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Search All Journals. In this research, the relationships among the 31 microsatellite markers with charcoal rot disease resistance related indices in different soybean cultivars and lines were evaluated using association analysis based on the general linear model GLM and the mixed linear model MLM by the Structure and Tassel software. In association analysis based on GLM and MLM models, 31 and 35 loci showed significant relationships with the evaluated traits, respectively, and confirmed considerable variation of the studied traits.

The identified markers related to some of the studied traits were the same which can probably be due to pleiotropic effects or tight linkage among the genomic regions controlling these traits. The results of this research and the linked microsatellite markers with the charcoal rot disease-related characteristics can be used to identify the suitable parents and to improve the soybean population in future breeding programs. Soybean Glycin max L. Soybean has a special status among the plants due to its high level of protein and oil.

In natural and agricultural ecosystems, plants are exposed to the stresses. Various factors including biotic insects, fungus, viruses and weeds and abiotic factors drought, salinity, high and low temperature, flooding and radiation affect growth of the crop plants. Soybean is sensitive to a large number of pathogens that cause the most damage to seedling and root of plant.

One of the soil-borne pathogens which attack the root and crown is the fungus Macrophomina phaseolina Tassi Goid which is the factor of charcoal rot pathogen or wilting. This fungus is poly-phage and pollutes more than plant species in families, including the monocotyledon and dicotyledon Jana et al.

In favourable conditions, this pathogens causes the burning and death of seedling, the crown rot and charcoal rot in most important crops such as soybean, cotton, corn, sunflower, sorghum and so on Babu et al. It seems that the only practical way to control the soybean charcoal rot is to use the resistant cultivars Mengistu et al. Therefore, identifying the resistant cultivars and mapping resistance gene helps significantly the plant breeders to progress the breeding programs for producing the disease resistant cultivars.

Association analysis which is also known as linkage disequilibrium LD mapping, has main advantages that mapping the genes. Since natural populations are used in association analysis, firstly, there is wider genetic diversity than the two-parents populations. Secondly, upon the population, LD mapping has high accuracy, because all meiosis events accumulated during the plant evolutionary history are taken into account, while in the ordinary method, mapping only occur in a number of cross or autogamous generations Musial et al.

Linkage disequilibrium has a important application in association mapping studies. In case of any linkage disequilibrium between the molecular marker and genes controlling a special trait, significant relationship can be determined between the marker and traits and using it in breeding programs. Therefore, association mapping is of high importance in determining the amount of linkage disequilibrium between the marker and trait Oraguzie et al.

Using the association mapping, Iqbal et al. By using the SSR markers, Wang et al. Li et al. Fusari et al. Through association analysis, Sun et al. Sonah et al. Coser et al. Five significant single nucleotide polymorphism SNP and putative candidate genes related to abiotic and biotic stress responses were reported from the field screening; while greenhouse screening revealed eight loci associated with eight candidate gene families, all associated with functions controlling plant defense response.

It seems that genes controlling some morphological attributes and a few number of diseases in soybean have been identified based on the consistency analysis as well as association analysis but genes or QTLs controlling the resistance to the charcoal rot disease in soybean have not been yet mapped.

In this study, SSR markers linked to some important traits related to the charcoal rot disease were identified by association analysis in Iranian soybean germplasm. To evaluate the resistance of different soybean genotypes to charcoal rot, the seeds of soybean genotypes from different maturity groups were planted in two separate experiments as a randomized complete block design with three replications at the research field of Seed and Plant Improvement Research Institute SPIRI , Karaj Iran, during two years, and The seeds of each genotype were planted in four lines of 2.

Primary plowing and disk were carried out at a depth of 30 cm and 15 cm, respectively, and the ground levelling was done by the trowel. The first irrigation was carried out 3 days before planting and the next irrigations were done once a week.

Weed control was carried out manually on several occasions. The genotypes were inoculated with the pathogen at flowering stage employing Tesso and Ejeta method with some modifications.

For contamination in field conditions, isolate S 8 , isolated and purified from infected soybean plants at SPIRI field, was propagated on a potato dextrose agar PDA culture medium to obtain a three-day culture.

