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All plant virus chip: Shifting from proof to use.
B. BAGEWADI (1), D. C. Henderson (2), K. Fischer (3), R. L. Jordan (4), D. Wang (5), K. L. Perry (6), U. Melcher (7), J. Hammond (8), C. M. Fauquet (1). (1) Danforth Plant Science Center, Saint Louis, MO, U.S.A.; (2) USDA-ARS, Beltsville, MD, U.S.A.; (3) University of Utah, School of Medicine, Salt Lake City, UT, U.S.A.; (4) USDA-ARS-BA, Molecular Plant Pathology Lab, Beltsville, MD, U.S.A.; (5) Washingto

The need to screen increasing numbers of plant viruses in a given sample has resulted in the development of highly parallel methods of detection and identification such as DNA microarray and next generation sequencing. Based on our results with a prototype universal plant virus microarray (UPVM) here we present the development and validation of a full UPVM to detect and identify all known plant viruses, viroids and satellites. A total of 9600 60-mer oligonucleotide probes were selected from 302,230 candidates representing every taxon. After confirming the capacity of selected probes to identify and discriminate viral species by <i>in silico</i> analysis, probes were synthesised without any linker or modifications and spotted on poly-l-lysine coated glass slides. The UPVM was validated with non-amplified amino-allyl labelled cDNA from nine healthy plants and more than 30 plants infected with characterized viruses. Validation is in progress with more samples from ATCC and ‘unknown’ samples. High-titre viruses could easily be detected and identified. For low-titre virus samples several strategies including increasing total RNA for labelling, depleting the host rRNAs and random-amplification are being tested. Comparison of hybridization profiles of healthy and infected plant samples identified a few non-specific reactions. Microarray data was also analyzed by hierarchical clustering and a predictive algorithm, T-Predict, to identify one or more viruses in a mixed infection.<p><p>Keywords:

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