Oral: Pathogen Detection
Comparison of two deep sequencing methods for the detection of viruses in sweet potato
R. LI (1), M. Cao (2), P. Lan (3), J. Abad (4), C. Zhou (5) (1) USDA-ARS, U.S.A.; (2) Southwest University of China, China; (3) Yunnan Agricultural University, China; (4) USDA-APHIS, U.S.A.; (5) Southwest University of China, China
Current methods used to detect viruses from imported accessions in plant germplasm quarantine programs face multiple challenges due to many pathogen targets, mixed infections and high genetic diversity of some pathogens. In this study, deep sequencing of small interfering RNAs (siRNAs) and RNAs (HiSeq) were compared using a sweet potato plant infected with five RNA viruses [Sweet potato chlorotic stunt virus, Sweet potato feathery mottle virus, Sweet potato virus C, Sweet potato virus G, Sweet potato virus 2] and two DNA viruses [Sweet potato leaf curl virus and Sweet potato symptomless 1]. Several bioinformatic approaches were used to resolve the viral genes and detect viruses and their quasispecies. Direct mapping of both read types against a crop-specific virus database resulted in rapid detection of the seven known viruses, whereas the blast search of assembled contigs from the HiSeq reads had low call on the DNA viruses. However, the genomic sequences of the viruses, especially the RNA viruses, were characterized to a high level of detail when analyzing the contigs from the HiSeq reads, enabling the detection of quasispecies. Deep sequencing is a powerful technique that can facilitate the detection and characterization of numerous pathogens in a single test, but both the sequencing strategy and data analysis aspects require careful consideration.