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Transcription profiling and identification of infection-related genes in Phytophthora cactorum

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Phytophthora cactorum, an oomycete pathogen, infects more than 200 plant species within several plant families. To gain insight into the repertoire of the infection-related genes of P. cactorum, Illumina RNA-Seq… Click to show full abstract

Phytophthora cactorum, an oomycete pathogen, infects more than 200 plant species within several plant families. To gain insight into the repertoire of the infection-related genes of P. cactorum, Illumina RNA-Seq was used to perform a global transcriptome analysis of three life cycle stages of the pathogen, mycelia (MY), zoospores (ZO) and germinating cysts with germ tubes (GC). From over 9.8 million Illumina reads for each library, 18,402, 18,569 and 19,443 distinct genes were identified for MY, ZO and GC libraries, respectively. Furthermore, the transcriptome difference among MY, ZO and GC stages was investigated. Gene ontology (GO) and KEGG pathway enrichment analyses revealed diverse biological functions and processes. Comparative analysis identified a large number of genes that are associated with specific stages and pathogenicity, including 166 effector genes. Of them, most of RXLR and NLP genes showed induction while the majority of CRN genes were down-regulated in GC, the important pre-infection stage, compared to either MY or ZO. And 14 genes encoding small cysteine-rich (SCR) secretory proteins showed differential expression during the developmental stages and in planta. Ectopic expression in the Solanaceae indicated that SCR113 and one elicitin PcINF1 can trigger cell death on Nicotiana benthamiana, tobacco (N. tabacum) and tomato (Solanum lycopersicum) leaves. Neither conserved domain nor homologues of SCR113 in other organisms can be identified. Collectively, our study provides a comprehensive examination of gene expression across three P. cactorum developmental stages and describes pathogenicity-related genes, all of which will help elucidate the pathogenicity mechanism of this destructive pathogen.

Keywords: infection; infection related; transcription profiling; related genes; phytophthora cactorum; profiling identification

Journal Title: Molecular Genetics and Genomics
Year Published: 2017

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