Virus detection in naturally infected plants using high-throughput sequencing
F. GAWEHNS (1), E. Meekes (1), I. Stulemeijer (2), M. de Kock (2), M. Ebskamp (1) (1) Naktuinbouw, Netherlands; (2) BKD, Netherlands

Despite the wide acceptance, robustness and low costs of traditional screening methods like ELISA and PCR, viruses can be missed using targeted detection. The number of unidentified viruses in plants is estimated to be relatively high due to a fast mutation rate, host specificity or low abundance. They can cause novel disease symptoms, can be part of a virus complex or can be present without showing any symptoms. Using the non-targeted high-throughput sequencing of RNA from infected leaves, both known and unknown viruses can be detected. RNA, including small RNAs, was isolated from different horticultural plants that were naturally infected and showed clear disease symptoms. The total RNA fraction (>200 nt) or the small RNA fraction (~21-24 nt) was sequenced and virus identification was performed using an in-house pipeline and virus database. All known viruses (including a viroid) could be identified with both methods. Small RNA sequencing, however, reached a by far higher mapping percentage and sensitivity. We also show that small RNA sequencing is suitable to detect mixed infections by a virus complex or different virus strains, and to identify viruses de novo. In conclusion, we prove that RNA sequencing is a valuable method for the Dutch Inspection services and can be used as a safety net or to discover unknown viruses.

Abstract Number: P11-357
Session Type: Poster