Applications of Next-Generation Sequencing for Large-Scale Pathogen Diagnoses in Soybean

Abstract

Soybean (Glycine max) has become an important crop in Manitoba, Canada, with a 10-fold increase in dedicated acreage over the past decade. Given the rapid increase in production, scarce information about foliar diseases present in the province has been recorded. In order to describe the foliar pathogens affecting this legume, we harnessed next-generation sequencing (NGS) to carry out a comprehensive survey across Manitoba in 2016. Fields were sampled during the V2/3 (33 fields) and R6 (70 fields) growth stages, with at least three symptomatic leaves per field collected and subjected to RNA sequencing. We successfully detected several bacteria, fungi, and viruses known to infect soybean, including Pseudomonas savastanoi pv. glycinea, Septoria glycines, and Peronospora manshurica, as well as pathogens not previously identified in the province (e.g., Pseudomonas syringae pv. tabaci, Cercospora sojina, and Bean yellow mosaic virus). For some microorganisms, we were able to disentangle the different pathovars present and/or assemble their genome sequence. Since NGS generates data on the entire flora and fauna occupying a leaf sample, we also identified residual pathogens (i.e., pathogens of crops other than soybean) and multiple species of arthropod pests. Finally, the sequence information produced by NGS allowed for the development of polymerase chain reaction-based diagnostics for some of the most widespread and important pathogens. Although there are many benefits of using NGS for large-scale plant pathogen diagnoses, we also discuss some of the limitations of this technology.