Next Article in Journal
Downregulation of sCD40 and sCTLA4 in Recovered COVID-19 Patients with Comorbidities
Next Article in Special Issue
Characterizing the Virome of Apple Orchards Affected by Rapid Decline in the Okanagan and Similkameen Valleys of British Columbia (Canada)
Previous Article in Journal
Clinical Characteristics and Risk Factors for Intra-Abdominal Infection with Chryseobacterium indologenes after Orthotopic Liver Transplantation
Previous Article in Special Issue
Complete Genomic RNA Sequence of Tuberose Mild Mosaic Virus and Tuberose Mild Mottle Virus Acquired by High-Throughput Sequencing
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Unlocking the Hidden Genetic Diversity of Varicosaviruses, the Neglected Plant Rhabdoviruses

by
Nicolas Bejerman
1,2,*,
Ralf G. Dietzgen
3,* and
Humberto Debat
1,2,*
1
Instituto de Patología Vegetal, Centro de Investigaciones Agropecuarias, Instituto Nacional de Tecnología Agropecuaria (IPAVE—CIAP—INTA), Camino 60 Cuadras Km 5.5, Córdoba X5020ICA, Argentina
2
Consejo Nacional de Investigaciones Científicas y Técnicas, Unidad de Fitopatología y Modelización Agrícola, Camino 60 Cuadras Km 5.5, Córdoba X5020ICA, Argentina
3
Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St. Lucia, QLD 4072, Australia
*
Authors to whom correspondence should be addressed.
Pathogens 2022, 11(10), 1127; https://doi.org/10.3390/pathogens11101127
Submission received: 20 September 2022 / Revised: 27 September 2022 / Accepted: 27 September 2022 / Published: 29 September 2022
(This article belongs to the Special Issue Plant Virus Genome Diversity in Plant Hosts and Insect Vectors)

Abstract

:
The genus Varicosavirus is one of six genera of plant-infecting rhabdoviruses. Varicosaviruses have non-enveloped, flexuous, rod-shaped virions and a negative-sense, single-stranded RNA genome. A distinguishing feature of varicosaviruses, which is shared with dichorhaviruses, is a bi-segmented genome. Before 2017, a sole varicosavirus was known and characterized, and then two more varicosaviruses were identified through high-throughput sequencing in 2017 and 2018. More recently, the number of known varicosaviruses has substantially increased in concert with the extensive use of high-throughput sequencing platforms and data mining approaches. The novel varicosaviruses have revealed not only sequence diversity, but also plasticity in terms of genome architecture, including a virus with a tentatively unsegmented genome. Here, we report the discovery of 45 novel varicosavirus genomes which were identified in publicly available metatranscriptomic data. The identification, assembly, and curation of the raw Sequence Read Archive reads has resulted in 39 viral genome sequences with full-length coding regions and 6 with nearly complete coding regions. The highlights of the obtained sequences include eight varicosaviruses with unsegmented genomes, which are linked to a phylogenetic clade associated with gymnosperms. These findings have resulted in the most complete phylogeny of varicosaviruses to date and shed new light on the phylogenetic relationships and evolutionary landscape of this group of plant rhabdoviruses. Thus, the extensive use of sequence data mining for virus discovery has allowed us to unlock of the hidden genetic diversity of varicosaviruses, the largely neglected plant rhabdoviruses.