Seven mm discs made from the fungus colony margin were placed in the center of 9 cm petri dishes containing a new PDA culture medium. Then, in sterile conditions, four sterilized toothpicks were placed in each petri with the same intervals and on two sides of the mycelium disk.

After the toothpicks were covered with mycelium colonies and fungal microsclerotia, they were transferred to the field for inoculation of plants at the flowering stage. To inoculate, some holes were firstly created on the stems horizontally by an awl which were in the diameter of the toothpick and the contaminated toothpicks were secondly inserted into the plant stem. To determine the resistance and susceptibility of soybean genotypes to charcoal rot disease, the traits including pod weight, grain weight, grain weight, grain yield, number of microsclerota in stem, amount of charcoal rot disease I and severity of charcoal rot disease S were measured.

Amount of charcoal rot disease I and severity of charcoal rot disease S were calculated based on Eqs. Where n is the number of plants with symptoms of the disease and N is the total number of evaluated plants Cardoso et al.

Which Hd is the height of the stem discoloration or the length of the lesion, and Ht is the total height of the stem measured Mengistu et al.

The ruler was used to measure the length of the lesion caused by the fungus. For genotypic evaluations, 3 to 4 newly-developed leaves were taken from each bush at five-leaf stage and wrapped up on a thin aluminium foil and put on the liquid nitrogen container.

The characteristics of 31 SSR markers Table 2 were extracted from soybase database www. The PCR products were separted by horizontal agarose gel elctrophoresis and the gels were stained by AgNO 3 and finally the observed bands for each of the studied genotypes were scored. To perform the association mapping, structure analysis was firstly conducted to construct the genetic structure matrix of the studied genotypes using the STRUCTURE software Pritchard et al.

Since there was no prior information on population structure, so the optimum number of groups or sub-populations K was determined by simulation, so that K was considered from 1 to 10 and simulation was conducted with period length of burn in and Markov Chain Monte Carlo MCMC repetition and the optimum K was determined using Evanno et al.

Then, membership percentage of each genotype in each group was determined by Spataro et al. Data obtained from the population structure Q matrix and breaking it into two or more sub-populations, was extracted from this software.

Descriptive statistics of the measured traits including minimum, maximum, mean, range and cofficient of variation CV for the studied population is shown in Table 3. The highest CV was observed for grain yield and amount of charcoal rot disease These results shows that the studied soybean germplasm has a high diversity for the all measured traits that can be useful for the association analysis.

Because in the association analysis, genetic factors related to phenotypic variations are searched in more diverse populations than those derived from the crossing of two pure lines, the occurrence of recombinant events during the evolutionary history of these highly diverse populations, which are usually several generations more further from their common ancestry, cause to the failure of the linkage disequilibrium blocks in the genome Oraguzie et al. In the other words, all the meiosis events accumulated over the evolutionary history of the plant are considered in the association mapping, while in the conventional mapping populations, the meiosis events occurs only in a few intercourse generations or self-pollination Oraguzie et al.

Therefore, it seems that to be necessary the existence of a high variation in the studied populations for clarity and accuracy of the results Oraguzie et al. This variation was observed in the studied population in this research. Wang et al. In genetic studies, the population structure which is used to explain the relationships of individuals within and between the populations, provides a perspective on the evolutionary relationships of individuals in a population.

Moreover, in the ideal association analysis, there should be no structure in the studied population, indeed, the population should not be structurally divided into subgroups, since the existence of the structure in the studied population could be a deterrent to achieve the reliable results. If the effects of population structure and kinship relationships are not considered in the association analysis, false positive results will arise Breseghello and Sorrells, Therefore, understanding the population structure as a prerequisite in association mapping can avoid false positive relationships between markers and traits Pritchard et al.

In this research, the genetic structure of the studied population and the proper number of sub-population were used as covariate in conducting association analysis based on the Bayesian method in STRUCTURE software Porras-Hurtado et al.

