Agriculture and Agri-Food Canada

About: Agriculture and Agri-Food Canada is a facility organization based out in Ottawa, Ontario, Canada. It is known for research contribution in the topics: Population & Soil water. The organization has 10921 authors who have published 21332 publications receiving 748193 citations. The organization is also known as: Department of Agriculture and Agri-Food.

Copy Number Variation and Transcriptional Polymorphisms of Phytophthora sojae RXLR Effector Genes Avr1a and Avr3a

Abstract: The importance of segmental duplications and copy number variants as a source of genetic and phenotypic variation is gaining greater appreciation, in a variety of organisms. Now, we have identified the Phytophthora sojae avirulence genes Avr1a and Avr3a and demonstrate how each of these Avr genes display copy number variation in different strains of P. sojae. The Avr1a locus is a tandem array of four near-identical copies of a 5.2 kb DNA segment. Two copies encoding Avr1a are deleted in some P. sojae strains, causing changes in virulence. In other P. sojae strains, differences in transcription of Avr1a result in gain of virulence. For Avr3a, there are four copies or one copy of this gene, depending on the P. sojae strain. In P. sojae strains with multiple copies of Avr3a, this gene occurs within a 10.8 kb segmental duplication that includes four other genes. Transcriptional differences of the Avr3a gene among P. sojae strains cause changes in virulence. To determine the extent of duplication within the superfamily of secreted proteins that includes Avr1a and Avr3a, predicted RXLR effector genes from the P. sojae and the P. ramorum genomes were compared by counting trace file matches from whole genome shotgun sequences. The results indicate that multiple, near-identical copies of RXLR effector genes are prevalent in oomycete genomes. We propose that multiple copies of particular RXLR effectors may contribute to pathogen fitness. However, recognition of these effectors by plant immune systems results in selection for pathogen strains with deleted or transcriptionally silenced gene copies.

Mass spectrometry-based metabolomics application to identify quantitative resistance-related metabolites in barley against Fusarium head blight.

Abstract: Quantitative resistance is generally controlled by several genes. More than 100 resistance quantitative trait loci (QTLs) have been identified in wheat and barley against Fusarium head blight (FHB), caused by Gibberella zeae (anamorph: Fusarium graminearum), implying the possible occurrence of several resistance mechanisms. The objective of this study was to apply metabolomics to identify the metabolites in barley that are related to resistance against FHB. Barley genotypes, Chevron and Stander, were inoculated with mock or pathogen during the anthesis stage. The disease severity was assessed as the proportion of spikelets diseased. The genotype Chevron (0.33) was found to have a higher level of quantitative resistance than Stander (0.88). Spikelet samples were harvested at 48 h post-inoculation; metabolites were extracted and analysed using an LC-ESI-LTQ-Orbitrap (Thermo Fisher, Waltham, MA, USA). The output was imported to an XCMS 1.12.1 platform, the peaks were deconvoluted and the adducts were sieved. Of the 1826 peaks retained, a t-test identified 496 metabolites with significant treatment effects. Among these, 194 were resistance-related (RR) constitutive metabolites, whose abundance was higher in resistant mock-inoculated than in susceptible mock-inoculated genotypes. Fifty metabolites were assigned putative names on the basis of accurate mass, fragmentation pattern and number of carbons in the formula. The RR metabolites mainly belonged to phenylpropanoid, flavonoid, fatty acid and terpenoid metabolic pathways. Selected RR metabolites were assayed in vitro for antifungal activity on the basis of fungal biomass production. The application of these RR metabolites as potential biomarkers for screening and the potential of mass spectrometry-based metabolomics for the identification of gene functions are discussed.