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Clubroot, a soil-borne disease caused by the obligate parasite Plasmodiophora brassicae Woronin, is a threat to canola (Brassica napus L.) production in western Canada. Genetic resistance represents the most effective tool to manage this disease. However, given the rapid spread of clubroot and the emergence of new virulent pathotypes of P. brassicae, it is important to accelerate the resistance breeding effort. The advent of genome-sequencing technologies has created a new toolbox that can aid in breeding strategies. Many genomic approaches, such as genotyping-by-sequencing, high-density single nucleotide polymorphism (SNP) arrays, genome-wide association studies, and transcriptomic approaches such as bulked segregant RNA-seq analysis and microarray/RNA-seq differential expression analysis have been applied to studies of clubroot resistance or susceptibility. Here, we review the impact of traditional marker-assisted selection-based breeding for clubroot resistance, and then discuss how omics approaches have contributed to the (1) detection and genotyping of genome-wide SNP markers linked with clubroot resistance genes or quantitative trait loci, (2) understanding of host resistance mechanisms upon P. brassicae infection, and (3) acceleration of resistance breeding by identifying and characterizing candidate genes, especially those with differential efficacy against new pathotypes of P. brassicae. We suggest that the use of different omics approaches together could improve the efficiency of clubroot-resistance breeding. Finally, we propose that the CRISPR/Cas9 system for genome editing is a promising tool to facilitate the validation and use of candidate genes for clubroot-resistance breeding. [ABSTRACT FROM AUTHOR]

Species of Phytophthora pose one of the most serious biosecurity threats to forest ecosystems worldwide. Despite management efforts and increased awareness of forest pathogens, there is continued introduction and spread of Phytophthora species. Uncertainty about the center of origin for many of the invasive species hampers disease control efforts. Additionally, the management efforts are often made impossible either by the vast host range or the extreme susceptibility of naïve hosts. In this review, we discuss how genomics has shed light on the extent of spread and destruction caused by invasive Phytophthora species, and how approaches leveraged by genomics can be applied to enhance the management of these invasive forest pathogens. Four case studies, Phytophthora ramorum, Phytophthora lateralis, Phytophthora cinnamomi, and Phytophthora pluvialis are used to illustrate how genomics can be applied to forest management. We urge researchers, governmental research institutes, private companies, and citizens to collaborate in order to stop the spread of invasive Phytophthora species. To accomplish this, we see the following themes as critical parts of resolving this forest health crisis: i) integration of DNA-based pathogen detection into forest inventory programs; ii) development of practical and affordable DNA-based diagnostic methods; iii) sequence hosts as models for resistance gene identification; iv) prediction of pathogen impact based on genomic data; and v) increase collaborative projects and outreach to raise awareness of forest diseases. [ABSTRACT FROM AUTHOR]

Globalization has allowed for rapid movement of plant pathogens that threaten food security. Successful disease management largely depends on timely and accurate detection of plant pathogens causing epidemics. Thus, biosurveillance of epidemic plant pathogens such asPseudoperonospora cubensis, the causal agent of cucurbit downy mildew, is becoming a priority to prevent disease outbreaks and deploy successful control efforts. Next Generation Sequencing (NGS) facilitates rapid development of genomics resources needed to generate molecular diagnostics assays forP. cubensis. Having information regarding the presence or absence of the pathogen, amount of inoculum, crop risk, time to initiate fungicide applications, and effective fungicides to apply would significantly contribute to reducing losses to cucurbit downy mildew. In this article, we discuss approaches to identify unique loci for rapid molecular diagnostics using genomic data, to develop molecular diagnostic tools that discriminate economically important pathogen alleles (i.e. mating type and fungicide resistance), and how to use molecular diagnostics with current and future spore trap strategies for biosurveillance purposes of important downy mildew pathogens. The combined use of these technologies within the already existent disease management framework has the potential to improve disease control. [ABSTRACT FROM PUBLISHER]

The genetic basis for the interaction(s) between plants and pathogens has been classically illustrated as a gene-for-gene relationship, through which a single gene product from the pathogen interacts within a single gene product found within the plant. In the simplest terms, it is the outcome of these interactions that underpin resistance and/or susceptibility signalling processes. While this basic concept shapes our understanding of many of the molecular-genetic mechanisms controlling immune signalling in plants, current research has revealed that the timing and ultimate outcome of these interactions are far more complex, and are typically regulated in a genome-by-genome manner. As a central theme for this review, we will focus on recent discoveries in the field of plant-oomycete interactions, primarily on the downy mildews, an important group of obligate oomycete pathogens of plants. Recent transcriptome-based studies have shown that survival, adaptation and virulence rely on complex, bi-directional interactions between the host and pathogen genomes. Taking advantage of the obligate nature of the downy mildews, insight into the transcriptional plasticity of these genomes has revealed a remarkable ability to adapt to host and environmental stressors. Herein, we will highlight a recent body of research using thePseudoperonospora cubensis – Cucumis sativusinteraction, which has identified a suite of alternative splicing and sRNA-based regulatory signals that are induced in a temporal and host-specific manner. In combination with recent studies in other plant-oomycete pathosystems, a comprehensive transcriptional profile of resistance and susceptibility within the host and pathogen illustrates the remarkable ability of this group of pathogens to adapt to host and environment to infect and cause disease in a diverse array of agriculturally important crops. [ABSTRACT FROM AUTHOR]

Worldwide, forest pathogens are a major cause of forest disturbances and can impact economic revenues and endanger host species and their ecosystems. Genomics represents one of the most promising avenues to better understand and prevent forest disease epidemics. Pathogen genome characterization and comparison at the individual and population levels make it possible to identify both common and unique genome regions. Genes in these regions can be translated into detection and monitoring assays. Tools can be developed and applied to improve our ability to recognize, detect and monitor pathogens, to prevent introductions of unwanted pathogens, and to monitor the spread and migration of established ones. Population genome re-sequencing can reveal population processes including gene flow, selection and adaptation. These tools can be applied to detecting pathogens that are targeted by quarantine, certification of import and export material, and pathogen surveillance and risk assessment. [ABSTRACT FROM AUTHOR]

The article discusses the identification and phylogenetic analysis of sequences of bean pod mottle virus (BPMV), soybean mosaic virus and cowpea chlorotic mottle virus in expressed sequence tag data from soybean. The soybean sequence was derived from the North Central and Northern Great Plains regions, where an outbreak of BPMV has been reported. The strains of BPMV may be a mixture of different BPMV RNA-1 and RNA-2 genotypes.