In order to determine yield stability of 23 bread wheat genotypes and two commercial cultivars as check, an experiment was conducted based on a randomized complete block design with three replications in the experimental field of faculty of Agriculture, Razi University Kermanshah (Iran), during three cropping seasons (2015-2018). The results of combined ANOVA showed that the effect of environment, genotype and genotype × environment interactions on grain yield were significant (P<0.01). Stability was evaluated using environmental variance statistics, coefficient of variation, Wrick´s ecovalence, Shukla’s stability variance, Regression slope, deviation from regression slope, Plaisted and Peterson method and AMMI model. Variance analysis of additive main effects and multiplicative (AMMI) showed that three IPCAs were significant at 1% probability level. The first three principal components justified a round 85.7% of the sum of square of the interaction. Also, AMMI stability value (ASV) was used for simultaneously using information obtained from two significant components of AMMI. According to ASV index, genotypes Pishgam, Wc-4958 and Pishtaaz had the lowest ASV value and were known as the most stable genotypes. Genotypes Wc-4987, Wc-47615, Wc-47399 and Wc-47638 had the highest ASV value and distance from the center of Bi-plot. Therefore, Pishtaaz is one of the most stable genotypes due to having the first rank in terms of studied parameters as well as proper bakery properties and desirable drought resistance. In general, regarding to the climate change in the country, especially in the rainfed conditions and based on the above statistics and the biplots derived from AMMI analysis, the Wc-4958 line, with pishtaaz and Pishgam cultivars as stable and adaptable genotypes, are suggested to rainfed conditions on the studied area.

Salinity stress falls into the major environmental factors that limit the production of various crops, including wheat. An effective approach to reducing the impacts of stress is the production of new salinity-tolerant cultivars. Accordingly, identifying effective genes and molecular mechanisms responsible for salinity tolerance is an essential step for breeding programs. In this investigation, a population of F12 recombinant inbred lines (RIL) comprising 186 genotypes was studied to identify the loci that control some physiological traits and element concentrations in the wheat seedling stage under salinity stress. Totally, 12 quantitative traits loci (QTLs) were identified for wet weight, dry weight, length, and sodium and potassium contents using the composite interval mapping (CIM) analysis. Most of the identified QTLs were located on chromosomes B and D. A gene ontology (GO) analysis specified candidate genes in QTL regions. However, it is noteworthy that candidate genes need confirmation using marker-assisted identification. The prioritization of genes resulted in determining 3486 candidate genes in 19 GO phrases (including eight biological processes). These genes are involved in the processes of glutathione metabolism, L-phenylalanine catabolism, cytoplasmic translation, auxin-activated signaling pathway, transcriptional regulation, DNA-patterning, protoporphyrinogen IX, cell wall organization and genesis, xyloglucan tRNA metabolism, protein glycosylation, pigment biosynthesis, etc. GO may be introduced for identifying novel CGs in which the associated QTL is responsible for complicated traits.
 

In order to identify loci controlling seedling morpho-physiologic characteristics in 88 bread wheat cultivars, a greenhouse experiment based on simple alpha lattice was conducted under both normal and 120 mM (12 ds/m) salt stress condition of the Faculty of Agriculture, Urmia University in 2020-2021 cropping season. Chlorophyll a, b and carotenoid content, proline, plant fresh and dry weight, plant height and leaf relative water content (RWC), Na⁺, K⁺ and K⁺/Na⁺ concentrations were measured. After genotyping by sequencing with Ion Torrent technology and removal of SNPs with more than 20% of missing data and minor allele frequency less than 5%, a total of 5869 SNP markers were identified. Based on association mapping with the mixed linear model (MLM) method, a total of 25 marker-trait associations were detected under normal conditions. The A and D genomes had the highest and lowest number of significant marker-trait associations (MTAs). Among the studied traits under normal conditions, chlorophyll a had the highest number of MTAs on 1A, 3B, 3D, 5B, 7A chromosomes with eight MTAs. A total of 21 MTAs were identified under salt stress conditions which the genome B and D had the highest and lowest number of MTAs, respectively. Five MTAs were identified for plant fresh weight, which were located on chromosomes 4A and 6B. The results of this study provide valuable information about the loci associated with the studied traits, which can be used in marker assisted selection in wheat breeding programs after confirmation in biparental populations and additional experiments.
 

Due to world population incline and the increasing wheat consumption as human main staple food, as well as high amount of waste of bread which is mainly due to its low quality, the wheat breeding programs to improve bread quality are of great importance. Therefore, evaluating the wheat grains quality and the genetic variation of bread-making quality traits among lines derived from crosses becomes imperative. To this end, the gliadin protein banding pattern of 28 recombinant inbred lines, their corresponding parents and 10 other commercial cultivars were examined via A-PAGE method. The variation between and within the lines and cultivars was determined using AMOVA according to the protein bands. The results of this study revealed high variation for gliadins coding loci with total mean of 73.96%. The percentage of polymorphism was estimated to be 91.67 and 56.25 for lines and commercial cultivars, respectively. The minimum and maximum number of gliadin bands were 12 and 25 bands, respectively. Also, based on PhiPT statistics, the significant difference was observed (P<0.05) between commercial cultivars and recombinant inbred lines in terms of gliadin banding patterns. Cluster analysis and PCoA via banding pattern of gliadins led to formation of three and four distinct groups, respectively. The highest variation was observed in ω-gliadins, suggesting that they may have a role in observed variation among genotypes and their bread making-quality traits.