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Aigu, Y.

Publications and source records attributed to Aigu, Y..

3 recordsLinked to original sources

Global population genomics and pangenome of the clubroot pathogen link clonal expansion and effector diversification to resistance breakdown in canola

Clubroot disease, caused by the obligate biotrophic protist Plasmodiophora brassicae, threatens Brassica crops worldwide. Novel pathogen virulence frequently breaks resistance in agricultural crops, and yet explanations for isolate evolution remain unknown. We combined whole genome sequencing of 192 isolates from 24 countries with a pangenome analysis of 55 high-quality complete or nearly complete genome assemblies and performed functional effector analyses to investigate potential mechanisms of virulence emergence. Three major phylogenetic clusters were identified, including two highly clonal lineages with contrasting virulence profiles, and a genetically diverse population retaining signatures of recombination. Our findings support a model in which genome-wide purifying selection maintained core genome integrity, while effector genes evolved under less constraint. Despite a compact closed pangenome, we identified chromosome 17 as a major hotspot of single nucleotide and structural variations, transposable elements and expansion of ankyrin repeat effectors. Within the variable chromosome 17, PbAnk2 alleles from virulent and avirulent isolates encoded proteins with distinct predicted structures. PbAnk2 interacted with the Arabidopsis co-chaperone DJC31 in yeast two-hybrid and BiFC assays, whereas co-immunoprecipitation did not detect an interaction for the allele found in isolates that break CRa-mediated resistance, suggesting that allelic variation may alter PbAnk2's association with DJC31. These findings reveal the clonal expansion of virulent isolates and connect it to effector diversification that led to resistance breakdown and establish a genomic framework for pathogen surveillance and durable clubroot resistance.

genomics↗

Natural epiallelic variation is associated with quantitative resistance to the pathogen Plasmodiophora brassicae

Clubroot caused by the protist Plasmodiophora brassicae is a major disease affecting cultivated Brassicaceae. Here, we uncover the existence of a natural epigenetic variation that is associated with partial resistance to clubroot in Arabidopsis, by using QTL fine mapping followed by extensive DNA sequence and methylation analyses. We show that at QTL Pb-At5.2, DNA methylation variation is extensive across accessions and strictly correlates with expression variation of the two neighboring genes At5g47260 and At5g47280, which encode NLR-immune receptors. Moreover, these natural variants are stably inherited and are not consistently associated with any nucleotide variation. These findings suggest a direct role for epigenetic variation in quantitative resistance of plants to pathogen attacks.

genetics↗

Computational analysis of the Plasmodiophora brassicae genome: mitochondrial sequence description and metabolic pathway database design

Plasmodiophora brassicae is an obligate biotrophic pathogenic protist responsible for clubroot, a root gall disease of Brassicaceae species. In addition to the reference genome of the P. brassicae European e3 isolate and the draft genomes of Canadian or Chinese isolates, we present the genome of eH, a second European isolate. Refinement of the annotation of the eH genome led to the identification of the mitochondrial genome sequence, which was found to be bigger than that of Spongospora subterranea, another plant parasitic Plasmodiophorid phylogenetically related to P. brassicae. New pathways were also predicted, such as those for the synthesis of spermidine, a polyamine up-regulated in clubbed regions of roots. A P. brassicae pathway genome database was created to facilitate the functional study of metabolic pathways in transcriptomics approaches. These available tools can help in our understanding of the regulation of P. brassicae metabolism during infection and in response to diverse constraints.

genomics↗