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128 results for “plant virus”
Data from: Molecular genetic analysis of virus isolates from wild and cultivated plants demonstrates that East Africa is a hotspot for the evolution and diversification of Sweet potato feathery mottle virus
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Data from: Allopolyploidy and the evolution of plant virus resistance
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Data from: RNA-Seq reveals virus–virus and virus–plant interactions in nature
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Data from: Fatal attraction of non-vector impairs fitness of manipulating plant virus
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Data from: Crop-associated virus infection in a native perennial grass: reduction in plant fitness and dynamic patterns of virus detection
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Data from: Crop-dominated landscapes have higher vector-borne plant virus prevalence
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Data from: Virus infection influences host plant interactions with non-vector herbivores and predators
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Data from: A new plant virus discovered by immunocapture of double stranded RNA; assessment of a novel approach for viral metagenomics studies
Next-generation sequencing technologies enable the rapid identification of viral infection of diseased organisms. However, despite a consistent decrease in sequencing costs, it is difficult to justify their use in large-scale surveys without a virus sequence enrichment technique. As the majority of plant viruses have an RNA genome, a common approach is to extract the double-stranded RNA (dsRNA) replicative form, to enrich the replicating virus genetic material over the host background. The traditional dsRNA extraction is time-consuming and labour-intensive. We present an alternative method to enrich dsRNA from plant extracts using anti-dsRNA monoclonal antibodies in a pull-down assay. The extracted dsRNA can be amplified by reverse transcriptase–polymerase chain reaction and sequenced by next-generation sequencing. In our study, we have selected three distinct plant hosts: Māori potato (Solanum tuberosum), rengarenga (Arthropodium cirratum) and broadleaved dock (Rumex obtusifolius) representing a cultivated crop, a New Zealand-native ornamental plant and a weed, respectively. Of the sequence data obtained, 31–74% of the reads were of viral origin, and we identified five viruses including Potato virus Y and Potato virus S in potato; Turnip mosaic virus in rengarenga (a new host record); and in the dock sample Cherry leaf roll virus and a novel virus belonging to the genus Macluravirus. We believe that this new assay represents a significant opportunity to upscale virus ecology studies from environmental, primary industry and/or medical samples.
Data from: Combined effects of mutualistic rhizobacteria counteract virus-induced suppression of indirect plant defenses in soybean
It is increasingly clear that microbial plant symbionts can influence interactions between their plant hosts and other organisms. Yet, such effects remain poorly understood, particularly under ecologically realistic conditions where plants simultaneously interact with diverse mutualists and antagonists. Here we examine how the effects of a plant virus on indirect plant defenses against its insect vector are influenced by co-occurrence of other microbial plant symbionts. Using a multi-factorial design, we manipulated colonization of soybean using three different microbes: a pathogenic plant virus (Bean pod mottle virus [BPMV]), a nodule-forming beneficial rhizobacterium (Bradyrhizobium japonicum), and a plant growth-promoting rhizobacterium (PGPR) (Delftia acidovorans). We then assessed recruitment of parasitoids (Pediobious foveolatus [Eulophidae]) and parasitism rates following feeding by the BPMV vector Epilachna varivestis (Coccinellidae). BPMV infection suppressed parasitoid recruitment, prolonged parasitoid foraging time, and reduced parasitism rates in semi-natural foraging assays. However, simultaneous colonization of BPMV-infected hosts by both rhizobacteria restored parasitoid recruitment and rates of parasitism to levels similar to uninfected controls. Co-colonization by the two rhizobacteria also enhanced parasitoid recruitment in the absence of BPMV infection. These results illustrate the potential of plant-associated microbes to influence indirect plant defenses, with implications for disease transmission and herbivory, but also highlight the potential complexity of such interactions.
Data from: Magnitude and sign epistasis among deleterious mutations in a positive-sense plant RNA virus
How epistatic interactions between mutations determine the genetic architecture of fitness is of central importance in evolution. The study of epistasis is particularly interesting for RNA viruses because of their genomic compactness, lack of genetic redundancy, and apparent low complexity. Moreover, interactions between mutations in viral genomes determine traits such as resistance to antiviral drugs, virulence and host range. In this study we generated 53 Tobacco etch potyvirus genotypes carrying pairs of single-nucleotide substitutions and measured their separated and combined deleterious fitness effects. We found that up to 38% of pairs had significant epistasis for fitness, including both positive and negative deviations from the null hypothesis of multiplicative effects. Interestingly, the sign of epistasis was correlated with viral protein–protein interactions in a model network, being predominantly positive between linked pairs of proteins and negative between unlinked ones. Furthermore, 55% of significant interactions were cases of reciprocal sign epistasis (RSE), indicating that adaptive landscapes for RNA viruses maybe highly rugged. Finally, we found that the magnitude of epistasis correlated negatively with the average effect of mutations. Overall, our results are in good agreement to those previously reported for other viruses and further consolidate the view that positive epistasis is the norm for small and compact genomes that lack genetic robustness.
Data from: Virus adaptation to quantitative plant resistance: erosion or breakdown?
