Identification of Plant Viruses Infecting Pear Using RNA Sequencing.
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ABSTRACT:
SUBMITTER: Kim NY
PROVIDER: S-EPMC8200581 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundPlums are a kind of stone fruit, a category that includes peaches, cherries, apricots, and almonds. In Korea, Japanese plum trees are usually cultivated as they best suit the climate. To date, there have been few studies in Korea on viruses infecting plum trees compared to those infecting peach trees.MethodsTo identify viruses and viroids infecting plum trees, we collected leaf samples from six different plum cultivars and subjected them to RNA-sequencing (RNA-seq). Six different plum transcriptomes were de novo assembled using the Trinity assembler followed by BLAST searching against a viral reference database.ResultsWe identified hop stunt viroid (HSVd) and six viruses, including apple chlorotic leaf spot virus (ACLSV), little cherry virus-1 (LChV-1), peach virus D (PeVD), peach leaf pitting-associated virus (PLPaV), plum bark necrosis stem pitting-associated virus (PBNSPaV), and prunus necrotic ringspot virus (PNRSV), from six plum cultivars by RNA-seq. RT-PCR confirmed the infection of HSVd and three viruses-ACLSV, PBNSPaV, and PNRSV-in plum trees. However, RT-PCR demonstrated that plum trees in this study were not infected by LChV-1, PeVD, or PLPaV. It is likely that the three viruses LChV-1, PeVD, and PLPaV as identified by RNA-seq were contaminants from other peach libraries caused by index misassignment, which suggests that careful confirmation by other methods should be carried out in next-generation sequencing (NGS)-based virus identification. Taken together, we identified a viroid and three viruses infecting plum trees in Korea.
| S-EPMC7395596 | biostudies-literature
Project description:BACKGROUND:The invasion of plant by viruses cause major damage to plants and reduces crop yield and integrity. Devastating plant virus infection has been experienced at different times all over the world, which are attributed to different events of mutation, re-assortment and recombination occurring in the viruses. Strategies for proper virus management has been mostly limited to eradicating the vectors that spreads the plant viruses. However, development of prompt and effective diagnostic methods are required to monitor emerging and re-emerging diseases that may be symptomatic or asymptomatic in the plant as well as the genetic variation and evolution in the plant viruses. A survey of plant viruses infecting field-grown Tobacco crop was conducted in Anhui Province of China by the deep sequencing of sRNAs. METHODS:Survey of plant viruses infecting Tobacco was carried based on 104 samples collected across the province. Nine different sRNA libraries was prepared and custom-made bioinformatics pipeline coupled with molecular techniques was developed to sequence, assemble and analyze the siRNAs for plant virus discovery. We also carried out phylogenetic and recombination analysis of the identified viruses. RESULTS:Twenty two isolates from eight different virus species including Cucumber mosaic virus, Potato virus Y, Tobacco mosaic virus, Tobacco vein banding Mosaic virus, Pepper mottle virus, Brassica yellow virus, Chilli venial mottle virus, Broad bean wilt virus 2 were identified in tobacco across the survey area. The near-complete genome sequence of the 22 new isolates were determined and analyzed. The isolates were grouped together with known strains in the phylogenetic tree. Molecular variation in the isolates indicated the conserved coding regions have majorly a nucleotide sequence identity of 80-94 % with previously identified isolates. Various events of recombination were discovered among some of the isolates indicating that two or more viruses or different isolates of one virus infect the same host cell. CONCLUSION:This study describes the discovery of a consortium of plant viruses infecting Tobacco that are broadly distributed in Anhui province of China. It also demonstrates the effectiveness of NGS in identifying plant viruses without a prior knowledge of the virus and the genetic diversity that enhanced mixed infection.
| S-EPMC5096307 | biostudies-literature
Project description:Viruses have caused much mortality and morbidity to humans and pose a serious threat to global public health. The virome with the potential of human infection is still far from complete. Novel viruses have been discovered at an unprecedented pace as the rapid development of viral metagenomics. However, there is still a lack of methodology for rapidly identifying novel viruses with the potential of human infection. This study built several machine learning models to discriminate human-infecting viruses from other viruses based on the frequency of k-mers in the viral genomic sequences. The k-nearest neighbor (KNN) model can predict the human-infecting viruses with an accuracy of over 90%. The performance of this KNN model built on the short contigs (?1 kb) is comparable to those built on the viral genomes. We used a reported human blood virome to further validate this KNN model with an accuracy of over 80% based on very short raw reads (150 bp). Our work demonstrates a conceptual and generic protocol for the discovery of novel human-infecting viruses in viral metagenomics studies.
