PVDP: A Portable Open Source Pipeline for Detection of Plant Viruses in RNAseq Data. A Case Study on Potato Viruses in Antioquia (Colombia)

High-throughput sequencing methods are becoming an essential tool in disease management programs. Unfortunately, the implementation of these techniques in developing countries can be hindered by a limited availability of well-trained bioinformaticians and/or high-performance computing centers that can process and analyze the data with reliability and speed. In this work we present a stand-alone plant virus detection pipeline (PVDP) optimized for the surveillance of potato viruses but also useful in other plant hosts. This open source pipeline runs under Python and includes a curated database of plant viruses in addition to an R script for presenting results as a user-friendly html report. The pipeline scripts are freely-available in GitHub, can be executed locally under LINUX, macOS or Windows, and does not require data submission to third-parties or access to high performance computing centers. The pipeline was calibrated using twelve previously obtained potato datasets and validated with new samples collected in Solanum tuberosum and S. phureja fields from eastern Antioquia (Colombia). The plant virus detection pipeline revealed high infection levels of PVY (1678.4 RPM) and lower levels of PMTV (1.2-2 RPM) infecting S. tuberosum. In S. phureja, the pipeline detected high infection levels of PVX, PVS and PVV (RPM > 2044) and lower levels of PMTV, PVY, and PYVV (RPM <82.1). Results also suggest the probable infection of S. phureja by pepino mosaic virus (PepMV) and by a putative unidentified potyvirus. Hopefully, this plant virus detection pipeline will facilitate the implementation of HTS methods in developing countries, such as Colombia, where there is an urgent need to improve the current plant and seed health standards.