PCR bias associated with conserved primer binding sites, used to determine genotype diversity within Citrus tristeza virus populations

Genetic Variation of Turnip Yellows Virus in Arable and Vegetable Brassica Crops, Perennial Wild Brassicas, and Aphid Vectors Collected from the Plants

Turnip yellows virus (TuYV; Polerovirus, Solemoviridae) infects and causes yield losses in a range of economically important crop species, particularly the Brassicaceae. It is persistently transmitted by several aphid species and is difficult to control. Although the incidence and genetic diversity of TuYV has been extensively investigated in recent years, little is known about how the diversity within host plants relates to that in its vectors. Arable oilseed rape (Brassica napus) and vegetable brassica plants (Brassica oleracea), wild cabbage (B. oleracea), and aphids present on these plants were sampled in the field in three regions of the United Kingdom. High levels of TuYV (82 to 97%) were detected in plants in all three regions following enzyme-linked immunosorbent assays. TuYV was detected by reverse transcription polymerase chain reaction in Brevicoryne brassicae aphids collected from plants, and TuYV sequences were obtained. Two TuYV open reading frames, ORF0 and ORF3, were partially sequenced from 15 plants, and from one aphid collected from each plant. Comparative analyses between TuYV sequences from host plants and B. brassicae collected from respective plants revealed differences between some ORF0 sequences, which possibly indicated that at least two of the aphids might not have been carrying the same TuYV isolates as those present in their host plants. Maximum likelihood phylogenetic analyses including published, the new TuYV sequences described above, 101 previously unpublished sequences of TuYV from oilseed rape in the United Kingdom, and 13 also previously unpublished sequences of TuYV from oilseed rape in Europe and China revealed three distinct major clades for ORF0 and one for ORF3, with some distinct subclades. Some clustering was related to geographic origin. Explanations for TuYV sequence differences between plants and the aphids present on respective plants and implications for the epidemiology and control of TuYV are discussed.

Molecular and biological characterization of a novel citrus tristeza virus isolate that causes severe symptoms in Citrus junos cv. Ziyangxiangcheng

The complete genomic sequence of a novel citrus tristeza virus (CTV) isolate, CT91-A1, from Orah tangor grafted on Citrus junos cv. Ziyangxiangcheng rootstock in China was determined by transcriptome sequencing. Sequence alignments showed that isolate CT91-A1 shared 83.3 to 95.5% nucleotide sequence identity with extant CTV genotypes at the whole-genome level, with the highest similarity to the S1 genotype. Phylogenetic analysis revealed that CT91-A1 clustered in a unique subclade with the S1 genotype. Isolate CT91-A1 induced severe stem pitting in Mexican lime and C. junos cv. Ziyangxiangcheng and moderate stem pitting in Guanximiyou pummelo and Duncan grapefruit. It was successfully transmitted by Aphis citricidus, and it can potentially cause significant damage to the citrus industry in China.

Analysis of Genotype Composition of Citrus tristeza virus Populations Using Illumina Miseq Technology

Recent research describing the strain-specific mechanisms underlying experimental CTV superinfection exclusion has far-reaching implications for the manner in which cross-protecting sources should be selected for. The strain composition of both cross-protecting sources and field populations needs to be sufficiently characterized to improve control of severe stem-pitting and decline isolates. Many of the biological, serological, and molecular techniques used in previous studies yield very limited information about the strain composition of populations and the relative titer of their components. In this chapter we describe a protocol for the characterization of CTV populations, based on the use of the next-generation sequencing Illumina MiSeq platform of p33 gene amplicons.

Application of next generation sequencing toward sensitive detection of enteric viruses isolated from celery samples as an example of produce

Next generation sequencing (NGS) holds promise as a single application for both detection and sequence identification of foodborne viruses; however, technical challenges remain due to anticipated low quantities of virus in contaminated food. In this study, with a focus on data analysis using several bioinformatics tools, we applied NGS toward amplification-independent detection and identification of norovirus at low copy (<10³ copies) or within multiple strains from produce. Celery samples were inoculated with human norovirus (stool suspension) either as a single norovirus strain, a mixture of strains (GII.4 and GII.6), or a mixture of different species (hepatitis A virus and norovirus). Viral RNA isolation and recovery was confirmed by RT-qPCR, and optimized for library generation and sequencing without amplification using the Illumina MiSeq platform. Extracts containing either a single virus or a two-virus mixture were analyzed using two different analytic approaches to achieve virus detection and identification. First an overall assessment of viral genome coverage for samples varying in copy numbers (1.1×10³ to 1.7×10⁷) and genomic content (single or multiple strains in various ratios) was completed by reference-guided mapping. Not unexpectedly, this targeted approach to identification was successful in correctly mapping reads, thus identifying each virus contained in the inoculums even at low copy (estimated at 12 copies). For the second (metagenomic) approach, samples were treated as "unknowns" for data analyses using (i) a sequence-based alignment with a local database, (ii) an "in-house" k-mer tool, (iii) a commercially available metagenomics bioinformatic analysis platform cosmosID, and (iv) an open-source program Kraken. Of the four metagenomics tools applied in this study, only the local database alignment and in-house k-mer tool were successful in detecting norovirus (as well as HAV) at low copy (down to <10³ copies) and within a mixture of virus strains or species. The results of this investigation provide support for continued investigation into the development and integration of these analytical tools for identification and detection of foodborne viruses.