2012 Annual Report
1a.Objectives (from AD-416):
To develop a universal plant virus micro array for detection and identification of plant viruses.
1b.Approach (from AD-416):
Develop microarrray containing probes representing all known plant viruses.
Most virus detection methods are specific for a single virus or closely-related viruses, and are unable to detect viruses that have not previously been characterized. It is thus possible to detect only the specific viruses tested for, and not possible to identify all components of the mixed infections common in vegetatively-propagated plants. It is highly desirable to have a method that can detect any virus, including previously uncharacterized viruses, and to identify all components of mixed infections. ARS researchers at Beltsville, MD in collaboration with scientists at the Danforth Science Center, Washington University, University of Utah, Oklahoma State University, and Cornell University, have developed a Universal Plant Virus Microarray (UPVM) with funding from the USDA NRI Plant Biosecurity program (grant no. 2009-55605-05023). Work at Beltsville has concentrated on increasing the sensitivity of detection of viruses occurring at low titer, as initial protocols (direct labeling of cDNA; or unbiased ABC amplification) did not yield reliable results. A subtractive hybridization protocol utilizing a duplex specific nuclease to reduce high-copy sequences such as ribosomal RNA, from samples, followed by the ABC amplification protocol, has allowed detection of several viruses not detected by previous methods. This protocol is significantly cheaper than subtractive hybridization using commercially-available kits. The duplex specific nuclease method has also allowed detection of a mixed infection in a sample previously known to be infected by only one virus. Collaborators at the Danforth Science Center have also increased sensitivity either by using significantly higher levels of sample nucleic acids, or by use of commercial subtractive hybridization kits; they also evaluated both diseased and healthy samples of several plant species in order to identify non-specific reactions of several of the 60-mer UPVM probes. These results, and improvements to the iterative T-predict analysis at the University of Utah, aid the interpretation of UPVM hybridization results. Additional printings of the UPVM were made using a different print layout, reducing the print time by about half. Extracts of virus-infected grapevines were prepared at Cornell University and sent to the Danforth Science Center for testing. At Oklahoma State University the UPVM probes were used to screen high-throughput sequencing data, aiding the identification of viral sequences with 100% specificity, over 80% accuracy of identification, and no false positives. Some of these results were presented at the UPVM Workshop and BARD Workshop ‘Microarrays and Next-Generation Sequencing for Detection and Identification of Plant Viruses’ held at Beltsville in November 2011. This information will be of most immediate application to the UPVM collaborators, but will also be of value to regulatory agencies, plant diagnostic clinics, germplasm repositories, and producers operating plant certification schemes.