A fast, accurate, and full indexing of viruses and viroids in a sample for the inspection and quarantine services and disease management is desirable but was unrealistic until recently. This article reviews the rapid and exciting recent progress in the use of next-generation sequencing (NGS) technologies for the identification of viruses and viroids in plants. A total of four viroids/viroid-like RNAs and 49 new plant RNA and DNA viruses from 18 known or unassigned virus families have been identified from plants since 2009. A comparison of enrichment strategies reveals that full indexing of RNA and DNA viruses as well as viroids in a plant sample at single-nucleotide resolution is made possible by one NGS run of total small RNAs, followed by data mining with homology-dependent and homology-independent computational algorithms. Major challenges in the application of NGS technologies to pathogen discovery are discussed.

Replicating circular RNAs are independent plant pathogens known as viroids, or act to modulate the pathogenesis of plant and animal viruses as their satellite RNAs. The rate of discovery of these subviral pathogens was low over the past 40 years because the classical approaches are technical demanding and time-consuming. We previously described an approach for homology-independent discovery of replicating circular RNAs by analysing the total small RNA populations from samples of diseased tissues with a computational program known as progressive filtering of overlapping small RNAs (PFOR). However, PFOR written in PERL language is extremely slow and is unable to discover those subviral pathogens that do not trigger in vivo accumulation of extensively overlapping small RNAs. Moreover, PFOR is yet to identify a new viroid capable of initiating independent infection. Here we report the development of PFOR2 that adopted parallel programming in the C++ language and was 3 to 8 times faster than PFOR. A new computational program was further developed and incorporated into PFOR2 to allow the identification of circular RNAs by deep sequencing of long RNAs instead of small RNAs. PFOR2 analysis of the small RNA libraries from grapevine and apple plants led to the discovery of Grapevine latent viroid (GLVd) and Apple hammerhead viroid-like RNA (AHVd-like RNA), respectively. GLVd was proposed as a new species in the genus Apscaviroid, because it contained the typical structural elements found in this group of viroids and initiated independent infection in grapevine seedlings. AHVd-like RNA encoded a biologically active hammerhead ribozyme in both polarities, and was not specifically associated with any of the viruses found in apple plants. We propose that these computational algorithms have the potential to discover novel circular RNAs in plants, invertebrates and vertebrates regardless of whether they replicate and/or induce the in vivo accumulation of small RNAs. Viroids are a unique class of subviral pathogens found in plants, and they are difficult to identify since they are free circular non-coding RNAs and often replicate to low levels in host cells. We previously described the computational algorithm PFOR that discovers viroids by analyzing total small RNAs of the infected plants obtained by next-generation sequencing platforms. However, the algorithm written in PERL language is very slow, and viroid identification depends on the in vivo accumulation of extensively overlapping sets of small RNAs to target viroids. Here we report the development of PFOR2 that adopted parallel programming in the C++ language and was significantly faster than PFOR. We also describe a simple computational program that after incorporation into PFOR2 is capable of identifying viroids from deep sequencing of long RNAs instead of small RNAs. Moreover, we report the identification of Grapevine latent viroid (GLVd) and Apple hammerhead viroid-like RNA by the computational approach. Since our new algorithms do not depend on the analysis of viroid-derived small RNAs produced in vivo, it is possible to discover viroids in a wide range of host species including plants, invertebrates and vertebrates.

Replication of viral RNA genomes in fruit flies and mosquitoes induces the production of virus-derived small interfering RNAs (siRNAs) to specifically reduce virus accumulation by RNA interference (RNAi). However, it is unknown whether the RNA-based antiviral immunity (RVI) is sufficiently potent to terminate infection in adult insects as occurs in cell culture. We show here that, in contrast to robust infection by Flock house virus (FHV), infection with an FHV mutant (FHVΔB2) unable to express its RNAi suppressor protein B2 was rapidly terminated in adult flies. FHVΔB2 replicated to high levels and induced high mortality rates in dicer-2 and argonaute-2 mutant flies that are RNAi defective, demonstrating that successful infection of adult Drosophila requires a virus-encoded activity to suppress RVI. Drosophila RVI may depend on the RNAi activity of viral siRNAs since efficient FHVΔB2 infection occurred in argonaute-2 and r2d2 mutant flies despite massive production of viral siRNAs. However, RVI appears to be insensitive to the relative abundance of viral siRNAs since FHVΔB2 infection was terminated in flies carrying a partial loss-of-function mutation in loquacious required for viral siRNA biogenesis. Deep sequencing revealed a low-abundance population of Dicer-2-dependent viral siRNAs accompanying FHVΔB2 infection arrest in RVI-competent flies that included an approximately equal ratio of positive and negative strands. Surprisingly, viral small RNAs became strongly biased for positive strands at later stages of infection in RVI-compromised flies due to genetic or viral suppression of RNAi. We propose that degradation of the asymmetrically produced viral positive-strand RNAs associated with abundant virus accumulation contributes to the positive-strand bias of viral small RNAs.

Background:Sogatella furcifera is an important phloem sap-sucking and plant virus-transmitting migratory insect of rice. Because of its high reproductive potential, dispersal capability and transmission of plant viral diseases, S. furcifera causes considerable damage to rice grain production and has great economical and agricultural impacts. Comprehensive studies into ecological aspects and virus–host interactions of S. furcifera have been limited because of the lack of a well-assembled genome sequence. Findings: A total of 241.3 Gb of raw reads from the whole genome of S. furcifera were generated by Illumina sequencing using different combinations of mate-pair and paired-end libraries from 17 insert libraries ranging between 180 bp and 40 kbp. The final genome assembly (0.72 Gb), with average N50 contig size of 70.7 kb and scaffold N50 of 1.18 Mb, covers 98.6 % of the estimated genome size of S. furcifera. Genome annotation, assisted by eight different developmental stages (embryos, 1^st-5^th instar nymphs, 5-day-old adults and 10-day-old adults), generated 21 254 protein-coding genes, which captured 99.59 % (247/248) of core CEGMA genes and 91.7 % (2453/2675) of BUSCO genes. Conclusions: We report the first assembled and annotated whole genome sequence and transcriptome of S. furcifera. The assembled draft genome of S. furcifera will be a valuable resource for ecological and virus–host interaction studies of this pest.