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PLOS ONE  2014 

Transcriptomics of the Interaction between the Monopartite Phloem-Limited Geminivirus Tomato Yellow Leaf Curl Sardinia Virus and Solanum lycopersicum Highlights a Role for Plant Hormones, Autophagy and Plant Immune System Fine Tuning during Infection

DOI: 10.1371/journal.pone.0089951

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Abstract:

Tomato yellow leaf curl Sardinia virus (TYLCSV), a DNA virus belonging to the genus Begomovirus, causes severe losses in tomato crops. It infects only a limited number of cells in the vascular tissues, making difficult to detect changes in host gene expression linked to its presence. Here we present the first microarray study of transcriptional changes induced by the phloem-limited geminivirus TYLCSV infecting tomato, its natural host. The analysis was performed on the midrib of mature leaves, a material naturally enriched in vascular tissues. A total of 2206 genes were up-regulated and 1398 were down-regulated in infected plants, with an overrepresentation of genes involved in hormone metabolism and responses, nucleic acid metabolism, regulation of transcription, ubiquitin-proteasome pathway and autophagy among those up-regulated, and in primary and secondary metabolism, phosphorylation, transcription and methylation-dependent chromatin silencing among those down-regulated. Our analysis showed a series of responses, such as the induction of GA- and ABA-responsive genes, the activation of the autophagic process and the fine tuning of the plant immune system, observed only in TYLCSV-tomato compatible interaction so far. On the other hand, comparisons with transcriptional changes observed in other geminivirus-plant interactions highlighted common host responses consisting in the deregulation of biotic stress responsive genes, key enzymes in the ethylene biosynthesis and methylation cycle, components of the ubiquitin proteasome system and DNA polymerases II. The involvement of conserved miRNAs and of solanaceous- and tomato-specific miRNAs in geminivirus infection, investigated by integrating differential gene expression data with miRNA targeting data, is discussed.

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