Location: Foreign Disease-weed Science ResearchTitle: E-probe Diagnostic Nucleic acid Analysis (EDNA): A theoretical approach for handling of next generation sequencing data for diagnostics Author
|Schneider, William - Bill|
Submitted to: Journal of Microbiological Methods
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/2/2013
Publication Date: 7/16/2013
Citation: Stobbe, A., Daniels, J., Espindola, A., Verma, R., Melcher, U., Ochoa-Corona, F., Garzon, C., Fletcher, J., Schneider, W.L. 2013. E-probe Diagnostic Nucleic acid Analysis (EDNA): A theoretical approach for handling of next generation sequencing data for diagnostics. Journal of Microbiological Methods. 94:356-366. 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. Many plant disease detection assays exist, but the vast majority of these assays are limited to identifying a single microbe at a time. 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, but the huge amount of data generated by the technology makes next-generation sequencing microbe detection difficult and unwieldy. To correct this problem, a new computer software tool was developed, 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 technology represents a significant step forward in turning a highly powerful sequencing technology into a very useful plant disease detection technology.
Technical Abstract: There are many plant pathogen-specific diagnostic assays, based on PCR and immune-detection. However, the ability to test for large numbers of pathogens simultaneously is lacking. Next generation sequencing (NGS) allows one to detect all organisms within a given sample, but has computational limitations during assembly and similarity searching of sequence data which extend the time needed to make a diagnostic decision. To minimize the amount of bioinformatic processing time needed, unique pathogen-specific sequences (termed e-probes) were designed to be used in searches of unassembled, non-quality checked, sequence data. E-probes have been designed and tested for several select phytopathogens, including an RNA virus, a DNA virus, bacteria, fungi, and an oomycete, illustrating the ability to detect several diverse plant pathogens. E-probes of 80 or more nucleotides in length provided satisfactory levels of specificity. The number of e-probes designed for each pathogen varied with the genome size of the pathogen. To give confidence to diagnostic calls, a statistical method of determining the presence of a given pathogen was developed, in which target e-probe signal (detection signal) are compared to a decoy set of e-probe signal (background signal). The E-probe Diagnostic Nucleic acid Assay (EDNA) process provides the framework for a new sequence-based detection system which eliminates the need for assembly of NGS data.