In this study, an F2:3 populations derived from the cross between Hiberna and Pfyner was used to analyze the inheritance of yield and its components in barley by generation mean analysis and to map the corresponding QTLs (quantitative trait loci) by microsatellite markers. Generation mean analysis suggested that both additive and dominance effects were important for most of the traits evaluated, but dominance and non-allelic interaction had a more pronounced effect for days to maturity, number of grains per spike, spike length and plant height. The highest heritability was obtained for number of tillers, indicating that this trait is controlled by additive effects. The additive effects played major role in the inheritance of grain yield per plant, since heritability of this trait was low. The linkage map constructed by 159 microsatellite markers covered a total length of about 1030.5 cM. Using the method of composite interval mapping 2, 4, 2, 4, 1, 4 and 7 QTLs were detected for days to maturity, number of tillers, 1000-grain weight, plant height, spike length, number of grains per spike and grain yield, respectively. Ten QTLs had corresponding occurrences with the QTLs reported earlier, indicating that these QTLs are stable across genetic backgrounds. The results of this study also showed that, grain yield per plant controls with several minor genes. It can therefore be concluded that direct improvement of this trait is somehow problematic. Two major QTLs contributed by ‘Pfyner’ on chromosomes 1H and 2H (qgs-1 and qnt-2a) were found to significantly increase number of grains per spike and number of tillers, respectively. Thus, genetic improvement in grain yield would be easier through indirect selection for these QTLs than through direct selection for grain yield.

Many QTLs related to agronomic triats have been registered in soybean (Glycine max) by different research groups during the last decade. Due to the interaction effects of QTLs, environmental and genetic backgrounds on the emergence of QTLs and also to confirm the previous results as well as to identify new QTLs, further studies are still required. In order to map QTL which control some agronomic triats, a population consisting of 140 F2 plants, derived from a cross between Williams-82xRGR-JAP, were genetypically assessed by employing 17 SSR and 70 AFLP markers. Ultimately, based on the expected mendelian segregation, 12 SSR and 50 AFLP markers were used for the genetic map along with QTL mapping. Phenotypic evaluation was carried out on 140 F2:3 families for 21 traits. In the end, the linkage map consisting of 13 linkage groups were perpared which covered the genetic map of 733 cM in length. QTL mapping was done using composite interval mapping method which collectively detected 13 QTLs for 10 traits. A major QTL with pleiotropic effects was detected between the two markers Satt-365 and Satt-489 in LG- U9. Results of previous studies confirmed the existence of this QTL. A QTL responsible for reproductive duration and as well for the no. of branches (close to Satt-231 marker in LG-U4) was also detected.

Yield and most morphological traits are controlled by the numerous of genes. In order to QTL mapping for yield and yield components traits, 169 barley recombinant inbred lines (F6 generation) and their parents “Igre” and “Arigashar”, were planted in a simple lattice design with two replications in Ghezlagh (research farm of Abouraihan college, Tehran University in 2007. The traits evaluated including: number of speckle, 1000-seed weight and yield. Analysis of variation showed that there was sufficient variation among the entries. Among traits in this study, the 1000-grain weight with the highest heritability is controlled mainly by additive effects. AFLP and SSR markers were used for preparing linkage map and 4 chromosomes of barley were mapped. Two QTLs identified for each trait on the number of 2 and 5 linkage maps. in and 5 linkage groups. Allelic effects (additive) justified the positive and negative correlation among traits. Pleiotropy of QTLs or linkage between them might lead to high correlation.

Drought tolerance is a quantitative trait and immeasurable directly. Hence, for assessing drought tolerance related characters should be measured. Drought related characters such as root architecture and water use efficiency are quantitative traits and their phenotypic assessment, especially under filed conditions, is difficult. Consequently marker assisted selection is a superior tool for overcoming this problem. At this research genetic control of drought related characters was assessed using QTL analysis method. A set of 220 double haploid lines, derived from Kukri (drought sensitive) and RAC875 (drought tolerant), were used. Overall, 35 QTL on 11 chromosomes were identified. Ten QTL had R2>10. 63% of identified QTLs were located on B genome that shows the substance of this genome in drought tolerance. Root system and water use efficiency are two imperative drought tolerant mechanisms. But their phenotypic assessment under drought condition is either difficult or impossible. Hence these two worthwhile mechanisms are ignored at breeding programs. At this research 3 QTLs on chromosomes 1B, 5A and 5B were identified for root number that explained 39.7 percent of phenotypic variations. Also 3 QTLs on chromosomes 1B, 4B and 6D were responsible for genetic control of water use efficiency and explained 30 percent of phenotypic variation. Root number and water use efficiency have genotypic correlation, the genotypes with more root had more water use efficiency. Leaf width is the most important related character for early vigor. Five QTLs on chromosomes 2B, 2D, 3D, 5A and 6A were identified for leaf width that explained 41.6 percent of phenotypic variations. Selecting genotypes, using Marker assisted selection (MAS), for favorable alleles that has been identified in this study such as Gwm0304b and Barc0256 may allow to improve drought tolerant mechanisms, consequently yield at drought prone environments.

