12-2023)
J Crop Breed 2023, 15(48): 164-177 |
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Majidi-Mehr A, Pahlavani M, Zaynali-Nezhad K, Karimizadeh R, Börner A. (2023). Studying the Population Structure of Spring Wheat Genotypes and Analysis of Marker-Trait Association under Water Deficit Conditions. J Crop Breed. 15(48), 164-177. doi:10.61186/jcb.15.48.164
URL: http://jcb.sanru.ac.ir/article-1-1457-en.html
URL: http://jcb.sanru.ac.ir/article-1-1457-en.html
Ahmad Majidi-Mehr 
, Mohammadhadi Pahlavani , Khalil Zaynali-Nezhad , Rahmatollah Karimizadeh , Andreas Börner
, Mohammadhadi Pahlavani , Khalil Zaynali-Nezhad , Rahmatollah Karimizadeh , Andreas Börner
Abstract: (769 Views)
Extended Abstract
Introduction and Objective: Water deficit stress is a serious threat to food security worldwide. Association mapping is a suitable method to identify the location of quantitative traits based on linkage disequilibrium, which is highly effective in describing complex genetic traits. This study aimed to evaluate the population structure and the SNP markers association morphological traits of spring wheat genotypes under water deficit stress conditions.
Material and Methods: In this research, genome-wide association mapping was done for 111 spring wheat genotypes. Phenotyping evaluation was done in the form of a simple lattice design with two replications in the agricultural year 2020-2021 under non stress and water deficit stress conditions in the experimental field of Gachsaran Rain-fed Agricultural Research Station in Iran. Genotyping of the samples was done using SNP markers (15 K SNP array) in Trait-Genetic company in Germany. Each genotype was evaluated using 15 thousand SNP markers. The obtained SNP data were filtered in terms of MAF indices (minor allele frequency) and missing data (Missing data >10%). From each of the 21 pairs of bread wheat homologous chromosomes, seven SNP markers with no missing data and with suitable distribution were selected (147 markers in total) to determine the structure of the studied population (Q matrix) using STRUCTURE 2.3 software and the number of groups (K) was identified. The studied traits were flag leaf area, number of nodes, first internode length, number of tiller per plant, number of fertile tillers per plant, number of infertile tiller per plant, and spike weight. Genome-wide association mapping using TASSEL 5.0 software and the general linear model (GLM) method with Q matrix and decomposition into principal components with more than 80% justification (PCA) with 52 components was used.
Results: The results of the analysis of variance showed that there was an acceptable genetic variation in terms of all studied traits and also the reaction of genotypes was different in facing water deficit stress.
In the water deficit stress condition, chromosome 2A had the maximum significant correlation with 39 and chromosome 5A had the minimum association marker with the trait with four. In the of water stress conditions, three bread wheat genomes (A, B, and D) accounted for 53, 36, and 11% of the frequency of marker-trait association, respectively. A and D genomes of bread wheat under water deficit stress conditions ratio to non-stress conditions assigned a more prominent role for the examined traits. In total in the non-stress and water deficit stress condition 180 and 111 marker trait association (MTA) were identified respectively. In the water deficit stress conditions, the number of correlations with markers for flag leaf area, first internode length, tiller of number per plant, and spike weight were 17, 24, 10 and 19, respectively. In the water deficit stress condition, the frequency of significant marker association more significant than in non-stress condition for traits of first internode and fertile tiller of number per plant. Three bread wheat genomes showed an unequal contribution for the studied traits in terms of the number of identified marker-trait associations (MTA). Also, genome A had a significant contribution to grain yield under water stress conditions with 74% of significant correlations between the marker and the spike weight trait.
Conclusion: Finally, the MTAs identified in the present study can be used in the development of wheat breeding programs under water deficit conditions especially gene pyramiding or marker-assisted selection.
Introduction and Objective: Water deficit stress is a serious threat to food security worldwide. Association mapping is a suitable method to identify the location of quantitative traits based on linkage disequilibrium, which is highly effective in describing complex genetic traits. This study aimed to evaluate the population structure and the SNP markers association morphological traits of spring wheat genotypes under water deficit stress conditions.
Material and Methods: In this research, genome-wide association mapping was done for 111 spring wheat genotypes. Phenotyping evaluation was done in the form of a simple lattice design with two replications in the agricultural year 2020-2021 under non stress and water deficit stress conditions in the experimental field of Gachsaran Rain-fed Agricultural Research Station in Iran. Genotyping of the samples was done using SNP markers (15 K SNP array) in Trait-Genetic company in Germany. Each genotype was evaluated using 15 thousand SNP markers. The obtained SNP data were filtered in terms of MAF indices (minor allele frequency) and missing data (Missing data >10%). From each of the 21 pairs of bread wheat homologous chromosomes, seven SNP markers with no missing data and with suitable distribution were selected (147 markers in total) to determine the structure of the studied population (Q matrix) using STRUCTURE 2.3 software and the number of groups (K) was identified. The studied traits were flag leaf area, number of nodes, first internode length, number of tiller per plant, number of fertile tillers per plant, number of infertile tiller per plant, and spike weight. Genome-wide association mapping using TASSEL 5.0 software and the general linear model (GLM) method with Q matrix and decomposition into principal components with more than 80% justification (PCA) with 52 components was used.
Results: The results of the analysis of variance showed that there was an acceptable genetic variation in terms of all studied traits and also the reaction of genotypes was different in facing water deficit stress.
In the water deficit stress condition, chromosome 2A had the maximum significant correlation with 39 and chromosome 5A had the minimum association marker with the trait with four. In the of water stress conditions, three bread wheat genomes (A, B, and D) accounted for 53, 36, and 11% of the frequency of marker-trait association, respectively. A and D genomes of bread wheat under water deficit stress conditions ratio to non-stress conditions assigned a more prominent role for the examined traits. In total in the non-stress and water deficit stress condition 180 and 111 marker trait association (MTA) were identified respectively. In the water deficit stress conditions, the number of correlations with markers for flag leaf area, first internode length, tiller of number per plant, and spike weight were 17, 24, 10 and 19, respectively. In the water deficit stress condition, the frequency of significant marker association more significant than in non-stress condition for traits of first internode and fertile tiller of number per plant. Three bread wheat genomes showed an unequal contribution for the studied traits in terms of the number of identified marker-trait associations (MTA). Also, genome A had a significant contribution to grain yield under water stress conditions with 74% of significant correlations between the marker and the spike weight trait.
Conclusion: Finally, the MTAs identified in the present study can be used in the development of wheat breeding programs under water deficit conditions especially gene pyramiding or marker-assisted selection.
Type of Study: Research |
Subject:
اصلاح نباتات مولكولي
Received: 2023/02/12 | Revised: 2024/01/23 | Accepted: 2023/06/3 | Published: 2024/01/23
Received: 2023/02/12 | Revised: 2024/01/23 | Accepted: 2023/06/3 | Published: 2024/01/23
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