In silico identification of viruses and viroids infecting grapevine cultivar cabernet sauvignon using a grapevine transcriptome

Abstract

Next-generation sequencing (NGS)-based studies have reported a large amount of transcriptome data. In fact, plant transcriptome data sometimes contain sequence reads associated with viruses and viroids. Recently, we screened several grapevine transcriptomes to identify viruses and viroids that infect grapevine and we selected a transcriptome of the grapevine cultivar Cabernet Sauvignon for an in silico data analysis. After de novo assembly of raw data, the obtained contigs were blasted against a virus reference database. We identified five viruses and two viroids that infected the grapevine. We discovered that 2.16% of the transcriptome was comprised of viral RNAs, with more than half of the viral reads deriving from grapevine rupestris stem pitting-associated virus. However, the RNA populations of the two viroids were more than half of the total viral population based on the viral RNA copy number. Moreover, we identified single nucleotide polymorphisms for each virus and viroid and performed phylogenetic analyses. Taken together, we report the successful application of plant transcriptome data using bioinformatics analyses in the identification of five viruses and two viroids in the grapevine cultivar Cabernet Sauvignon, which is one of the most important grapevine cultivars in the world.