Viral Diagnostics in Plants Using Next Generation Sequencing: Computational Analysis in Practice

Abstract

Viruses cause significant yield and quality losses in a wide variety of cultivated crops. Hence, the detection and identification of viruses is a crucial facet of successful crop production and of great significance in terms of world food security. Whilst the adoption of molecular techniques such as RT-PCR has increased the speed and accuracy of viral diagnostics, such techniques only allow the detection of known viruses, i.e., each test is specific to one or a small number of related viruses. Therefore, unknown viruses can be missed and testing can be slow and expensive if molecular tests are unavailable. Methods for simultaneous detection of multiple viruses have been developed, and (NGS) is now a principal focus of this area, as it enables unbiased and hypothesis-free testing of plant samples. The development of NGS protocols capable of detecting multiple known and emergent viruses present in infected material is proving to be a major advance for crops, nuclear stocks or imported plants and germplasm, in which disease symptoms are absent, unspecific or only triggered by multiple viruses. Researchers want to answer the question “how many different viruses are present in this crop plant?” without knowing what they are looking for: RNA-sequencing (RNA-seq) of plant material allows this question to be addressed. As well as needing efficient nucleic acid extraction and enrichment protocols, virus detection using RNA-seq requires fast and robust bioinformatics methods to enable host sequence removal and virus classification. In this review recent studies that use RNA-seq for virus detection in a variety of crop plants are discussed with specific emphasis on the computational methods implemented. The main features of a number of specific bioinformatics workflows developed for virus detection from NGS data are also outlined and possible reasons why these have not yet been widely adopted are discussed. The review concludes by discussing the future directions of this field, including the use of bioinformatics tools for virus detection deployed in analytical environments using cloud computing.

Pathogenicity and Virulence Factors of Fusarium graminearum Including Factors Discovered Using Next Generation Sequencing Technologies and Proteomics

“…On the contrary, Ion Torrent utilizes the pH variation sequencing method [18,24], whereas the modern platforms, such as Illumina MiSeq and Gene Reader System, utilize the fluorescence emission sequencing method [24,25]. NGS technologies have impressively accelerated research and are becoming employed routinely to seek solutions in different areas of research, as well as provide insights into pathogenicity and virulence of various plant pathogens [26][27][28][29][30][31][32][33][34]. Although NGS is more affordable than first-generation sequencing (considering time and money), it is still not within the reach of many laboratories in undeveloped countries [16].…”

Recent Advances on the Multiplex Molecular Detection of Plant Viruses and Viroids

“…Next-generation sequencing, known also as massively parallel sequencing or deep sequencing, is a powerful technology that allows the generation of massive amounts of sequence data. There are various approaches or NGS platforms, each with different characteristics and with the potential in some cases to generate as many as three billion reads per run with read lengths that vary from approximately 35 to 800 nucleotides depending on the platform ( Barzon et al, 2011 ; Buermans and den Dunnen, 2014 ; Wu et al, 2015 ; Jones et al, 2017 ; Rott et al, 2017 ). The technology has been proposed as a valuable tool for diagnostic virology ( Adams et al, 2009 ; Barzon et al, 2011 ).…”

“…The broad-spectrum and unbiased nature of the technology makes it a valuable tool for plant-based metagenomics, allowing the simultaneous screening and detection of populations of graft transmissible agents that include viruses (RNA and DNA), viroids, and phytoplasma in a sample ( Adams et al, 2009 ; Kreuze et al, 2009 ). Jones et al (2017) indicated that the multiplexing potential of NGS (RNA-seq) might allow a researcher to answer the question of how many different viruses are present in a crop plant. NGS even has the power to detect plant viruses that were not detected using current and standard tools that were based on biological, serological, and molecular tests ( Villamor et al, 2016 ).…”

“…NGS even has the power to detect plant viruses that were not detected using current and standard tools that were based on biological, serological, and molecular tests ( Villamor et al, 2016 ). See Jones et al (2017) for an excellent review describing the use of RNA-seq for the detection of multiple viruses in each of various host plants.…”

Sweet potato viromes in eight different geographical regions in Korea and two different cultivars

“…With the rapid development of next-generation sequencing (NGS) technologies, NGS-based approaches enable us to facilitate the identification of viruses, virus diagnostics, and the assembly of virus genomes [17][18][19][20] . For instance, the NGS technique is widely applied in the study of viruses infecting sweet potato by RNA-Sequencing (RNA-Seq) 17,21 and small RNA-Seq 22,23 .…”