| S-EPMC7168554 | biostudies-literature
Project description:Apple stem grooving virus (ASGV; genus Capillovirus) is an economically important virus. It has an approx. 6.5 kb, monopartite, linear, positive-sense, single-stranded RNA genome. The present study includes identification of 24 isolates-13 isolates from apple (Pyrus malus L.) and 11 isolates from pear (Pyrus communis L.)-from different agricultural fields in South Korea. The coat protein (CP) gene of the corresponding 23 isolates were amplified, sequenced, and analyzed. The CP sequences showed phylogenetic separation based on their host species, and not on the geography, indicating host adaptation. Further analysis showed that the ASGV isolated in this study followed host adaptation influenced and preferred by the host codon-usage.
| S-EPMC8223792 | biostudies-literature
Project description:The cosmopolitan fungus Rhizoctonia solani has a wide host range and is the causal agent of numerous crop diseases, leading to significant economic losses. To date, no cultivars showing complete resistance to R. solani have been identified and it is imperative to develop a strategy to control the spread of the disease. Fungal viruses, or mycoviruses, are widespread in all major groups of fungi and next-generation sequencing (NGS) is currently the most efficient approach for their identification. An increasing number of novel mycoviruses are being reported, including double-stranded (ds) RNA, circular single-stranded (ss) DNA, negative sense (-)ssRNA, and positive sense (+)ssRNA viruses. The majority of mycovirus infections are cryptic with no obvious symptoms on the hosts; however, some mycoviruses may alter fungal host pathogenicity resulting in hypervirulence or hypovirulence and are therefore potential biological control agents that could be used to combat fungal diseases. R. solani harbors a range of dsRNA and ssRNA viruses, either belonging to established families, such as Endornaviridae, Tymoviridae, Partitiviridae, and Narnaviridae, or unclassified, and some of them have been associated with hypervirulence or hypovirulence. Here we discuss in depth the molecular features of known viruses infecting R. solani and their potential as biological control agents.
| S-EPMC6950361 | biostudies-literature
Project description:We used high-throughput sequencing to identify viruses on tomato samples showing virus-like symptoms. Samples were collected from crops in the Iberian Peninsula. Either total RNA or double-stranded RNA (dsRNA) were used as starting material to build the cDNA libraries. In total, seven virus species were identified, with pepino mosaic virus being the most abundant one. The dsRNA input provided better coverage and read depth but missed one virus species compared with the total RNA input. By performing in silico analyses, we determined a minimum sequencing depth per sample of 0.2 and 1.5 million reads for dsRNA and rRNA-depleted total RNA inputs, respectively, to detect even the less abundant viruses. Primers and TaqMan probes targeting conserved regions in the viral genomes were designed and/or used for virus detection; all viruses were detected by qRT-PCR/RT-PCR in individual samples, with all except one sample showing mixed infections. Three virus species (Olive latent virus 1, Lettuce ring necrosis virus and Tomato fruit blotch virus) are herein reported for the first time in tomato crops in Spain.
| S-EPMC8150983 | biostudies-literature
Project description:Deep sequencing has generated 52 contigs derived from five viruses; Apple chlorotic leaf spot virus (ACLSV), Apple stem grooving virus (ASGV), Apple stem pitting virus (ASPV), Apple green crinkle associated virus (AGCaV), and Apricot latent virus (ApLV) were identified from eight apple samples showing small leaves and/or growth retardation. Nucleotide (nt) sequence identity of the assembled contigs was from 68% to 99% compared to the reference sequences of the five respective viral genomes. Sequences of ASPV and ASGV were the most abundantly represented by the 52 contigs assembled. The presence of the five viruses in the samples was confirmed by RT-PCR using specific primers based on the sequences of each assembled contig. All five viruses were detected in three of the samples, whereas all samples had mixed infections with at least two viruses. The most frequently detected virus was ASPV, followed by ASGV, ApLV, ACLSV, and AGCaV which were withal found in mixed infections in the tested samples. AGCaV was identified in assembled contigs ID 1012480 and 93549, which showed 82% and 78% nt sequence identity with ORF1 of AGCaV isolate Aurora-1. ApLV was identified in three assembled contigs, ID 65587, 1802365, and 116777, which showed 77%, 78%, and 76% nt sequence identity respectively with ORF1 of ApLV isolate LA2. Deep sequencing assay was shown to be a valuable and powerful tool for detection and identification of known and unknown virome in infected apple trees, here identifying ApLV and AGCaV in commercial orchards in Korea for the first time.
