Plant biosecurity requires rapid identification of pathogenic organisms. While there are many pathogen-specific diagnostic assays, 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-specificsequences (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 selected 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 precision (75%). The number of e-probes designed for each pathogen variedwith the genome size of the pathogen. To give confidence to diag- nostic calls, a statistical method of determining the presence of a given pathogenwas developed, inwhich target e-probe signals (detection signal) are compared to signals generated by a decoy set of e-probes (background signal). The E-probe Diagnostic Nucleic acid Analysis (EDNA) process provides the framework for a newsequence-based detection system that eliminates the need for assembly of NGS data.
NGS produces billions of sequences, which theoretically will permit to retrieve information from various pathogens at the same time by using one sequencing run. Therefore, using NGS it is possible to sequence a potentially infected crop and analyze the sequencing output using bioinformatic tools like EDNA2.