Author
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MELCHER, ULRICH - Oklahoma State University |
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VERMA, RUCHI - Oklahoma State University |
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Schneider, William |
Submitted to: Frontiers in Plant Science
Publication Type: Peer Reviewed Journal Publication Acceptance Date: 6/1/2014 Publication Date: 6/11/2014 Citation: Melcher, U.K., Verma, R., Schneider, W.L. 2014. Metagenomic search strategies for interactions among plants and multiple microbes. Frontiers in Plant Science. DOI: 10.3389/fpls.2014.00268. Interpretive Summary: One of the most critical weapons in the fight against plant diseases is early detection, the ability to correctly identify the microbe that is causing a given disease outbreak. This is difficult enough, but an added challenge occurs when it becomes necessary to identify the cause of a completely novel plant disease. Many plant disease detection assays exist, but the vast majority of these assays are limited to identifying a single microbe at a time. In addition, none of these technologies are capable of identifying a new or unknown pathogen. A new technology, called next-generation sequencing, was developed for determining the genetic sequence of organisms. This technology has been used as a tool to detect microbes, using a new computer software tool called E-probe Diagnostic Nucleic acid Assay (EDNA). This tool has the ability to ignore a lot of the less useful information that is generated by next-generation sequencing technologies, seeking out microbial sequences of interest in a manner similar to a Google search of web pages. This paper discusses the application of EDNA to the detection and discovery of known and unknown viruses of plants. This technology represents a significant step forward in turning a highly powerful sequencing technology into a very useful plant disease detection technology. Technical Abstract: Next generation sequencing (NGS) is a highly processive form of sequencing that generates tremendous amounts of sequence data. Normally NGS is used for the generation of genome sequences for single organisms. However, the technology can also be applied to any environmental sample, where the large amount of data allows one to detect all organisms within a given sample. This type of sequencing is known as metagenomics. The downsides to a metagenomic approach to pathogen detection and discovery are the computational limitations during assembly and similarity searching of sequence data, which extend the time needed to make a diagnostic decision. Searching for novel pathogens in a metagenome is even more complex, as truly novel organisms may not be identified because of a lack of available relatives in searchable databases. This manuscript reviews the current approaches for metagenomic pathogen detection and discovery. Further, this study looks at E-probe Diagnostic Nucleic acid Assay (EDNA) as a successful tool for dealing with large volumes of complex metagenome data in a consistent and versatile manner. EDNA utility for detection and discovery of plant viruses is introduced. |