Next generation sequencing (NGS) technologies are becoming routinely employed in different fields of virus research. Different sequencing platforms and sample preparation approaches, in the laboratories worldwide, contributed to a revolution in detection and discovery of plant viruses and viroids. In this work, we are presenting the comparison of two RNA sequence inputs (small RNAs versus ribosomal RNA depleted total RNA) for the detection of plant viruses by Illumina sequencing. This comparison includes several viruses, which differ in genome organization and viroids from both known families. The results demonstrate the ability for detection and identification of a wide array of known plant viruses/viroids in the tested samples by both approaches. In general, yield of viral sequences was dependent on viral genome organization and the amount of viral reads in the data. A putative novel Cytorhabdovirus, discovered in this study, was only detected by analysing the data generated from ribosomal RNA depleted total RNA and not from the small RNA dataset, due to the low number of short reads in the latter. On the other hand, for the viruses/viroids under study, the results showed higher yields of viral sequences in small RNA pool for viroids and viruses with no RNA replicative intermediates (single stranded DNA viruses).

Recent developments in high-throughput sequencing (HTS), also called next-generation sequencing (NGS), technologies and bioinformatics have drastically changed research on viral pathogens and spurred growing interest in the field of virus diagnostics. However, the reliability of HTS-based virus detection protocols must be evaluated before adopting them for diagnostics. Many different bioinformatics algorithms aimed at detecting viruses in HTS data have been reported but little attention has been paid thus far to their sensitivity and reliability for diagnostic purposes. Therefore, we compared the ability of 21 plant virology laboratories, each employing a different bioinformatics pipeline, to detect 12 plant viruses through a double-blind large-scale performance test using 10 datasets of 21- to 24-nucleotide small RNA (sRNA) sequences from three different infected plants. The sensitivity of virus detection ranged between 35 and 100% among participants, with a marked negative effect when sequence depth decreased. The false-positive detection rate was very low and mainly related to the identification of host genome-integrated viral sequences or misinterpretation of the results. Reproducibility was high (91.6%). This work revealed the key influence of bioinformatics strategies for the sensitive detection of viruses in HTS sRNA datasets and, more specifically (i) the difficulty in detecting viral agents when they are novel or their sRNA abundance is low, (ii) the influence of key parameters at both assembly and annotation steps, (iii) the importance of completeness of reference sequence databases, and (iv) the significant level of scientific expertise needed when interpreting pipeline results. Overall, this work underlines key parameters and proposes recommendations for reliable sRNA-based detection of known and unknown viruses.

Background: In agroecosystems, viruses are well known to influence crop health and some cause phytosanitary and economic problems, but their diversity in non-crop plants and role outside the disease perspective is less known. Extensive virome explorations that include both crop and diverse weed plants are therefore needed to better understand roles of viruses in agroecosystems. Such unbiased exploration is available through viromics, which could generate biological and ecological insights from immense high-throughput sequencing (HTS) data. Results: Here, we implemented HTS-based viromics to explore viral diversity in tomatoes and weeds in farming areas at a nation-wide scale. We detected 125 viruses, including 79 novel species, wherein 65 were found exclusively in weeds. This spanned 21 higher-level plant virus taxa dominated by Potyviridae, Rhabdoviridae, and Tombusviridae, and four non-plant virus families. We detected viruses of non-plant hosts and viroid-like sequences and demonstrated infectivity of a novel tobamovirus in plants of Solanaceae family. Diversities of predominant tomato viruses were variable, in some cases, comparable to that of global isolates of the same species. We phylogenetically classified novel viruses and showed links between a subgroup of phylogenetically related rhabdoviruses to their taxonomically related host plants. Ten classified viruses detected in tomatoes were also detected in weeds, which might indicate possible role of weeds as their reservoirs and that these viruses could be exchanged between the two compartments. Conclusions: We showed that even in relatively well studied agroecosystems, such as tomato farms, a large part of very diverse plant viromes can still be unknown and is mostly present in understudied non-crop plants. The overlapping presence of viruses in tomatoes and weeds implicate possible presence of virus reservoir and possible exchange between the weed and crop compartments, which may influence weed management decisions. The observed variability and widespread presence of predominant tomato viruses and the infectivity of a novel tobamovirus in solanaceous plants, provided foundation for further investigation of virus disease dynamics and their effect on tomato health. The extensive insights we generated from such in-depth agroecosystem virome exploration will be valuable in anticipating possible emergences of plant virus diseases and would serve as baseline for further post-discovery characterization studies.

