1- Razi University
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Extended Abstract
Introduction and Objective: Oat (Avena sativa L.), a major global cereal crop belonging to the Poaceae family, is widely cultivated for animal feed and increasingly recognized as a valuable source of nutrients for human consumption. Given the decline in the production of this crop, the conservation of its genetic resources plays a vital role in ensuring global food security. Maintenance of grain quality and yield potential is essential to enhance the nutritional and economic value of oats. This not only ensures enhanced economic return to producers but also helps oats remain competitive with other cereal crops. Understanding the genetic makeup of any plant species is a prerequisite for effective plant breeding. Utilizing the diversity within a germplasm can lead to the identification of suitable parents and superior varieties, as well as the improvement of existing agricultural traits. Recent advances in molecular tools have enabled more precise and rapid assessments of genetic diversity and intra-species relationships. Molecular markers, especially dominant DNA-based techniques such as SCoT, are key tools in genetic diversity studies. The SCoT (Start Codon Targeted) marker is a PCR-based marker designed around the conserved sequences flanking the start codons of plant genes. Its advantages include ease of use, cost-effectiveness, high polymorphism, broad genome coverage and informativeness, and widespread presence throughout the genome. Given these benefits and the high cost of evaluating genetic resources and identifying new varieties, the use of simple and economical markers like SCoT can be a viable solution. This study assessed the genetic diversity in cultivated oat (Avena sativa L.) genotypes using SCoT marker.
Materials and Methods: This research was conducted in 2021 at the Biotechnology Laboratory of the Department of Plant Production and Genetics Engineering at Razi University, Kermanshah, Iran. The study utilized 148 cultivated oat genotypes, obtained from the Australian Grains Genebank (AGG), with various origins. These genotypes are maintained in the seed bank of the College of Agriculture and Natural Resources at the university. To identify the genetic diversity among the 148 genotypes of cultivated oat (Avena sativa L.), 12 SCoT primers were used. DNA extraction from leaf samples was performed using a modified-Dellaporta method. For data analysis, cluster analysis and dendrogram cut-off points based on the Jaccard distance were determined using SYSTAT 13.0 software. The NTSYSpc 2.02 software was employed to calculate the cophenetic coefficient for cluster analysis, perform principal coordinate analysis, and generate the genetic similarity matrix based on the Jaccard similarity coefficient.
Results: In total, 135 bands were generated by the primers, with 84 bands (61.75%) being polymorphic. The average number of total bands per primer was 11.25, while the average number of polymorphic bands was seven. The highest values for marker indices, including polymorphic band count, polymorphism percentage, marker index, effective multiplex ratio, and resolving power, were obtained for primer SCoT1, indicating its suitable efficiency in differentiating oat genotypes. The genetic similarity coefficients among the studied genotypes ranged from 0.32 to 0.87. The highest genetic similarity was observed between Genotypes 147 (DUNNART) and 148 (HOUDAN), while the lowest was between Genotypes 113 (WESTON) and 131 (STORMONT IRIS). Cluster analysis based on the UPGMA algorithm and Jaccard's distance coefficient divided the oat genotypes into six groups. Most genotypes within the same group were geographically close in origin. Genotypes 116 (SANTA LUZIA) and 144 (FREJA) were positioned farthest apart on the dendrogram, reflecting a significant genetic and geographical distance between them. Principal coordinate analysis showed that a small amount of variation was explained by the first two principal components, largely confirming the pattern of genetic diversity obtained from the cluster analysis. Based on the principal coordinate analysis (PCoA), a small proportion of the total variation was explained by the first two principal components, which largely confirmed the genetic diversity pattern revealed by cluster analysis. Considering the low percentage of variance explained by the first two components in the PCoA, the SCoT markers appeared to be well distributed across the oat genome and to have effectively scanned the entire genome.
Conclusion: The cornerstone of plant breeding research rests on genetic diversity. Without access to this diversity, breeders have little chance of creating and releasing new, improved varieties. Consequently, oat breeding programs may be relying on only a limited portion of the genetic diversity available within this crop species. Given the insufficient knowledge of the genetic potential of cultivated oats within Iran, assessing the genetic diversity of its genotypes is a crucial step. Overall, the results of the present study indicate that SCoT marker are an effective molecular tool for evaluating genetic diversity in oat genotypes. The diversity identified in this research can be utilized in future oat breeding programs to facilitate targeted crosses and variety development. Furthermore, crossing of genotypes with high genetic distance can create populations with greater diversity.