1. Introduction

A recently discovered huge number of diverse viruses has revealed the complexities of the evolutionary landscape of replicating entities and the challenges associated with their classification [1], leading to the first comprehensive proposal of the virus world megataxonomy [2]. Nevertheless, a minuscule portion, likely a small fraction of one percent, of the virosphere has been characterized so far [3]. Therefore, we have a limited knowledge of the vast world virome, with its remarkable diversity, that includes every potential host organism assessed so far [4,5,6]. Data mining of publicly available transcriptome datasets has become an efficient and inexpensive strategy to unlock the diversity of the plant virosphere [5]. Data-driven virus discovery relies on the vast number of available datasets on the Sequence Read Archive (SRA) of the National Center for Biotechnology Information (NCBI). This resource, which is growing at an exceptional rate and includes data of a large and diverse number of organisms, represents a substantial fraction of species that populate our planet, which makes the SRA database an invaluable source to identify novel viruses [7].
Varicosavirus is one of the six genera that are comprised of plant rhabdoviruses (family Rhabdoviridae, subfamily Betarhabdovirinae), and its members are thought to have a negative-sense, single-stranded, bi-segmented RNA genome [8]. Nevertheless, recently, we described the first apparently unsegmented varicosavirus [9]. In those varicosaviruses with segmented genomes, RNA 1 consists of one to two genes, with one of those encoding the RNA-dependent RNA polymerase L, while RNA 2 consists of three to five genes, with the first open reading frame (ORF) encoding a nucleocapsid protein (N) [8,10]. On the other hand, the only unsegmented varicosavirus described so far has five ORFs, in the order: 3′-N-Protein 2-Protein 3-Protein 4-L-5′ [9]. Varicosaviruses appear to have a diverse host range that includes dicots, monocots, gymnosperms, ferns, and liverworts [6,9]. The vector of a sole member, lettuce big vein-associated virus (LBVaV), has been characterized, which is the chytrid fungus Olpidium spp. [11].
Until 2017, LBVaV was the only identified and extensively characterized varicosavirus [12,13,14], and then, in 2017 and 2018, two novel varicosaviruses were identified through high-throughput sequencing (HTS) [15,16]. However, in 2021 and 2022, there was a five-fold increase in the number of reported varicosaviruses, with 12 out 15 discovered through data mining of publicly available transcriptome datasets [6,9,17,18], while the other three were identified using HTS [19,20,21] (Supplementary Figure S1). Nevertheless, only some minor biological aspects, such as mechanical transmissibility, of some of these members were further characterized [15,20]. Therefore, varicosaviruses are, by far, the least-studied plant rhabdoviruses, and many aspects of their epidemiology remain elusive. In terms of genetic diversity, before this study, while greatly expanded by recent works, the Varicosavirus genus includes only three accepted species and 15 tentative members.
In this study, we identified 45 novel varicosaviruses by analyzing publicly available metatranscriptomic data. Thus, the extensive use of data mining for virus discovery has allowed us to unlock some of the hidden diversity of varicosaviruses, the much-neglected plant rhabdoviruses.

2. Material and Methods

2.1. Identification of Plant Rhabdovirus Sequences from Public Plant RNA-seq Datasets

Three strategies were used to detect varicosavirus sequences: (1) Amino acid sequences corresponding to the nucleocapsid and polymerase proteins of known varicosaviruses were used as queries in tBlastn searches with the parameters word size = 6, expected threshold = 10, and scoring matrix = BLOSUM62, against the Viridiplantae (taxid: 33090) Transcriptome Shotgun Assembly (TSA) sequence databases. The obtained hits were manually explored and based on percentage identity, query coverage, and E-value (>1 × 10−5) and shortlisted as likely corresponding to novel virus transcripts, which were then further analyzed. (2) Raw sequence data corresponding to the SRA database associated with the 1K study [22] were explored for varicosa-like virus sequences. (3) The Serratus database was explored, employing the serratus explorer tool [5], and using as queries the sequences of LBVaV, red clover varicosavirus, and black grass varicosavirus. Those SRA libraries that matched the query sequences (alignment identity > 45%; score > 10) were further explored in detail.

