SUMMARYA novel, unbiased approach to plant viral disease diagnosis has been developed which requires no a priori knowledge of the host or pathogen. Next-generation sequencing coupled with metagenomic analysis was used to produce large quantities of cDNA sequence in a model system of tomato infected with Pepino mosaic virus . The method was then applied to a sample of Gomphrena globosa infected with an unknown pathogen originally isolated from the flowering plant Liatris spicata . This plant was found to contain a new cucumovirus, for which we suggest the name 'Gayfeather mild mottle virus'. In both cases, the full viral genome was sequenced. This method expedites the entire process of novel virus discovery, identification, viral genome sequencing and, subsequently, the development of more routine assays for new viral pathogens.

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Environmental DNA (eDNA) analysis is a rapid, cost‐effective, non‐invasive biodiversity monitoring tool which utilises DNA left behind in the environment by organisms for species detection. The method is used as a species‐specific survey tool for rare or invasive species across a broad range of ecosystems. Recently, eDNA and “metabarcoding” have been combined to describe whole communities rather than focusing on single target species. However, whether metabarcoding is as sensitive as targeted approaches for rare species detection remains to be evaluated. The great crested newt Triturus cristatus is a flagship pond species of international conservation concern and the first UK species to be routinely monitored using eDNA. We evaluate whether eDNA metabarcoding has comparable sensitivity to targeted real‐time quantitative PCR (qPCR) for T. cristatus detection. Extracted eDNA samples (N = 532) were screened for T. cristatus by qPCR and analysed for all vertebrate species using high‐throughput sequencing technology. With qPCR and a detection threshold of 1 of 12 positive qPCR replicates, newts were detected in 50% of ponds. Detection decreased to 32% when the threshold was increased to 4 of 12 positive qPCR replicates. With metabarcoding, newts were detected in 34% of ponds without a detection threshold, and in 28% of ponds when a threshold (0.028%) was applied. Therefore, qPCR provided greater detection than metabarcoding but metabarcoding detection with no threshold was equivalent to qPCR with a stringent detection threshold. The proportion of T. cristatus sequences in each sample was positively associated with the number of positive qPCR replicates (qPCR score) suggesting eDNA metabarcoding may be indicative of eDNA concentration. eDNA metabarcoding holds enormous potential for holistic biodiversity assessment and routine freshwater monitoring. We advocate this community approach to freshwater monitoring to guide management and conservation, whereby entire communities can be initially surveyed to best inform use of funding and time for species‐specific surveys.

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 vs. 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).

The diagnosis of novel unidentified viral plant diseases can be problematic, as the conventional methods such as real‐time PCR or ELISA may be too specific to a particular species or even strain of a virus, whilst alternatives such as electron microscopy (EM) or sap inoculation of indicator species do not usually give species level diagnosis. Next‐generation sequencing (NGS) offers an alternative solution where sequence is generated in a non‐specific fashion and identification is based on similarity searching against GenBank. The conventional and NGS techniques were applied to a damaging and apparently new disease of maize, which was first identified in Kenya in 2011. ELISA and TEM provided negative results, whilst inoculation of other cereal species identified the presence of an unidentified sap transmissible virus. RNA was purified from material showing symptoms and sequenced using a Roche 454 GS‐FLX+. Database searching of the resulting sequence identified the presence of Maize chlorotic mottle virus and Sugarcane mosaic virus, a combination previously reported to cause maize lethal necrosis disease. Over 90% of both viral genome sequences were obtained, allowing strain characterization and the development of specific real‐time PCR assays which were used to confirm the presence of the virus in material with symptoms from six different fields in two different regions of Kenya. The availability of these assays should aid the assessment of the disease and may be used for routine diagnosis. The work shows that next‐generation sequencing is a valuable investigational technique for rapidly identifying potential disease‐causing agents such as viruses.