Authors:A. Etminan, A. Pour-Aboughadareh, R. Mohammadi, A. Noori, and A. Ahmadi-Rad
Progress in plant molecular tools has been resulted in the development of gene-targeted and functional marker systems. CAAT box region is a different pattern of nucleotides with a consensus sequence, GGCCAATCT, which situated upstream of the start codon of eukaryote genes and plays an important role during transcription. In the present study, several CAAT box-derived polymorphism (CBDP) primers were used for fingerprinting in mini-core collection of durum wheat (including internationally developed breeding lines and Iranian landraces). Twelve selected primers amplified 98 loci, of which all were polymorphic. The average values of the polymorphism information content (PIC) and resolving power (Rp) were 0.31 and 9.16, respectively, indicating a high level of variability among studied genotypes. Analysis of molecular variance (AMOVA) indicated that 92% of the total variation resided among populations. The values of the percentage polymorphic bands (PPL), the observed (Na) and effective (Ne) number of alleles, Nei’s gene diversity (He) and Shannon’s information index (I) for Iranian landraces were higher than the breeding lines. The Fandendrogram obtained by cluster analysis grouped all individuals into three main clusters. Our results showed a remarkable level of genetic diversity among studied durum wheat, especially among Iranian landraces, which can be interest for future breeding programs. More importantly, the present study also revealed that CBDP technique was efficient and powerful tool to assess genetic diversity in wheat germplasm. Hence, this technique could be employed individually or in combination with other molecular markers to evaluate genetic diversity and relations among different species.
Authors:A. Pour-Aboughadareh, J. Ahmadi, A.A. Mehrabi, A. Etminan, and M. Moghaddam
The knowledge about genetic diversity in the wild relatives of wheat provides useful information for breeding programs and gene pool management. In the present study, an assessment of agro-morphological diversity and molecular variability among 70 accessions of Triticum, belonging to T. boeoticum, T. urartu, T. durum and T. aestivum species, collected from different regions of Iran was made. According to phenotypic analysis, all traits except peduncle length, stem diameter and the number of seeds per spike indicated a high level of diversity among studied accessions. Also, principal component analysis identified six components that explained 87.53% of the total variation in agro-morphological traits. In molecular analysis, 15 start codon targeted (SCoT) polymorphism primers produced 166 bands, out of which, 162 (97.59%) were polymorphic. Analysis of molecular variance (AMOVA) indicated the 63% of the variation resided among populations. The maximum value of polymorphism information content (PIC), the observed (Na) and effective (Ne) number of alleles, Nie’s gene diversity (He) and Shannon’s information index (I) was detected for T. boeoticum than the other species. The SCoT-based tree revealed three different groups corresponding to the genomic constitution in Triticum germplasm, which was in part confirmed by STRUCTURE and principal coordinate (PCoA) analyses. Our results indicated a remarkable level of genetic diversity among studied Iranian Triticum species, especially T. boeoticum, which can be of interest for future breeding and other analyses associated with future studies of the wild relatives of wheat. More importantly, our results revealed that SCoT markers could be used to accurate evaluate genetic diversity and phylogenetic relationships among different Triticum species.
Authors:A. Etminan, A. Pour-Aboughadareh, R. Mohammadi, L. Shooshtari, M. Yousefiazarkhanian, and H. Moradkhani
In the present study, efficiency of the artificial neural network (ANN) method to identify the best drought tolerance indices was investigated. For this purpose, 25 durum genotypes were evaluated under rainfed and supplemental irrigation environments during two consecutive cropping seasons (2011–2013). The results of combined analysis of variance (ANOVA) revealed that year, environment, genotype and their interaction effects were significant for grain yield. Mean grain yield of the genotypes ranged from 184.93 g plot–1 under rainfed environment to 659.32 g plot–1 under irrigated environment. Based on the ANN results, yield stability index (YSI), harmonic mean (HM) and stress susceptible index (SSI) were identified as the best indices to predict drought-tolerant genotypes. However, mean productivity (MP) followed by geometric mean productivity (GMP) and HM were found to be accurate indices for screening drought tolerant genotypes. In general, our results indicated that genotypes G9, G12, G21, G23 and G24 were identified as more desirable genotypes for cultivation in drought-prone environments. Importantly, these results could provide an evidence that ANN method can play an important role in the selection of drought tolerant genotypes and also could be useful in other biological contexts.