2.2. Sequence Assembly and Identification

The nucleotide (nt) raw sequence reads from each SRA experiment, which are associated with different NCBI bioprojects (Table 1), were downloaded and pre-processed by trimming and filtering with the Trimmomatic tool as implemented in http://www.usadellab.org/cms/?page=trimmomatic (accessed on 19 August 2022). The resulting reads were assembled de novo with rnaSPAdes using standard parameters on the Galaxy.org server. The transcripts obtained from the de novo transcriptome assembly were subjected to bulk local BLASTX searches (E-value < 1 × 10−5) against a collection of varicosavirus protein sequences available at https://www.ncbi.nlm.nih.gov/protein?term=txid140295[Organism] (accessed on 19 August 2022). The resulting viral sequence hits of each bioproject were visually explored. Tentative virus-like contigs were curated (extended or confirmed) by iteratively mapping each SRA library’s filtered reads. This strategy used BLAST/nhmmer to extract a subset of reads related to the query contig and used the retrieved reads to extend the contig and then repeated the process iteratively using the extended sequence as query. The extended and polished transcripts were reassembled using the Geneious v8.1.9 (Biomatters Ltd., San Diego, CA, USA) alignment tool with high sensitivity parameters. Bowtie2, available at http://bowtie-bio.sourceforge.net/bowtie2/index.shtml (accessed on 26 September 2022), was used with standard parameters for filtered read mapping to calculate the mean coverage of each assembled virus sequence.

2.3. Bioinformatics Tools and Analyses

2.3.1. Sequence Analyses

ORFs were predicted with ORFfinder (minimal ORF length 150 nt, genetic code 1, https://www.ncbi.nlm.nih.gov/orffinder/, accessed on 22 August 2022) and the functional domains and architectures of translated gene products were determined using InterPro (https://www.ebi.ac.uk/interpro/search/sequence-search, accessed on 22 August 2022) and the NCBI conserved domain database-CDD v3.19 (https://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi, accessed on 22 August 2022). Further, HHPred and HHBlits, as implemented in https://toolkit.tuebingen.mpg.de/#/tools/ (accessed on 22 August 2022), were used to complement the annotation of divergent predicted proteins by hidden Markov models. Transmembrane domains were predicted using the TMHMM version 2.0 tool (http://www.cbs.dtu.dk/services/TMHMM/, accessed on 22 August 2022).

2.3.2. Pairwise Sequence Identity

Percentage amino acid (aa) sequence identities of the L protein of those varicosaviruses identified in this study, as well as those available in the NCBI database, were calculated using SDTv1.2 [59]. Virus names, abbreviations, and NCBI accession numbers of the varicosaviruses already reported are shown in Supplementary Table S1.

2.3.3. Phylogenetic Analysis

Phylogenetic analysis based on the predicted polymerase protein of all available varicosaviruses was completed using MAFFT 7.505 (https://mafft.cbrc.jp/alignment/software) (accessed on 25 August 2022) with multiple aa sequence alignments and using FFT-NS-i as the best-fit model. The aligned aa sequences were used as inputs to generate phylogenetic trees using the maximum-likelihood method (best-fit model = E-INS-i) with the FastTree 2.1.11 tool (available at http://www.microbesonline.org/fasttree/) (accessed on 25 August 2022). Local support values were calculated with the Shimodaira-Hasegawa test (SH) and 1000 trees were resampled. The L proteins of four selected cytorhabdoviruses were used as outgroups. To explore the potential phylogenetic co-divergence of varicosaviruses with their associated host plants, plant host cladograms were generated in phyloT v.2 (https://phylot.biobyte.de/, accessed on 26 August 2022) based on NCBI Taxonomy. Connections were manually inferred between the viral and plant phylograms and cladograms and visually inspected.