| S-EPMC5051563 | biostudies-literature
Project description:BACKGROUND: Animal faeces comprise a community of many different microorganisms including bacteria and viruses. Only scarce information is available about the diversity of viruses present in the faeces of pigs. Here we describe a protocol, which was optimized for the purification of the total fraction of viral particles from pig faeces. The genomes of the purified DNA and RNA viruses were simultaneously amplified by PCR and subjected to deep sequencing followed by bioinformatic analyses. The efficiency of the method was monitored using a process control consisting of three bacteriophages (T4, M13 and MS2) with different morphology and genome types. Defined amounts of the bacteriophages were added to the sample and their abundance was assessed by quantitative PCR during the preparation procedure. RESULTS: The procedure was applied to a pooled faecal sample of five pigs. From this sample, 69,613 sequence reads were generated. All of the added bacteriophages were identified by sequence analysis of the reads. In total, 7.7% of the reads showed significant sequence identities with published viral sequences. They mainly originated from bacteriophages (73.9%) and mammalian viruses (23.9%); 0.8% of the sequences showed identities to plant viruses. The most abundant detected porcine viruses were kobuvirus, rotavirus C, astrovirus, enterovirus B, sapovirus and picobirnavirus. In addition, sequences with identities to the chimpanzee stool-associated circular ssDNA virus were identified. Whole genome analysis indicates that this virus, tentatively designated as pig stool-associated circular ssDNA virus (PigSCV), represents a novel pig virus. CONCLUSION: The established protocol enables the simultaneous detection of DNA and RNA viruses in pig faeces including the identification of so far unknown viruses. It may be applied in studies investigating aetiology, epidemiology and ecology of diseases. The implemented process control serves as quality control, ensures comparability of the method and may be used for further method optimization.
| S-EPMC3326065 | biostudies-literature
Project description:Metagenomic sequencing has revolutionised our knowledge of virus diversity, with new virus sequences being reported faster than ever before. However, virus discovery from metagenomic sequencing usually depends on detectable homology: without a sufficiently close relative, so-called 'dark' virus sequences remain unrecognisable. An alternative approach is to use virus-identification methods that do not depend on detecting homology, such as virus recognition by host antiviral immunity. For example, virus-derived small RNAs have previously been used to propose 'dark' virus sequences associated with the Drosophilidae (Diptera). Here, we combine published Drosophila data with a comprehensive search of transcriptomic sequences and selected meta-transcriptomic datasets to identify a completely new lineage of segmented positive-sense single-stranded RNA viruses that we provisionally refer to as the Quenyaviruses. Each of the five segments contains a single open reading frame, with most encoding proteins showing no detectable similarity to characterised viruses, and one sharing a small number of residues with the RNA-dependent RNA polymerases of single- and double-stranded RNA viruses. Using these sequences, we identify close relatives in approximately 20 arthropods, including insects, crustaceans, spiders, and a myriapod. Using a more conserved sequence from the putative polymerase, we further identify relatives in meta-transcriptomic datasets from gut, gill, and lung tissues of vertebrates, reflecting infections of vertebrates or of their associated parasites. Our data illustrate the utility of small RNAs to detect viruses with limited sequence conservation, and provide robust evidence for a new deeply divergent and phylogenetically distinct RNA virus lineage.
| S-EPMC6966834 | biostudies-literature
Project description:Small RNA sequencing (sRNA-seq) can be used to detect viruses in infected hosts without the necessity to have any prior knowledge or specialized sample preparation. The sRNA-seq method was initially used for viral detection and identification in plants and then in invertebrates and fungi. However, it is still controversial to use sRNA-seq in the detection of mammalian or human viruses. In this study, we used 931 sRNA-seq runs of data from the NCBI SRA database to detect and identify viruses in human cells or tissues, particularly from some clinical samples. Six viruses including HPV-18, HBV, HCV, HIV-1, SMRV, and EBV were detected from 36 runs of data. Four viruses were consistent with the annotations from the previous studies. HIV-1 was found in clinical samples without the HIV-positive reports, and SMRV was found in Diffuse Large B-Cell Lymphoma cells for the first time. In conclusion, these results suggest the sRNA-seq can be used to detect viruses in mammals and humans.
| S-EPMC4811048 | biostudies-literature