The results indicated that Fig. In assoction mapping where the quantitative trait loci QTLs are mapped based on the linkage disequilibrium LD in addition to combining the population structure, the extent of LD in the genome is also very important Al-Maskri et al. In this study, The linkage disequilibrium in the studied genetic population allows association mapping analysis.

The factors increasing the amount of LD are system of autogamy, epistasis, genomic alterations, genetic drift, genetic isolation, population structure, small size of population, selection and degree of kinship, while alternating allogamy , gene transformation, high levels of recombinant and mutation, as well as periodic mutations, are factors that decrease the LD levels Al-Maskri et al.

Slatkin reported that the multiallelic markers such as microsatellite are more likely to achieve a meaningful LD than the bi-allelic markers such as DArT, SNP, etc. Remington et al. The associated and significant markers in GLM method were including the relationships between 2 markers with severity of disease, 3 markers with grain yield, 4 markers with each of the traits of number of microsclerota in stem and the amount of charcoal rot disease, 5 markers with pod weight, 6 markers with grain weight and 7 markers with grain weight Table 4.

This result can probably be due to the pleiotropic effects or tight linkage of the genomic regions involved in controlling these traits Jun et al. The identification of common markers is very important in plant breeding since the simultaneous selection of several traits is possible Tuberosa et al. Moreover, the significant relationships between several markers with a specific trait was also showed in this research Table 4.

On the other hand, low values of the coefficients of determination R 2 for most of the linked markers also confirms the same issue and shows the determination of some variances in these traits through identified genetic locations and, therefore, the greater effect of the environment relative to genetic effects on variation of these traits. In general, considering the constraints of the linkage mapping method, such as the lack of availability of dispersed populations and the long time required to create them, the association analysis method by eliminating these limitations provides researchers with appropriate marker information Oraguzie et al.

The results of the present study showed the effectiveness of the association mapping method in identifying markers linked to the evaluated traits in the studied soybean genotypes. Evidently, it is necessary to validate the markers identified and associated with relevant traits in large populations with a higher level of diversity as well as in different environments, in order to ensure their relevance to the related traits, and thus to increase the efficiency these markers will increase in various breeding programs such as marker assisted selection MAS.

Neale and Savolainen, showed that genetic locations selected by the association analysis have important advantages such as involving adequate levels of nucleotide diversity and also the ability accurately phenotypic evaluations that can be used in MAS. Several studies have previously been conducted to identify genetic locations associated with resistance to charcoal rot disease in different plants by different molecular markers.

Olaya et al. They also identified two RAPD markers related to resistance. Miklas et al. Yuan et al. Sun et al. Soybean genotypes evaluated to charcoal rot disease Macrophomina phaseolina in field conditions in this research. Microsatellite markers linked to evaluated traits in the studied soybean population using the association mapping based on GLM and MLM models. Search for Search All Journals. Title Author Keyword Volume Vol. Other Sections Abstract Materials and Methods Results and Discusion Acknowledgments Figure Table Reference Abstract In this research, the relationships among the 31 microsatellite markers with charcoal rot disease resistance related indices in different soybean cultivars and lines were evaluated using association analysis based on the general linear model GLM and the mixed linear model MLM by the Structure and Tassel software.

Keywords : linkage disequilibrium, microsatellite markers, pleiotropic effect, population genetic structure. Other Sections Abstract Materials and Methods Results and Discusion Acknowledgments Figure Table Reference Materials and Methods Plant materials and phenotypic evaluations To evaluate the resistance of different soybean genotypes to charcoal rot, the seeds of soybean genotypes from different maturity groups were planted in two separate experiments as a randomized complete block design with three replications at the research field of Seed and Plant Improvement Research Institute SPIRI , Karaj Iran, during two years, and The severity of disease S is based on the rate of colour changes in the plant tissue stem.

Genotypic evaluations For genotypic evaluations, 3 to 4 newly-developed leaves were taken from each bush at five-leaf stage and wrapped up on a thin aluminium foil and put on the liquid nitrogen container. Data analysis To perform the association mapping, structure analysis was firstly conducted to construct the genetic structure matrix of the studied genotypes using the STRUCTURE software Pritchard et al.

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