3. Results and Discussion

Most varicosaviruses likely do not induce easily discernable disease symptoms. Since their presence is not expected in the sequencing libraries of apparently “healthy” vegetables, they are ideal candidates to be identified through mining publicly available metatranscriptomic data. Accordingly, very recently, 12 novel proposed varicosaviruses were discovered when publicly available transcriptome datasets were mined [6,9,17,18]. Therefore, to unlock the hidden diversity of varicosaviruses, we extensively searched for these viruses in already available plant transcriptome data. This bioinformatics research resulted in the identification of 45 novel varicosaviruses, including the corrected full-length coding genome segments of the previously reported Arceuthobium sichuanense-associated virus 2 (ASaV2) [18], which had apparently been reconstructed from the genome segments of two different varicosaviruses. We also identified three novel variants of three recently discovered varicosaviruses, confirming and strengthening the results previously reported by Bejerman et al. [9]. This significant number of newly discovered varicosaviruses represents a 3.5-fold increase in the known varicosaviruses (Supplementary Figure S1), which clearly highlights the importance of data-driven virus discovery to illuminate the landscape of largely overlooked taxonomic groups, such as varicosaviruses.
More details, identification, assembly, and curation of raw SRA reads in this study resulted in 39 viral genome sequences with full-length coding regions and six with nearly complete coding regions. These viruses were associated with 45 plant host species (Table 1). Most of the tentative plant hosts of the novel varicosaviruses are herbaceous dicots (24/45), nine are herbaceous monocots, eight are gymnosperms, and four are liverworts and ferns (Table 1).
The genomes of 37 viruses identified in this study were bisegmented, where the RNA 1 of 36 of them encodes only the L protein, while the RNA 1 of Chamaemelum virus 1 (ChaV1) has an additional ORF 5’ to the L gene, supported by the identification of the conserved intergenic sequence (see below), encoding a 171 aa putative protein (Table 1, Figure 1), which appears to be the first varicosavirus reported with an ORF in this position. The RNA 2 segments of these 37 viruses have three to five genes in the order 3′-N-PX-5′. Twelve of them have three genes, while 17 have four genes and eight contained five genes (Table 1, Figure 1). Of the previously reported varicosaviruses, six have three genes, four have four genes, and four have five genes; therefore, RNA 2 has a flexible genomic architecture and is apparently the most frequent genomic organization in the RNA 2 of varicosaviruses that includes four genes (21 members) or three genes (18 members).
The consensus gene junction sequences of the bisegmented varicosaviruses were determined to be 3′ AU(N)5UUUUUGCUCU 5′ (Table 2), while the gene junction sequences of all but one of the unsegmented varicosaviruses differed slightly in the 3´ end, being GU(N)5 instead of AU(N)5 (Table 2). Strikingly, the consensus gene junction of the unsegmented Torreya virus 1 (TorV1) was similar to that of the bisegmented varicosaviruses. The potential implication of this difference in the gene junctions needs to be explored since it could be linked to the basal evolutionary grouping of TorV1 (see below).
There is a great dearth of data on the potential functions of putative proteins, other than N and L, encoded by varicosaviruses, and, intriguingly, there were no conserved domains identified in these proteins. We grasped some shared identities, primarily for the cognate P3 (but also for several P2 proteins) (Table 1), though for most of the encoded proteins, the BlastP results were orphans, with no known signals or domains present and no clues towards their putative (or conserved) function. Thus, further studies should be focused on the functional characterization of these proteins to gain essential knowledge regarding the elusive proteome of varicosaviruses beyond the N and L proteins.
The pairwise aa sequence identities between the L proteins of all the reported varicosaviruses, including those identified in this study, showed great diversity and an overall low identity between the different varicosaviruses (Figure 2, Supplementary Table S2). Relatively low sequence identity is a common feature among rhabdovirus taxa, characterized by a high level of diversity in both the genome sequence and organization [10]. In addition, the overall low sequence identity among the novel viruses detected here and with the previously described varicosaviruses suggests that despite the many viruses identified in this study, there likely remains a significant amount of virus “dark matter” for yet-to-be-discovered varicosaviruses.
