SCNProDB: A database for the identification of soybean cyst nematode proteins |
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Authors: | Savithiry Natarajan Mona Tavakolan Nadim W Alkharouf Benjamin F Matthews |
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Institution: | 1.USDA-ARS, Soybean Genomics and Improvement Laboratory, Beltsville, MD 20705, USA;2.Department of Computer and Information Sciences, Towson University, Towson, MD 21252, USA |
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Abstract: | Soybean cyst nematode (Heterodera glycines, SCN) is the most destructive pathogen of soybean around the world. Crop rotation and
resistant cultivars are used to mitigate the damage of SCN, but these approaches are not completely successful because of the
varied SCN populations. Thus, the limitations of these practices with soybean dictate investigation of other avenues of protection
of soybean against SCN, perhaps through genetically engineering of broad resistance to SCN. For better understanding of the
consequences of genetic manipulation, elucidation of SCN protein composition at the subunit level is necessary. We have
conducted studies to determine the composition of SCN proteins using a proteomics approach in our laboratory using twodimensional
polyacrylamide gel electrophoresis (2D-PAGE) to separate SCN proteins and to characterize the proteins further using
mass spectrometry. Our analysis resulted in the identification of several hundred proteins. In this investigation, we developed a
web based database (SCNProDB) containing protein information obtained from our previous published studies. This database will
be useful to scientists who wish to develop SCN resistant soybean varieties through genetic manipulation and breeding efforts.
The database is freely accessible from:
http://bioinformatics.towson.edu/Soybean_SCN_proteins_2D_Gel_DB/Gel1.aspx |
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Keywords: | Soybean SCN nematode 2D-PAGE MALDI-TOF-MS LC-MS/MS proteins |
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