Transcriptome analysis of Phoenix canariensis Chabaud in response to Rhynchophorus ferrugineus Olivier attacks

Abstract

Red Palm Weevil (RPW, Rhynchophorus ferrugineus Olivier) threatens most palm species worldwide. Until now, no studies have analyzed the gene regulatory networks of Phoenix canariensis (Chabaud) in response to RPW attacks. The aim of this study was to fill this knowledge gap. Providing this basic knowledge is very important to improve its management.Results: A deep transcriptome analysis was performed on fully expanded leaves of healthy non-infested trees and attacked trees at two symptom stages (middle and late infestation). A total of 54 genes were significantly regulated during middle stage. Pathway enrichment analysis showed that phenylpropanoid-related pathways were induced at this stage. More than 3300 genes were affected during late stage of attacks. Higher transcript abundances were observed for lipid fatty acid metabolism (fatty acid and glycerolipids), tryptophan metabolism, phenylpropanoid metabolism. Key RPW-modulated genes involved in innate response mediated by hormone crosstalk were observed belonging to auxin, jasmonate and salicylic acid (SA) pathways. Among transcription factors, some WRKYs were clearly induced. qRT-PCR validation confirmed the upregulation of key genes chosen as validation of transcriptomic analysis.Conclusion: A subset of these genes may be further analyzed in future studies to confirm their specificity to be induced by RPW infestations.

Members of the WRKY gene family are upregulated in Canary palms attacked by Red Palm Weevil

“…The rationale of this work was to determine if a subset of host RPW-regulated genes identified in a previous study (Giovino et al 2015) was able to effectively help in the detection and confirmation of symptomatology of RPW infestation in Phoenix canariensis Hort. ex Chabaud.…”

“…ex Chabaud. We aimed at dividing the genes in two groups: (1) genes encoding transcription factors modulating plant responses to biotic stresses, (2) previously identified RPW-regulated genes not Table 1 ANOVA analysis of expression data of a subset of genes involved in pathways not involved in biotic stress responses The choice of these genes was based on the previous transcriptomic analysis conducted by Giovino et al (2015). Relative quantification analysis using qRT-PCR was performed based on ΔΔC T and using 18S (AF206991.1) as an endogenous reference.…”

“…However, these induced volatiles do not have high specificity and sensitivity. A transcriptome profiling at two symptomatic stages has been conducted with Next-Generation Sequencing (NGS) to elucidate early and late mechanisms of symptoms progression, and to identify early host biomarkers that may be used to help diagnosis of the RPW infestations (Giovino et al 2015). This approach was shown to be effective in identifying possible candidate to improve detection of diseases in crops (Martinelli et al 2016).…”

“…An important goal for the RPW management will be the identification of RPW-regulated genes associated with the symptomatology in order to analyse them with both lab or infield instruments. Previous transcriptomic and metabolomic analysis highlighted the upregulation of pathways linked with biotic stress response as well as the early induction of some members of WRKY transcription factors (Giovino et al 2015(Giovino et al , 2016.…”

Proposed Research for Innovative Solutions for Chickpeas and Beans in a Climate Change Scenario: The Mediterranean Basin

“…Expected outcomes of this objective will be (1) the identification of thousands of methylation sites and single nucleotide polymorphisms (SNPs) linked with tolerance/susceptibility to these environmental constraints, (2) the establishment of the link between epigenetic information and previous identified molecular clusters in model legumes such as bean or chickpea (Table 1). Similar approaches have been performed to identify key players in molecular regulatory networks in plant responses to environmental stresses [35][36][37]. Thanks to the agronomic evaluation of first objective, we would select one bean genotype with high resistance and one genotype with high susceptibility to drought stress.…”