Current study was designed to fine map the Ol-QTL1 area by evaluation of F2, BC2 and BC2S1 progenies, obtained by hybridizing the susceptible L. esculentum cv Money Maker with the resistant L. parviflorum G1.1601, for segregation of resistance to Oidium lycopersici. Two flanking markers, ct21 and ct184 were used to screen recombinant plants. To monitor the targeted area effectively, 24 out of 54 new designed primers have been identified as SCAR and CAPS markers. The results confirmed the presence of resistant controlling area flanked by ct21 and ct184. Resistant homozygote individuals were resistant, with average 0.5 disease index (DI) value, heterozygote plants had intermediate responses and susceptible homozygote individuals showed susceptible performance. Results of recombinant screening showed that the targeted area is located in the upstream of tg25. Based on the results of this research, targeted area was narrowed down to a region of approximately 15 cM. Newly developed SCAR and CAPS markers can be used in marker assisted selection based breeding programs.

Objective Lodging is the permanent horizontal growth of stem and has been considered as a limiting factor in cereal production. Identification of traits that affect grain yield is very important in breeding programs. Furthermore, genetic diversity is essential for breeding programs and increasing selection efficiency. This research was set up to study genetic diversity, evaluation of biomechanical traits, assess lodging stem and detect quantitative traits loci (QTLs) in a RIL population of bread wheat. Materials and methods A large population including 225 bread wheat lines was assessed in a randomized complete block design with two replications in research field of Shahid Bahonar University of Kerman during 2017-2018 growing season. To define biomechanical properties of stems, a universal testing machine equipped with 3-point bend and shear test probes was used. Results Results of ANOVA showed significant difference between wheat genotypes for all traits. Modulus of elasticity of stem had the highest response to selection (21. 65) in comparison with other traits. Moreover, this trait had high genetic variation. Based on these results, modulus of elasticity of each individual plant stem can be used as an effective factor in selection programs. Plant height had the highest narrow sense heritability (0. 59) among evaluated traits. Cross section area had strong and significant correlation with moment of inertia (r=0. 818**). In the molecular assay of this research, linkage map and QTL mapping of traits performed by inclusive composite interval mapping (ICIM) method. Linkage map was constructed based on diversity array technology (DArTs) and SSR markers. Conclusions A total of 12 QTLs have been identified which had LOD higher than 2. 5. These QTLs were controlling 6 biomechanical traits including: specific shear energy, maximum shear energy, moment of inertia, flexural stiffness, maximum specific bending strength and modulus of elasticity. The information of identified QTLs could be used in wheat breeding programs using marker assisted selection.

The aim of this study was to QTL mapping of body weight traits from hatch to 45 days on chromosome one in Japanese quail. For this purpose, a crossbred population from a fourgeneration crossbreeding pattern was used. The four strains A and M Texas, Wild, Italian Speckled and Tuxedo Japanese quail were crossed in diallel-cross, creating the first generation. Then, from the crossbreed of first generation, a mapping population including second, third and fourth generations was created. Blood samples were collected for DNA extraction and amplification of microsatellite markers on the chromosome 1 of the subcutaneous veins in tubes containing 0. 5% EDTA. Observations included body weight traits from birth to 45 days with an interval of 5 days. The effects of markers and components of variance were performed with three models of additive, dominance and additive-dominance with AI-REML procedure of GVCBLUP software. Based on the estimated effects of markers, the point with the highest value of F statistic was reported as the QTL location. The results of QTL analysis in the additive model for body weight traits, at hatch, 5 and 30 days indicate the presence of QTLs affecting these traits at the (hatch, 5 and 30 days), (10, 15, 20, 25, 40 and 45 days) and 35 days on the end, middle and the beginning of chromosome one, respectively. In dominance model, QTLs affecting body weight traits at (hatch, 5, 10, 15, 35, 40 and 45 days), (20, 25, and 30 days) were identified in the middle and at the end of chromosome one. The percentage of additive and dominance genetic variance due to markers in different models ranged from 0. 17 to 9. 4% and 3. 3 to 23. 3% of the total phenotypic variance, respectively. Therefore, the results of this study confirm the existence of at least two distinct gene loci with additive and dominance function effective on body weight traits on chromosome one in Japanese quail.