Annual meeting, the Canadian phytopathological society, 2022/Réunion annuelle, la société canadienne de phytopathologie, 2022

Abstract

Emerging outbreaks of plant diseases pose enormous threat to agricultural production and global food security. Early detection and identification of plant pathogens using next-generation sequencing (NGS) technology and bioinformatics analysis are important to cope with the increase of international trade. Here, we present the PolyChrome bioinformatics toolkit for the detection and identification of regulated plant diseases. The PolyChrome toolkit con-sists of two programs, PolyChrome Detector (PCD) and PolyChrome Classifier (PCC). The former detects the presence of specific species from metagenomic and meta-transcriptomic data and the latter focus on the classification of closely related microorganisms at species or sub-species levels. In the PCD workflow, adapters and low-quality reads of raw NGS sequences are removed using Atria, an in-house designed trimming program. Clean reads are mapped to individual genomes, and then assembled to larger contigs, which are aligned to databases with taxonomy assignment. At the end of the pipeline, the annotated contigs are filtered with statistics on identity, alignment lengths, and bit scores, and suspected contigs of pathogens are reported. In PCC platform analysis, we first built curated PCC databases of selected regulated agents, e.g. Clavibacter, Liberibacter, Dickeya and Pectobacter , containing the genome sequences, anno-tations and the pre-analysis results, including average nucleotide identity (ANI) values. Testing dataset goes through the similar pipeline as PCD for contig generation and are classified using ANI values. The PolyChrome with PCD and PCC pipelines have been used to detect and identify plant pathogens, and has great potential in the detection of potato wart pathogen in soil.