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Showing 3 results for Badakhshan
Raheleh Aziznia, Hedieh Badakhshan, Taimoor Javadi, Soma Zamani,
Volume 6, Issue 2 (3-2020)
Abstract
In this study, variation of beta-glucan content was assessed in 20 barley line and cultivars based on complete block design with three replications. Genetic diversity of these genotypes was also evaluated using ISSR markers. Beta-glucan extracted by an enzymatic method. Significant differences were found at the level of 1% among barley genotypes for beta-glucan content. The beta glucan content was variable from 7.21 to 12.48 and, the Yosef, E94B3 and E94B17 genotypes hold the highest content of the beta-glucan. ISSR primers with average polymorphism of 66.79%, genetic diversity of 0.25 and Shannon index of 0.37 were determined as efficient markers for studying genetic diversity. The barley lines and cultivars were assigned in two distinct groups according to their genetic pedigree. On the basis of non-parametric Kruskal-Wallis, Spearman correlation, and stepwise regression analysis, nine informative primers were detected explaining highest seed’s beta-glucan content variations ranging from 24.3 to 42.4 percent. The ISSR6 (700), the combination of ISSR1+ISSR4 (1400) and IS2+ ISSR2 (1400) primers were the most informative primers for the beta-glucan content. The informative markers provide possible functional and efficient marker based selection method and, screening the barley germplasms for the highest beta-glucan content.
Shahla Hosseini, Mohammad Reza Rahgozar, Hedieh Badakhshan,
Volume 8, Issue 2 (3-2022)
Abstract
Genus Allium L. contains very taxonomically complex sections, especially the subgenus Melanocrommyum. The systematic position of the species in each section has been revised many times over time. In the present study, the relationship between 32 ecotypes belonging to 10 different species of Allium was investigated using ISSR markers. The nine primers used produced 166 polymorphic bands (average 18 bands per primer). Among the primers used, ISSR873 primer with 27 bands made the most, and ISSR4 primer with two bands had the lowest polymorphic bands. The PIC of the markers ranged from 0.04 to 0.43. Cluster analysis by UPGMA method based on molecular markers divided the studied ecotypes into four groups. The clustering and principal coordinate analysis results showed that most morphologically similar species were grouped in closed clusters. According to Dice similarity coefficient, the highest percentage of similarity was shown between Allium stipitatum and Allium saralicum ecotypes (72 percent) from the Melanocrommyum subgenus, and the lowest similarity was obtained between Allium tripedale and Allium iranicum ecotypes (12 percent). The ecotypes with the lowest similarity percentage belong to the subgenus Allium and Nectaroscordum, which are placed in separate clusters. Based on the results, the ecotypes of Pseudoprason, Melanocrommyum, and Procerallium sections showed the highest affinity. In general, it can be concluded that ISSR markers are useful for classifying Allium species and have sufficient potential for phylogenetic studies of species. In addition, due to significant genetic diversity among the studied ecotypes of wild Allium species, this diversity can be used in future breeding programs of crop.
Parastoo Zarei, Hedieh Badakhshan, Ghader Mirzaghaderi,
Volume 11, Issue 1 (9-2024)
Abstract
Evaluating genetic diversity in plant species is essential for crop improvement. This research compared the genetic diversity between common oat (Avena sativa) and wild oat (Avena fatua) using molecular markers, phenotypic traits, and chromosomal characteristics. SCoT and IRAP markers generated 283 and 117 bands, respectively. Both marker systems revealed higher polymorphism in wild oat compared to common oat. SCoT markers showed 65.37 percent polymorphism in wild oat versus 60.07 percent in common oat, while IRAP markers exhibited 76.07 and 69.23 percent polymorphism, respectively. Genetic diversity indices (Ne, He, and PIC) indicated slightly higher genetic diversity in wild oat for both marker systems, although the genetic distance between the two species was relatively low. Population structure analysis using Bayesian methods, Principal Coordinate Analysis (PCoA), and Analysis of Molecular Variance (AMOVA) consistently identified distinct subpopulations and significant genetic variation within species. Phenotypic trait analysis revealed significant differences among genotypes. Common oat genotypes generally exhibited greater plant height, while wild oat genotypes had higher 100-seed weight. Heatmap cluster analysis grouped genotypes into three clusters based on phenotypic traits. All genotypes were hexaploid but showed differences in chromosomal parameters such as total chromosome length, centromeric index, and dispersion index. However, no significant differences were found between common and wild oat species in these parameters. Principal Component Analysis (PCA) of chromosomal parameters explained 94.72 percent of the cumulative variance, with PC1 emphasizing centromere position and PC2 highlighting chromosomal asymmetry. This comprehensive study provides valuable insights for breeding and conservation strategies in oat species.
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