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Identification of emerging viral genomes in transcriptomic datasets of alfalfa (Medicago sativa L.).

ABSTRACT: BACKGROUND:Publicly available transcriptomic datasets have become a valuable tool for the discovery of new pathogens, particularly viruses. In this study, several coding-complete viral genomes previously not found or experimentally confirmed in alfalfa were identified in the plant datasets retrieved from the NCBI Sequence Read Archive. METHODS:Publicly available Medicago spp. transcriptomic datasets were retrieved from the NCBI SRA database. The raw reads were first mapped to the reference genomes of Medicago sativa and Medigago truncatula followed by the alignment of the unmapped reads to the NCBI viral genome database and de novo assembly using the SPAdes tool. When possible, assemblies were experimentally confirmed using 5'/3' RACE and RT-PCRs. RESULTS:Twenty three different viruses were identified in the analyzed datasets, of which several represented emerging viruses not reported in alfalfa prior to this study. Among them were two strains of cnidium vein yellowing virus, lychnis mottle virus and Cactus virus X, for which coding-complete genomic sequences were obtained by a de novo assembly. CONCLUSIONS:The results improve our knowledge of the diversity and host range of viruses infecting alfalfa, provide essential tools for their diagnostics and characterization and demonstrate the utility of transcriptomic datasets for the discovery of new pathogens.

SUBMITTER: Jiang P

PROVIDER: S-EPMC6902351 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description: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.

Project description:Flower development, pollination, and fertilization are important stages in the sexual reproduction process of plants; they are also critical steps in the control of seed formation and development. During alfalfa (Medicago sativa L.) seed production, some distinct phenomena such as a low seed setting ratio, serious flower falling, and seed abortion commonly occur. However, the causes of these phenomena are complicated and largely unknown. An understanding of the mechanisms that regulate alfalfa flowering is important in order to increase seed yield. Hence, proteomic technology was used to analyze changes in protein expression during the stages of alfalfa flower development. Flower samples were collected at pre-pollination (S1), pollination (S2), and the post-pollination senescence period (S3). Twenty-four differentially expressed proteins were successfully identified, including 17 down-regulated in pollinated flowers, one up-regulated in pollinated and senesced flowers, and six up-regulated in senesced flowers. The largest proportions of the identified proteins were involved in metabolism, signal transduction, defense response, oxidation reduction, cell death, and programmed cell death (PCD). Their expression profiles demonstrated that energy metabolism, carbohydrate metabolism, and amino acid metabolism provided the nutrient foundation for pollination in alfalfa. Furthermore, there were three proteins involved in multiple metabolic pathways: dual specificity kinase splA-like protein (kinase splALs), carbonic anhydrase, and NADPH: quinone oxidoreductase-like protein. Expression patterns of these proteins indicated that MAPK cascades regulated multiple processes, such as signal transduction, stress response, and cell death. PCD also played an important role in the alfalfa flower developmental process, and regulated both pollination and flower senescence. The current study sheds some light on protein expression profiles during alfalfa flower development and contributes to the understanding of the basic molecular mechanisms during the alfalfa flowering process. These results may offer insight into potential strategies for improving seed yield, quality, and stress tolerance in alfalfa.

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Identification of emerging viral genomes in transcriptomic datasets of alfalfa (Medicago sativa L.).

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