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Wiley Open Access, Molecular Plant Pathology, 4(14), p. 379-390, 2012

DOI: 10.1111/mpp.12014

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Identification of candidate effector genes in the transcriptome of the rice root-knot nematode Meloidogyne graminicola

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Data provided by SHERPA/RoMEO

Abstract

Plant-parasitic nematodes secrete so-called effectors into their host plant which are able to suppress the plant's defence responses, alter plant signalling pathways and, in the case of root knot nematodes, induce the formation of giant cells. Putative effectors have been successfully identified by genomics, transcriptomics and proteomics approaches. In this study, we investigated the transcriptome of the rice root knot nematode Meloidogyne graminicola by 454 sequencing of second-stage juveniles as well as mRNA-seq of rice infected tissue. Over 350000 reads derived from M.graminicola preparasitic juveniles were assembled, annotated and checked for homologues in different databases. From infected rice tissue, 1.4% of all reads generated were identified as being derived from the nematode. Using multiple strategies, several putative effector genes were identified, both pioneer genes and genes corresponding to already known effectors. To check whether these genes could be involved in the interaction with the plant, insitu hybridization was performed on a selection of genes to localize their expression in the nematode. Most were expressed in the gland cells or amphids of the nematode, confirming possible secretion of the proteins and hence a role in infection. Other putative effectors showed a different expression pattern, potentially linked with the excretory/secretory system. This transcriptome study is a good starting point to functionally investigate novel effectors derived from M.graminicola. This will lead to better insights into the interaction between these nematodes and the model plant rice. Moreover, the transcriptome can be used to identify possible target genes for RNA interference (RNAi)-based control strategies. Four genes proved to be interesting targets by showing up to 40% higher mortality relative to the control treatment when soaked in gene-specific small interfering RNAs (siRNAs).