European Journal of Plant Pathology

, Volume 147, Issue 1, pp 211–228 | Cite as

Putative pathogenicity genes of Phytophthora cinnamomi identified via RNA-Seq analysis of pre-infection structures

  • Anandi Reitmann
  • Dave K. Berger
  • Noëlani van den BergEmail author


Phytophthora cinnamomi is an economically important oomycete that infects more than 3,000 plant species. We aimed to identify the repertoire of genes expressed during pre-infection stages by analysing an RNA-Seq library of cysts and germinating cysts of a P. cinnamomi isolate, originating from Persea americana. Over 70,000 transcripts were identified from 225,049 contigs, assembled from 13 million Illumina paired-end reads. Contaminant sequences were eliminated, resulting in 37,534 transcripts used in further analysis. A total of 1394 transcripts had a putative role in pathogenesis. Genes aiding in detoxification and metabolite transport (cytochrome P450 and ABC transporters) and protection against oxidative stress were most abundant, followed by the genes coding cell wall degrading enzymes. The transcript set included 44 putative RXLR effector genes and genes encoding elicitin and necrosis-inducing proteins. Expression patterns of seven putative pathogenicity genes (encoding RXLR-, necrosis-inducing Phytophthora protein 1 (NPP1), elicitin, polygalacturonase, cellulose binding and elicitor lectin (CBEL), mucin, and adhesion proteins) were assessed across four in vitro developmental stages of P. cinnamomi. High expression of these genes in zoospores suggests their functional importance in the subsequent developmental stage, germination of cysts, implying a role in pre-infection. This work is the first step towards understanding the molecular basis of infection strategies employed by P. cinnamomi.


Phytophthora cinnamomi Pathogenicity Expression analysis RXLR Oomycete 



The financial assistance of the National Research Foundation (NRF) and The Hans Merensky Foundation, towards this research is hereby acknowledged. Opinions expressed and conclusions arrived at, are those of the authors and are not necessarily to be attributed to the NRF and HMF. We thank Paul Birch and Remco Stam (The James Hutton Institute, Scotland) for predicting putative RXLR proteins from contigs generated by Beijing Genomics Institute, and Fourie Joubert and Nanette Christie for assisting with general bioinformatics analysis.

Author contributions

NvdB and A.R conceived and designed the experiments. A.R conducted the experiments, analysed the data and wrote the manuscript. NvdB and D.K.B provided guidance with data analysis and revised the manuscript. All authors reviewed the manuscript.

Compliance with ethical standards

Competing financial interests

The authors declare no competing financial interests or conflict of interest.

Supplementary material

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Copyright information

© Koninklijke Nederlandse Planteziektenkundige Vereniging 2016

Authors and Affiliations

  • Anandi Reitmann
    • 1
  • Dave K. Berger
    • 2
  • Noëlani van den Berg
    • 3
    Email author
  1. 1.Department of Genetics, Forestry and Agricultural Biotechnology InstituteUniversity of PretoriaPretoriaSouth Africa
  2. 2.Department of Plant Science, Forestry and Agricultural Biotechnology InstituteUniversity of PretoriaPretoriaSouth Africa
  3. 3.Department of Microbiology and Plant Pathology, Forestry and Agricultural Biotechnology InstituteUniversity of PretoriaPretoriaSouth Africa

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