Viruses cause a big fraction of economically important diseases in major crops, including tomato. In the past decade (2011–2020), many emerging or re-emerging tomato-infecting viruses were reported worldwide. In this period, 45 novel viral species were identified in tomato, 14 of which were discovered using high-throughput sequencing (HTS). In this review, we first discuss the role of HTS in these discoveries and its general impact on tomato virome research. We observed that the rate of tomato virus discovery is accelerating in the past few years due to the use of HTS. However, the extent of the post-discovery characterization of viruses is lagging behind and is greater for economically devastating viruses, such as the recently emerged tomato brown rugose fruit virus. Moreover, many known viruses still cause significant economic damages to tomato production. The review of databases and literature revealed at least 312 virus, satellite virus, or viroid species (in 22 families and 39 genera) associated with tomato, which is likely the highest number recorded for any plant. Among those, here, we summarize the current knowledge on the biology, global distribution, and epidemiology of the most important species. Increasing knowledge on tomato virome and employment of HTS to also study viromes of surrounding wild plants and environmental samples are bringing new insights into the understanding of epidemiology and ecology of tomato-infecting viruses and can, in the future, facilitate virus disease forecasting and prevention of virus disease outbreaks in tomato.

High-throughput sequencing (HTS) technologies have become indispensable tools assisting plant virus diagnostics and research thanks to their ability to detect any plant virus in a sample without prior knowledge. As HTS technologies are heavily relying on bioinformatics analysis of the huge amount of generated sequences, it is of utmost importance that researchers can rely on efficient and reliable bioinformatic tools and can understand the principles, advantages, and disadvantages of the tools used. Here, we present a critical overview of the steps involved in HTS as employed for plant virus detection and virome characterization. We start from sample preparation and nucleic acid extraction as appropriate to the chosen HTS strategy, which is followed by basic data analysis requirements, an extensive overview of the in-depth data processing options, and taxonomic classification of viral sequences detected. By presenting the bioinformatic tools and a detailed overview of the consecutive steps that can be used to implement a well-structured HTS data analysis in an easy and accessible way, this paper is targeted at both beginners and expert scientists engaging in HTS plant virome projects.

Mammalian orthoreoviruses (MRVs) are known to cause mild enteric and respiratory infections in humans. They are widespread and infect a broad spectrum of mammals. We report here the first case of an MRV detected in a child with acute gastroenteritis, which showed the highest similarity to an MRV reported recently in European bats. An examination of a stool sample from the child was negative for most common viral and bacterial pathogens. Reovirus particles were identified by electron microscopic examination of both the stool suspension and cell culture supernatant. The whole-genome sequence was obtained with the Ion Torrent next-generation sequencing platform. Prior to sequencing, the stool sample suspension and cell culture supernatant were pretreated with nucleases and/or the convective interaction medium (CIM) monolithic chromatographic method to purify and concentrate the target viral nucleic acid. Whole-genome sequence analysis revealed that the Slovenian SI-MRV01 isolate was most similar to an MRV found in a bat in Germany. High similarity was shared in all genome segments, with nucleotide and amino acid identities between 93.8 to 99.0% and 98.4 to 99.7%, respectively. It was shown that CIM monolithic chromatography alone is an efficient method for enriching the sample in viral particles before nucleic acid isolation and next-generation sequencing application.