use of rapid serological and nucleic acid- based methods for detecting the soybean mosaic virus
نویسندگان
چکیده
soybean mosaic virus (smv) which belongs to the virus family potyviridae, causes a disease in soybean that is present in soybean-growing areas of the world, and is widely distributed in northern iran. detection of smv is very important for disease management. in the present study several serological and molecular (nucleic acid- based) methods of rapid virus detection were compared. serological studies including das- elisa, dac-elisa, tpia and diba were optimized and compared to identify the virus by using a polyclonal antibody. among the serological methods, tpia and diba are simple and tpia is rapidly and easily applicable in the field. however, tpia was found to be preferable. tpia is time-saving, not requiring conventional sap extraction and also nitrocellulose membranes used for printing can be used in the field and stored for a long time or transported to other laboratory to be processed. rt-pcr and immunocapture rt-pcr (ic-rt-pcr) were performed as molecular methods for detecting smv using a pair of primers designed to amplify a fragment in the coding region of the smv coat protein. to extract total rna for rt-pcr, two methods including rnawiz and phenol-chloroform were used. a part of the coat protein genome of smv was converted to cdna using a reverse transcription (rt) reaction. for ic-rt-pcr method, virus partial purification was carried out by solid-phase (0.2 ml microfuge tube) adsorbed polyclonal antibody, and then the rt reaction was carried out in the tube. in both methods cdnas were amplified by pcr. both methods amplified the expected fragment in virus-infected plants. whereas rt-pcr requires total rna extraction, icrt- pcr do not have total rna extraction problems. our findings suggest that tpia and ic- rt- pcr can be routinely used for smv detection, with high efficiency.
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عنوان ژورنال:
journal of agricultural science and technologyناشر: tarbiat modares university
ISSN 1680-7073
دوره 11
شماره Number 1 2010
میزبانی شده توسط پلتفرم ابری doprax.com
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