When we analyzed the diversity between the variants of viruses which are likely members of the same species, we found that proteins encoded by the Brassica virus 2, Spinach virus 1, and Sciadopitys virus 1 variants were very similar. On the other hand, proteins encoded by the Brassica virus 1, Lolium virus 1, and Melilotus virus 1 variants were quite diverse, but, nevertheless, they showed aa identities for the N and L proteins exceeding 80%. Thus, we tentatively propose an aa sequence identity of 80% across the L gene as the threshold for species demarcation in the Varicosavirus genus, a taxonomic criterion which had previously not been fully defined [10]. This threshold is strongly supported by the comparison of the L protein aa sequence of 60 viruses (Figure 2, Supplementary Table S2). Based on this criterion, all 39 novel viruses with their complete coding region assembled in this study should be considered as belonging to novel Varicosavirus species, which would increase the number of members of the genus by more than an order of magnitude.
Bejerman et al. [9] tentatively reported the first unsegmented varicosavirus, Pinus flexilis virus 1 (PiFleV1), which was associated with the gymnosperm Pinus flexilis. In this study, we complemented that result by the discovery of eight additional unsegmented varicosaviruses which were exclusively associated with gymnosperms (Table 1), some of which are linked to the same genus Pinus and present a significant co-evolution of viruses and hosts. These results robustly support a clade of gymnosperm-associated varicosaviruses with a distinct genome architecture, requiring the rewriting of a previously proposed key feature and fundamental marker of varicosaviruses: their genomic bisegmented nature. It is tempting to speculate that the unsegmented genomic architecture may be linked to the adaptation to gymnosperm hosts and a shared ancient evolutionary history of these viruses and hosts.
Interestingly, in the BlastP analyses of N, P2, and P3 of the gymnosperm-associated viruses, most of them had, as a best hit to the cognate proteins encoded by the putative bisegmented ASaV2 (Table 1), a virus apparently hosted by a parasitic plant of spruce (Picea, Pinacea). Furthermore, unexpectedly, the best hit of the putative P5 protein encoded on ASaV2 RNA2 was a fragment of the PiFleV1 L protein, while the deduced L protein on ASaV2 RN1 was not a best hit with PiFleV1, but instead, with the non-gymnosperm-linked MelRoV1 hosted by the Orobanchaceae parasitic plant Melampyrum roseum. Thus, we suspected that ASaV2 was potentially misassembled from fragments belonging to two different viruses. Consequently, we re-analyzed the original SRA data used by Sidhartan et al. [18] and were able to assemble two distinct varicosavirus genomes: one bisegmented genome presumably linked to the parasitic plant and one unsegmented genome most likely linked to spruce, which would support our hypothesis. We believe that there are several reasons that led to the original ASaV2 description: (i) the atypical and unexpected existence at the time of an unsegmented varicosavirus; (ii) the presence of two varicosaviruses in the very same sequencing library, which may be the first tentative evidence in the literature of co-infection of two varicosaviruses; and (iii) the fact that the sequence reads corresponding to the L gene region of the unsegmented varicosavirus were low, which may have affected the assembling pipelines used by the authors. All in all, independently verifying unexpected re-analysed SRA data may lead to a clearer understanding of the genomic structure of the mined RNA virus genomes. Nevertheless, the inability to return to the original biological material to replicate, confirm, and validate the assembled viral genome sequences is a significant limitation of the data mining approach for virus discovery. Thus, researchers must be cautious when analysing SRA public data for virus discovery and understand the preliminary nature of its results.
The phylogenetic analysis based on the deduced L protein aa sequences placed all unsegmented varicosaviruses, except TorV1, into a distinct clade. Interestingly, TorV1 was placed in a clade that was basal to all varicosaviruses (Figure 1). This distinct phylogenetic branching and clustering of the unsegmented viruses suggests that they share a unique evolutionary history among varicosaviruses. Moreover, this may suggest that bisegmented varicosaviruses are evolutionarily younger than unsegmented ones. It may also mean that a genome split in varicosa-like viruses occurred after the radiation of gymnosperms and angiosperms. Bisegmented varicosaviruses did not cluster according to their genomic organization, nor did they cluster with the plant species associated with each virus (Figure 1). For example, brassica virus 1 and brassica virus 2 were placed in distinct clades, while two viruses associated with orchids (Ophius virus 1 and Caladenia virus 1) were placed in different clusters, and monocot-associated viruses were not all grouped together. On the other hand, all varicosaviruses associated with ferns and liverworts belonged to the same cluster, which was also shared with previously reported varicosaviruses from these plant types, while most of the grass-associated varicosaviruses were also clustered together (Figure 1).
