A new approach for detecting fungal and oomycete plant pathogens in next generation sequencing metagenome data utilising electronic probes
by Andres Espindola; William Schneider; Peter R. Hoyt; Stephen M. Marek; Carla Garzon
International Journal of Data Mining and Bioinformatics (IJDMB), Vol. 12, No. 2, 2015

Abstract: Early stage infections caused by fungal/oomycete spores may not be detected until signs or symptoms develop. Serological and molecular techniques are currently used for detecting these pathogens. Next-generation sequencing (NGS) has potential as a diagnostic tool, due to the capacity to target multiple unique signature loci of pathogens in an infected plant metagenome. NGS has significant potential for diagnosis of important eukaryotic plant pathogens. However, the assembly and analysis of huge amounts of sequence is laborious, time consuming, and not necessary for diagnostic purposes. Previous work demonstrated that a bioinformatic tool termed Electronic probe Diagnostic Nucleic acid Analysis (EDNA) had potential for greatly simplifying detecting fungal and oomycete plant pathogens in simulated metagenomes. The initial study demonstrated limitations for detection accuracy related to the analysis of matches between queries and metagenome reads. This study is a modification of EDNA demonstrating a better accuracy for detecting fungal and oomycete plant pathogens.

Online publication date: Fri, 15-May-2015

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