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The current widely used molecular methods for detection and identification of viruses and viroids in plants, mostly RT-(q)PCR and Sanger sequencing, have their limitations. First of all, the need to make the right choice of the virus-specific molecular test has an important impact on the reliability of the test result. Secondly, in case of multiple infections, the correct conclusion is not always drawn, and thirdly, unexpected presence of viruses or viroids may easily remain unresolved and related symptoms may lead to the false conclusion of a “non parasitic cause”. Next generation sequencing (NGS) or deep sequencing follows a massively parallel sequencing (MPS) approach, a powerful technology offering a huge potential for holistic virus/viroid identification in all kinds of (suspected) plant tissues and this without preceding knowledge on the target sequences. Within the framework of the transnational EUPHRESCO project “NGS Detect”, a group of 15 partners is working towards developing and adapting a standardized NGS technology for viruses and viroids in plants. In a first series of experiments, ILVO has assessed several key aspects, starting from the subsampling procedure, up to the comparison of data analysis strategies, following NGS on an Illumina platform. Several host plants were used (e.g. apple, pear, potato, cherry), both with known and unknown virus infections. Initially, partial virus enrichment (purification by ultra centrifugation) was compared with a direct RNA extraction on the plant tissue. However, the virus purification procedure did not lead to sufficient RNA of yield and integrity to pass the quality control (QC) and was abandoned. Further, the effect of three total RNA extraction methods (Trizol and 2 kit extraction methods, RNeasy (Qiagen) and mirVana (Ambion)) on the NGS results were mutually compared. The results of these methods based on total RNA extraction were also compared to a protocol starting from small RNAs extracted directly from the plant tissue (mirVana (Ambion) siRNA extraction). In addition, the effect of rRNA depletion was evaluated. Library preparation and NGS were outsourced (Admera Health, USA). Finally, the data were analysed using in-house scripts and through an automated pipeline for virus detection in the NGS data (VirusDetect pipeline; Zheng et al. 2017). Currently, a comparison with a second automated pipeline (Virtool; ©2016 Canadian Food Inspection Agency) is being evaluated, both for the detection of known, and “new” viruses. All obtained NGS results were confirmed and evaluated by specific detection with the available classic molecular tools. The current evolution in continuous cost reduction for the routine use of NGS also lets presume that in the very near future, once an optimised strategy will be available, the technology may be widely implemented by plant virus research and diagnostic labs.
|The 12th EFPP-10th SFP conference abstract book
|Gepubliceerd - 30-jun.-2017
- 1 Afgerond