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In order to select the best parents for crossings, plant breeders seek varieties or genotypes with highest genetic dissimilarities. This can be achieved by measuring the similarities among genotypes, using multivariate analysis methods such as cluster analysis. This study aimed to group 50 aerobic and lowland rice genotypes based on biochemical characteristics including Iron, Zinc, Manganese and protein, and their linked DNA markers. According to the cluster analysis results using Ward method, the genotypes were assigned to four groups. The third group, as the smallest group including three genotypes (IR82635-B-B-82-2, Caiapo, and Gohar), had the highest value for these micronutrients. Their mean value for Iron, Zinc, Manganese, and protein were 32.39, 34.15, 25.66 mg/kg and 6.71%, respectively. Also, all genotypes were classified into two main groups based on microsatellite markers information, that according to QTL mapping studies these markers were identified as linked to elements. So, the most of non-local genotypes and aerobic rice cultivars were assigned in a separate group. The correlation between Euclidean distance of elements and protein matrix and genetic similarity matrix (Nie) using Mental correlation test was estimated significant (p<0.01) that can be evidence of a genetic relationship between the SSR markers and genome controlling regions of elements in this population.

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water stress and, in this regard, it is necessary to improve rice cultivars to tolerance to environmental stresses. In this research 154 recombinant inbred lines (F9) derived from a cross between Shah-Pasand and IR28 in three conditions (non-stress, osmotic stress -0.3 and -0.6 Mpa induced through polyethylene glycol-6000) were evaluated as a factorial experiment in randomized complete block design. In addition, for molecular polymorphism experiment, 110 SSR and EST-SSR markers were assessed on parents of population and among them, 41 markers identified which had proper polymorphism between two parents. The regression analysis between germination components and molecular markers revealed the most coefficient of determination were found in RM211 for allometric coefficient (17%) under non-stress, RMES10-1 for Plumule dry weight (18%) under -0.3 MPa; and RM273 for germination uniformity (22.7%) under -0.6 MPa. RM3496, RM452, and RMES6-1 in three conditions had the most number of significant relationships with six, three and eight traits, respectively, and they can be a suitable candidate for simultaneous improvement of several traits in breeding programs of marker-assisted selection. In addition, after the identification of significant markers associated with germination components, the closest genes to these markers were identified using bioinformatic analysis, and the analysis of their expression were performed by rice transcriptome database. According to the results, the maximum gene expression pattern under drought stress and under non-stress conditions were related to loci LOC_Os01g57220 and LOC_Os01g26039, respectively and this information could be applied in breeding programs.