Identification of emerging viral genomes in transcriptomic datasets of alfalfa (Medicago sativa L.)

Abstract

Background: Publicly available transcriptomic datasets have become a valuable tool for the discovery of new pathogens, particularly viruses. In this study, several coding-complete viral genomes previously not found or experimentally confirmed in alfalfa were identified in the plant datasets retrieved from the NCBI Sequence Read Archive. Methods: Publicly available Medicago spp. transcriptomic datasets were retrieved from the NCBI SRA database. The raw reads were first mapped to the reference genomes of Medicago sativa and Medigago truncatula followed by the alignment of the unmapped reads to the NCBI viral genome database and de novo assembly using the SPAdes tool. When possible, assemblies were experimentally confirmed using 5′/3′ RACE and RT-PCRs. Results: Twenty three different viruses were identified in the analyzed datasets, of which several represented emerging viruses not reported in alfalfa prior to this study. Among them were two strains of cnidium vein yellowing virus, lychnis mottle virus and Cactus virus X, for which coding-complete genomic sequences were obtained by a de novo assembly. Conclusions: The results improve our knowledge of the diversity and host range of viruses infecting alfalfa, provide essential tools for their diagnostics and characterization and demonstrate the utility of transcriptomic datasets for the discovery of new pathogens.