Combined DECS Analysis and Next-Generation Sequencing Enable Efficient Detection of Novel Plant RNA Viruses

Abstract

The presence of high molecular weight double-stranded RNA (dsRNA) within plant cells is an indicator of infection with RNA viruses as these possess genomic or replicative dsRNA. DECS (dsRNA isolation, exhaustive amplification, cloning, and sequencing) analysis has been shown to be capable of detecting unknown viruses. We postulated that a combination of DECS analysis and next-generation sequencing (NGS) would improve detection efficiency and usability of the technique. Here, we describe a model case in which we efficiently detected the presumed genome sequence of Blueberry shoestring virus (BSSV), a member of the genus Sobemovirus, which has not so far been reported. dsRNAs were isolated from BSSV-infected blueberry plants using the dsRNA-binding protein, reverse-transcribed, amplified, and sequenced using NGS. A contig of 4,020 nucleotides (nt) that shared similarities with sequences from other Sobemovirus species was obtained as a candidate of the BSSV genomic sequence. Reverse transcription (RT)-PCR primer sets based on sequences from this contig enabled the detection of BSSV in all BSSV-infected plants tested but not in healthy controls. A recombinant protein encoded by the putative coat protein gene was bound by the BSSV-antibody, indicating that the candidate sequence was that of BSSV itself. Our results suggest that a combination of DECS analysis and NGS, designated here as “DECS-C,” is a powerful method for detecting novel plant viruses.

Keywords

• deep-sequencing
• dsRNA
• dsRNA-binding protein
• detection
• blueberry
• Sobemovirus
• Blueberry shoestring virus