We generated a tanglegram to compare the virus phylogram and plant host cladogram to further explore virus–host relationships (Figure 3). This analysis showed that the viruses of some clades clearly co-diverged with their hosts, including the gymnosperm-associated virus clade, the SpV1 and Silene virus 1 clade, the grass-associated virus clade, and the clade of fern and liverworts viruses, suggesting a shared host–virus evolution in those clades (Figure 3). However, the tanglegram topology also indicated that for most of the varicosaviruses, there was no apparent concordant evolutionary history with their plant hosts, similar to what was previously reported for invertebrate and vertebrate rhabdoviruses [60].
Several lines of evidence suggest that varicosaviruses may be vertically transmitted: (i) a close host–virus co-evolution in some clades may reflect species isolation and a lack of horizontal transmission, (ii) some viruses detected in this study were identified from seed transcriptomics databases, and (iii) an emerging characteristic of persistent, chronic infections of several plant viruses which are likely vertically transmitted are latent/asymptomatic infections, a characteristic which appears to be shared with varicosaviruses. Thus, further studies should be carried out to elucidate the transmission mode of varicosaviruses beyond the fungal-transmitted LBVaV [11]. It is worth mentioning that even with the availability of thousands of RNAseq libraries of fungi and arthropods, we failed to detect any evidence of varicosaviruses in those organisms, which could suggest that vectors of varicosaviruses are rare or non-existent.
Before the era of data-driven virus discovery, few viruses had been identified in gymnosperms [61,62,63,64]. However, when data mining was applied to publicly available transcriptomes, many novel viruses were identified in this large group of higher plants, highlighting the rich and diverse gymnosperm virosphere, which still is largely unexplored. A distinct clade of gymnosperm-associated viruses was recently identified within amalgaviruses [65], while we recently described two distinct caulimovirids and geminivirids linked to the gnetophyte Welwitschia mirabilis [66]. Eight unsegmented varicosaviruses associated with gymnosperms were identified in this study, and another was discovered by Bejerman et al. [9]. Taken together, all of these recently discovered viruses in gymnosperms strongly suggest that they may have evolutionary trajectories that are distinct from those infecting angiosperms. Thus, it is likely that further exploration of additional gymnosperm datasets or new transcriptome studies of other gymnosperms will yield plenty of novel viruses with unique features, highlighting their close evolution with their hosts. The clear association between gymnosperm-associated viruses and their hosts likely indicates a close coevolution, which suggest an early adaptation of this group of viruses to infect gymnosperms. This hypothesis is also supported by the distinct genomic architecture and divergent evolutionary history among varicosaviruses, as shown in the phylogenetic tree, which are characterized by long branches and distinctive clustering. Taken together, the gymnosperm-associated varicosaviruses could be taxonomically classified in a novel genus within the family Rhabdoviridae, subfamily Betarhabdovirinae, for which we suggest the name “Gymnorhavirus”.
In summary, this study highlights the importance of the analysis of SRA public data as a valuable tool not only to accelerate the discovery of novel viruses, but also to gain insight into their evolution and to refine virus taxonomy. Using this approach, we looked for hidden varicosa-like virus sequences to unlock the veiled diversity of a largely neglected plant rhabdovirus genus, the varicosaviruses. Our findings, including an approximately 3.5-fold expansion of the current genomic diversity within the genus, resulted in the most complete phylogeny of varicosaviruses to date, and they shed new light on the genomic architecture, phylogenetic relationships, and evolutionary landscape of this unique group of plant rhabdoviruses. Future studies should assess many intriguing aspects of the biology and ecology of these viruses such as potential symptoms, vertical transmission, and putative vectors.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/pathogens11101127/s1, Figure S1: Stacked bar chart showing the number of previously reported varicosaviruses and those in this study; Table S1: Virus names, abbreviations, and NCBI accession numbers of the varicosavirus sequences used in this study; Table S2: Amino acid sequence identity of the complete L gene ORF.