Adaptation of populations to new environments is frequently costly due to trade-offs between life history traits, and consequently, parasites are expected to be locally adapted to sympatric hosts. Also, during adaptation to the host, an increase of parasite fitness could have direct consequences on its aggressiveness (i.e. the quantity of damages caused to the host by the virus). These two phenomena have been observed in the context of pathogen adaptation to host qualitative and monogenic resistances. However, the ability of pathogens to adapt to quantitative polygenic plant resistances and the consequences of these potential adaptations on other pathogen life history traits remain to be evaluated. Using Potato virus Y and two pepper genotypes (one susceptible and one with quantitative resistance), experimental evolutions showed that adaptation to a quantitative resistance was possible and resulted in resistance breakdown. This adaptation was associated to a fitness cost on the susceptible cultivar, but had no consequence neither in terms of aggressiveness, which could be explained by a high tolerance level, nor in terms of aphid transmission efficiency. It results that quantitative resistances are not necessarily durable but management strategies mixing susceptible and resistant cultivars in space and/or in time should be useful to preserve their efficiency.
Data from: An experimental test of the transmission−virulence trade-off hypothesis in a plant virus
The transmission–virulence trade-off hypothesis is one of the few adaptive explanations of virulence evolution, and assumes that there is an overall positive correlation between parasite transmission and virulence. The shape of the transmission–virulence relationship predicts whether virulence should evolve toward either a maximum or to an intermediate optimum. A positive correlation between each of these traits and within-host growth is often suggested to underlie the relationship between virulence and transmission. There are few experimental tests of this hypothesis; this study reports on the first empirical test on a plant pathogen. We infected Brassica rapa plants with nine natural isolates of Cauliflower mosaic virus and then estimated three traits: transmission, virulence, and within-host viral accumulation. As predicted by the trade-off hypothesis, we observed a positive correlation between transmission and virulence, suggestive of the existence of an intermediate optimum. We discovered the unexpected existence of two groups of within-host accumulation, differing by at least an order of magnitude. When accumulation groups were not accounted for, within-host accumulation was correlated neither to virulence nor transmission, although our results suggest that within each group these correlations exist.
Semi-artificial datasets as a resource for validation of bioinformatics pipelines for plant virus detection
<p>In the last decade, High-Throughput Sequencing (HTS) has revolutionized biology and medicine. This technology allows the sequencing of huge amount of DNA and RNA fragments at a very low price. In medicine, HTS tests for disease diagnostics are already brought into routine practice. However, the adoption in plant health diagnostics is still limited. One of the main bottlenecks is the lack of expertise and consensus on the standardization of the data analysis. The Plant Health Bioinformatic Network (PHBN) is an Euphresco project aiming to build a community network of bioinformaticians/computational biologists working in plant health. One of the main goals of the project is to develop reference datasets that can be used for validation of bioinformatics pipelines and for standardization purposes.</p> <p>Semi-artificial datasets have been created for this purpose (Datasets 1 to 10). They are composed of a "real" HTS dataset spiked with artificial viral reads. It will allow researchers to adjust their pipeline/parameters as good as possible to approximate the actual viral composition of the semi-artificial datasets. Each semi-artificial dataset allows to test one or several limitations that could prevent virus detection or a correct virus identification from HTS data (<i>i.e.</i> low viral concentration, new viral species, non-complete genome).</p> <p>Eight artificial datasets only composed of viral reads (no background data) have also been created (Datasets 11 to 18). Each dataset consists of a mix of several isolates from the same viral species showing different frequencies. The viral species were selected to be as divergent as possible. These datasets can be used to test haplotype reconstruction software, the goal being to reconstruct all the isolates present in a dataset.</p> <p><span>A GitLab repository (<a href="https://gitlab.com/ilvo/VIROMOCKchallenge">https://gitlab.com/ilvo/VIROMOCKchallenge</a>) is available and provides a complete description of the composition of each dataset, the methods used to create them and their goals.</span></p>
Figure 10 in Evaluation of the Chilli veinal mottle virus CP gene expressing transgenic Nicotiana benthamiana plants for disease resistance against the virus
Figure 10. Symptoms development in transgenic plants after challenging with ChiVMV isolate ATIPK at15dpi. A) Resistance transgenic lines. B) Moderately resistance transgenic lines. C) Moderately susceptible transgenic lines.
Figure 8 in Evaluation of the Chilli veinal mottle virus CP gene expressing transgenic Nicotiana benthamiana plants for disease resistance against the virus
Figure 8. PCR products from transgenic plants. (a) Lane 1-3, represent PCR product from agro-infilterated plants. Lane 4, control plant. (b) Lane 1-9, RT- PCR product from transgenic plants represent the presence of CP gene transcription. Lane 10, represents untransformed control sample.
Figure 5 in Evaluation of the Chilli veinal mottle virus CP gene expressing transgenic Nicotiana benthamiana plants for disease resistance against the virus
Figure 5. Maximum likelihood tree of ChiVMV isolate ATIPK on nucleotide sequence of CP gene with 22 ChiVMV isolates from the world. The bootstrap analysis was conducted in 1000 replications. ZYMV (AB127936) sequence is used as out-group.
Figure 4 in Evaluation of the Chilli veinal mottle virus CP gene expressing transgenic Nicotiana benthamiana plants for disease resistance against the virus
Figure 4. RT-PCR amplification of the CP gene with CVMV1037/ oligo(dT). Lane 1, 2, 3 and 4 contains 1.2kb amplified product of NIb and CP gene.
Area wide monitoring of plant and honey bee (Apis mellifera) viruses in blueberry (Vaccinium corymbosum) agroecosystems facilitated by honey bee pollination
<p>Metadata associated with plant and bee virus identification on blueberry farms</p>
Data from: A new plant virus discovered by immunocapture of double stranded RNA; assessment of a novel approach for viral metagenomics studies
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Semi-artificial datasets as a resource for validation of bioinformatics pipelines for plant virus detection
Open the record for dataset details and reuse information.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.