Immunocapture of virions with virus-specific antibodies prior to high-throughput sequencing effectively enriches for virus-specific sequences

Knierim, Dennis; Menzel, W.; Winter, Stephan

doi:10.1371/journal.pone.0216713

Cited by 6 publications

(3 citation statements)

References 39 publications

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“…Different templates used for library preparation and different strategies for the enriching of viral sequences can be applied prior to the HTS analysis; e.g., virus-derived small interfering RNAs, double-stranded RNAs, ribosomal RNA-depleted total RNAs and virion-associated nucleic acids [19][20][21]. Our results confirmed the suitability of the total RNA templates, in which the virus fraction was enriched by ribosomal RNA depletion prior to library preparation for HTS.…”

Section: Discussionsupporting

confidence: 73%

High-Throughput Sequencing Reveals Bell Pepper Endornavirus Infection in Pepper (Capsicum annum) in Slovakia and Enables Its Further Molecular Characterization

Tomašechová

Hančinský

Predajňa

et al. 2019

Plants

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Ribosomal RNA-depleted total RNAs from a sweet pepper plant (Capsicum annuum, labelled as N65) grown in western Slovakia and showing severe virus-like symptoms (chlorosis, mottling and deformation of leaf lamina) were subjected to high-throughput sequencing (HTS) on an Illumina MiSeq platform. The de novo assembly of ca. 5.5 million reads, followed by mapping to the reference sequences, revealed the coinfection of pepper by several viruses; i.e., cucumber mosaic virus (CMV), watermelon mosaic virus (WMV), pepper cryptic virus 2 (PCV2) and bell pepper endornavirus (BPEV). A complete polyprotein-coding genomic sequence (14.6 kb) of BPEV isolate N65 was determined. A comparison of BPEV-N65 sequences with BPEV genomes available in GenBank showed 86.1% to 98.6% identity at the nucleotide level. The close phylogenetic relationship with isolates from India and China resulted in their distinct grouping compared to the other BPEV isolates. Further analysis has revealed the presence of BPEV in sweet or chili peppers obtained from various sources and locations in Slovakia (plants grown in gardens, greenhouse or retail shop). Additionally, the partial sequencing of two genomic portions from 15 BPEV isolates revealed that the Slovak isolates segregated into two molecular clusters, indicating a genetically distinct population (mean inter-group nucleotide divergence reaching 12.7% and 14.5%, respectively, based on the genomic region targeted). Due to the mix infections of BPEV-positive peppers by potato virus Y (PVY) and/or CMV, the potential role of individual viruses in the observed symptomatology could not be determined. This is the first evidence and characterization of BPEV from the central European region.

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Section: Discussionsupporting

confidence: 73%

High-Throughput Sequencing Reveals Bell Pepper Endornavirus Infection in Pepper (Capsicum annum) in Slovakia and Enables Its Further Molecular Characterization

Tomašechová

Hančinský

Predajňa

et al. 2019

Plants

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“…-Dataset 1: The challenge addressed is the detection of several virus strains showing different concentrations, some being very low. In this case, one or more strains can be missed, especially if the sample has not been enriched in viral sequences (Barzon et al, 2013;Knierim et al, 2019). The real dataset is composed of mixed infections of citrus tristeza virus (CTV), citrus vein enation virus (CVEV), citrus exocortis viroid (CEVd), citrus viroid III (CVd-III) and hop stunt viroid (HSVd) on citrus.…”

Section: Availability and Description Of The Datasetsmentioning

confidence: 99%

Semi-artificial datasets as a resource for validation of bioinformatics pipelines for plant virus detection

Tamisier¹,

Haegeman²,

Foucart³

et al. 2021

Peer Community Journal

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The widespread use of High-Throughput Sequencing (HTS) for detection of plant viruses and sequencing of plant virus genomes has led to the generation of large amounts of data and of bioinformatics challenges to process them. Many bioinformatics pipelines for virus detection are available, making the choice of a suitable one difficult. A robust benchmarking is needed for the unbiased comparison of the pipelines, but there is currently a lack of reference datasets that could be used for this purpose. We present 7 semi-artificial datasets composed of real RNA-seq datasets from virus-infected plants spiked with artificial virus reads. Each dataset addresses challenges that could prevent virus detection. We also present 3 real datasets showing a challenging virus composition as well as 8 completely artificial datasets to test haplotype reconstruction software. With these datasets that address several diagnostic challenges, we hope to encourage virologists, diagnosticians and bioinformaticians to evaluate and benchmark their pipeline(s).

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“…The main limitation of this approach is the low concentration of extracted dsRNA which can be challenging for some library preparations. It is unclear whether PNYDV sequences (a DNA virus) were recovered as RNA/DNA hybrid molecule and amplified by HTS or if contaminating DNA was carried over in the dsRNA preparations (Knierim et al, 2019).…”

Section: Virus Characterisationmentioning

confidence: 99%

Plant virus identification and virus-vector-host interactions

Gaafar¹

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BackgroundNucleorhabdoviruses possess bacilliform particles which contain a single-stranded negative-sense RNA genome. They replicate and mature in the nucleus of infected cells. Together with viruses of three other genera of the family Rhabdoviridae, they are known to infect plants and can be transmitted by arthropod vectors, during vegetative propagation, or by mechanical means. In 2010, an alfalfa (Medicago sativa) plant showing virus-like symptoms was collected from Stadl-Paura, Austria and sent to Julius Kühn Institute for analysis. MethodsElectron microscopy (EM) of leaf extracts from infected plants revealed the presence of rhabdovirus-like particles and was further used for ultrastructural analyses of infected plant tissue. Partially-purified preparations of rhabdovirus nucleocapsids were used for raising an antiserum. To determine the virus genome sequence, high throughput sequencing (HTS) was performed. RT-PCR primers were designed to confirm virus infection and to be used as a diagnostic tool. ResultsEM revealed bacilliform virions resembling those of plant-infecting rhabdoviruses. HTS of ribosomal RNA-depleted total RNA extracts revealed a consensus sequence consisting of 13,875 nucleotides (nt) and containing seven open reading frames (ORFs). Homology and phylogenetic analyses suggest that this virus isolate represents a new species of the genus Nucleorhabdovirus (family Rhabdoviridae). Since the virus originated from an alfalfa plant in Austria, the name alfalfa-associated nucleorhabdovirus (AaNV) is proposed. Viroplasms (Vp) and budding virions were observed in the nuclei of infected cells by EM, thus confirming its taxonomic assignment based on sequence data. ConclusionsIn this study, we identified and characterised a new nucleorhabdovirus from alfalfa. It shared only 39.8% nucleotide sequence identity with its closest known relative, black currant-associated rhabdovirus 1. The virus contains an additional open reading frame (accessory gene) with unknown function, located between the matrix protein and the glycoprotein genes. Serological and molecular diagnostic assays were designed for future screening of field samples. Further studies are needed to identify other natural hosts and potential vectors.

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Immunocapture of virions with virus-specific antibodies prior to high-throughput sequencing effectively enriches for virus-specific sequences

Cited by 6 publications

References 39 publications

High-Throughput Sequencing Reveals Bell Pepper Endornavirus Infection in Pepper (Capsicum annum) in Slovakia and Enables Its Further Molecular Characterization

High-Throughput Sequencing Reveals Bell Pepper Endornavirus Infection in Pepper (Capsicum annum) in Slovakia and Enables Its Further Molecular Characterization

Semi-artificial datasets as a resource for validation of bioinformatics pipelines for plant virus detection

Plant virus identification and virus-vector-host interactions

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