Introduction and Objective: Oat (Avena sativa L.), a major global cereal crop belonging to the Poaceae family, is widely cultivated for animal feed and increasingly recognized as a valuable source of nutrients for human consumption. Given the decline in the production of this crop, the conservation of its genetic resources plays a vital role in ensuring global food security. Maintenance of grain quality and yield potential is essential to enhance the nutritional and economic value of oats. This not only ensures enhanced economic return to producers but also helps oats remain competitive with other cereal crops. Understanding the genetic makeup of any plant species is a prerequisite for effective plant breeding. Utilizing the diversity within a germplasm can lead to the identification of suitable parents and superior varieties, as well as the improvement of existing agricultural traits. Recent advances in molecular tools have enabled more precise and rapid assessments of genetic diversity and intra-species relationships. Molecular markers, especially dominant DNA-based techniques such as SCoT, are key tools in genetic diversity studies. The SCoT (Start Codon Targeted) marker is a PCR-based marker designed around the conserved sequences flanking the start codons of plant genes. Its advantages include ease of use, cost-effectiveness, high polymorphism, broad genome coverage and informativeness, and widespread presence throughout the genome. Given these benefits and the high cost of evaluating genetic resources and identifying new varieties, the use of simple and economical markers like SCoT can be a viable solution. This study assessed the genetic diversity in cultivated oat (Avena sativa L.) genotypes using SCoT marker.
Materials and Methods: This research was conducted in 2021 at the Biotechnology Laboratory of the Department of Plant Production and Genetics Engineering at Razi University, Kermanshah, Iran. The study utilized 148 cultivated oat genotypes, obtained from the Australian Grains Genebank (AGG), with various origins. These genotypes are maintained in the seed bank of the College of Agriculture and Natural Resources at the university. To identify the genetic diversity among the 148 genotypes of cultivated oat (Avena sativa L.), 12 SCoT primers were used. DNA extraction from leaf samples was performed using a modified-Dellaporta method. For data analysis, cluster analysis and dendrogram cut-off points based on the Jaccard distance were determined using SYSTAT 13.0 software. The NTSYSpc 2.02 software was employed to calculate the cophenetic coefficient for cluster analysis, perform principal coordinate analysis, and generate the genetic similarity matrix based on the Jaccard similarity coefficient.
Results: In total, 135 bands were generated by the primers, with 84 bands (61.75%) being polymorphic. The average number of total bands per primer was 11.25, while the average number of polymorphic bands was seven. The highest values for marker indices, including polymorphic band count, polymorphism percentage, marker index, effective multiplex ratio, and resolving power, were obtained for primer SCoT1, indicating its suitable efficiency in differentiating oat genotypes. The genetic similarity coefficients among the studied genotypes ranged from 0.32 to 0.87. The highest genetic similarity was observed between Genotypes 147 (DUNNART) and 148 (HOUDAN), while the lowest was between Genotypes 113 (WESTON) and 131 (STORMONT IRIS). Cluster analysis based on the UPGMA algorithm and Jaccard's distance coefficient divided the oat genotypes into six groups. Most genotypes within the same group were geographically close in origin. Genotypes 116 (SANTA LUZIA) and 144 (FREJA) were positioned farthest apart on the dendrogram, reflecting a significant genetic and geographical distance between them. Principal coordinate analysis showed that a small amount of variation was explained by the first two principal components, largely confirming the pattern of genetic diversity obtained from the cluster analysis. Based on the principal coordinate analysis (PCoA), a small proportion of the total variation was explained by the first two principal components, which largely confirmed the genetic diversity pattern revealed by cluster analysis. Considering the low percentage of variance explained by the first two components in the PCoA, the SCoT markers appeared to be well distributed across the oat genome and to have effectively scanned the entire genome.
Conclusion: The cornerstone of plant breeding research rests on genetic diversity. Without access to this diversity, breeders have little chance of creating and releasing new, improved varieties. Consequently, oat breeding programs may be relying on only a limited portion of the genetic diversity available within this crop species. Given the insufficient knowledge of the genetic potential of cultivated oats within Iran, assessing the genetic diversity of its genotypes is a crucial step. Overall, the results of the present study indicate that SCoT marker are an effective molecular tool for evaluating genetic diversity in oat genotypes. The diversity identified in this research can be utilized in future oat breeding programs to facilitate targeted crosses and variety development. Furthermore, crossing of genotypes with high genetic distance can create populations with greater diversity.
Keywords: cluster analysis, genetic similarity, genome coverage, marker indices, principal coordinate analysis, polymorphism.
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