Abstract
Virus infection of plants may induce a variety of disease symptoms. However, little is known about the molecular mechanism of systemic symptom development in infected plants. Here we performed the first next-generation sequencing study to identify gene expression changes associated with disease development in tobacco plants (Nicotiana tabacum cv. Xanthi nc) induced by infection with the M strain of Cucumber mosaic virus (M-CMV). Analysis of the tobacco transcriptome by RNA-Seq identified 95,916 unigenes, 34,408 of which were new transcripts by database searches. Deep sequencing was subsequently used to compare the digital gene expression (DGE) profiles of the healthy plants with the infected plants at six sequential disease development stages, including vein clearing, mosaic, severe chlorosis, partial and complete recovery, and secondary mosaic. Thousands of differentially expressed genes were identified, and KEGG pathway analysis of these genes suggested that many biological processes, such as photosynthesis, pigment metabolism and plant-pathogen interaction, were involved in systemic symptom development. Our systematic analysis provides comprehensive transcriptomic information regarding systemic symptom development in virus-infected plants. This information will help further our understanding of the detailed mechanisms of plant responses to viral infection.
Highlights
Understanding the responses of plant hosts to viral infection is important for developing strategies for disease control
The disease development induced by M strain of Cucumber mosaic virus (M-Cucumber mosaic virus (CMV)) includes the initial and secondary pathogenesis processes that are interrupted by a transient recovery
Leaves above the inoculated leaves or emerged after inoculation with M-CMV representing the six stages were collected for RNA extraction on 6, 9, 11, 13, 16 and 20 dpi, respectively
Summary
Understanding the responses of plant hosts to viral infection is important for developing strategies for disease control. Next-generation deep-sequencing techniques such as Solexa/Illumina RNA-Seq and digital gene expression (DGE) have provided new approaches for studying the transcriptome, and have several advantages over microarray analysis [17,18,19,20]. DGE sequences short tags (usually about 20 bp) generated by endonucleases from the 39 ends of genes and the copy number of each tag indicates the expression level of the corresponding gene. This tag-based sequencing method is suitable and cost-effective for genome-wide expression profiling to analyze gene expression levels [25,26,27]. Many transcriptome studies have been carried out using RNA-Seq and/or DGE and these studies have greatly extended our knowledge of the complexity of eukaryotic transcriptomes [21,22,23,24,25,26,27,28,29,30]
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