LAUSR

BackgroundColletotrichum is a fungal genus in Ascomycota that contain many plant pathogens. Among all Colletotrichum genomes that have been sequenced, C. fructicola contains the largest number of candidate virulence factors, such as plant cell wall degrading enzymes, secondary metabolite (SM) biosynthetic enzymes, secreted proteinases, and small secreted proteins. Systematic analysis of the expressional patterns of these factors would be an important step toward identifying key virulence determinants.ResultsIn this study, we obtained and compared the global transcriptome profiles of four types of infection-related structures: conidia, appressoria, infected apple leaves, and cellophane infectious hyphae (bulbous hyphae spreading inside cellophane) of C. fructicola. We also compared the expression changes of candidate virulence factors among these structures in a systematic manner. A total of 3189 genes were differentially expressed in at least one pairwise comparison. Genes showing in planta-specific expressional upregulations were enriched with small secreted proteins (SSPs), cytochrome P450s, carbohydrate-active enzymes (CAZYs) and secondary metabolite (SM) synthetases, and included homologs of several known candidate effectors and one SM gene cluster specific to the Colletotrichum genus. In conidia, tens of genes functioning in triacylglycerol biosynthesis showed coordinately expressional upregulation, supporting the viewpoint that C. fructicola builds up lipid droplets as energy reserves. Several phosphate starvation responsive genes were coordinately up-regulated during early plant colonization, indicating a phosphate-limited in planta environment immediately faced by biotrophic infectious hyphae.ConclusionThis study systematically analyzes the expression patterns of candidate virulence genes, and reveals biological activities related to the development of several infection-related structures of C. fructicola. Our findings lay a foundation for further dissecting infection mechanisms in Colletotrichum and identifying disease control targets.