Author Contributions

Conceptualization, N.B., R.G.D. and H.D.; data analysis, N.B. and H.D.; writing—original draft preparation, N.B.; writing—review and editing, N.B., R.G.D. and H.D. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding. The participation of R.G.D. in this study was jointly supported by the Queensland Government Department of Agriculture and Fisheries and the University of Queensland through the Queensland Alliance for Agriculture and Food Innovation.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The nucleotide sequence data reported are available in the Third Party Annotation Section of the DDBJ/ENA/GenBank databases under the accession numbers TPA: BK061731-BK061826. These sequences are available as Supplementary Materials.

Acknowledgments

The authors would like to express their sincere gratitude to the generators of the underlying data used for this work, which are cited in Table 1. By following open-access practices and supporting accessible raw sequence data in public repositories available to the research community, they have promoted the generation of new knowledge and ideas.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Koonin, E.V.; Krupovic, M.; Agol, V.I. The Baltimore Classification of Viruses 50 Years Later: How Does It Stand in the Light of Virus Evolution? Microbiol. Mol. Biol. Rev. 2021, 85, e0005321. [Google Scholar] [CrossRef]
  2. Koonin, E.V.; Dolja, V.V.; Krupovic, M.; Varsani, A.; Wolf, Y.I.; Yutin, N.; Zerbini, F.M.; Kuhn, J.H. Global Organization and Proposed Megataxonomy of the Virus World. Microbiol. Mol. Biol. Rev. 2020, 84, e00061-19. [Google Scholar] [CrossRef] [PubMed]
  3. Geoghegan, J.L.; Holmes, E.C. Predicting virus emergence amid evolutionary noise. Open Biol. 2017, 7, 170–189. [Google Scholar] [CrossRef] [PubMed]
  4. Dolja, V.V.; Krupovic, M.; Koonin, E.V. Deep Roots and Splendid Boughs of the Global Plant Virome. Annu. Rev. Phytopathol. 2020, 58, 23–53. [Google Scholar] [CrossRef] [PubMed]
  5. Edgar, R.C.; Taylor, J.; Lin, V.; Altman, T.; Barbera, P.; Meleshko, D.; Lohr, D.; Novakovsky, G.; Buchfink, B.; Al-Shayeb, B.; et al. Petabase-scale sequence alignment catalyses viral discovery. Nature 2022, 602, 142–147. [Google Scholar] [CrossRef]
  6. Mifsud, J.C.O.; Gallagher, R.V.; Holmes, E.C.; Geoghegan, J.L. Transcriptome Mining Expands Knowledge of RNA Viruses across the Plant Kingdom. J. Virol. 2022, e00260-22. [Google Scholar] [CrossRef]
  7. Lauber, C.; Seitz, S. Opportunities and Challenges of Data-Driven Virus Discovery. Biomolecules 2022, 12, 1073. [Google Scholar] [CrossRef]
  8. Dietzgen, R.G.; Bejerman, N.E.; Goodin, M.M.; Higgins, C.M.; Huot, O.B.; Kondo, H.; Martin, K.M.; Whitfield, A.E. Diversity and epidemiology of plant rhabdoviruses. Virus Res. 2020, 281, 197942. [Google Scholar] [CrossRef]
  9. Bejerman, N.; Dietzgen, R.; Debat, H. Illuminating the Plant Rhabdovirus Landscape through Metatranscriptomics Data. Viruses 2021, 13, 1304. [Google Scholar] [CrossRef]
  10. Walker, P.J.; Freitas-Astúa, J.; Bejerman, N.; Blasdell, K.R.; Breyta, R.; Dietzgen, R.G.; Fooks, A.R.; Kondo, H.; Kurath, G.; Kuzmin, I.V.; et al. ICTV Virus Taxonomy Profile: Rhabdoviridae 2022. J. Gen. Virol. 2022, 103, 001689. [Google Scholar] [CrossRef]
  11. Campbell, R.N. Fungal Transmission of Plant Viruses. Annu. Rev. Phytopathol. 1996, 34, 87–108. [Google Scholar] [CrossRef] [PubMed]
  12. Sasaya, T.; Ishikawa, K.; Koganezawa, H. The nucleotide sequence of RNA1 of Lettuce big-vein virus, genus Varicosavirus, reveals its relation to nonsegmented negative-strand RNA viruses. Virology 2002, 297, 289–297. [Google Scholar] [CrossRef] [PubMed]
  13. Sasaya, T.; Kusaba, S.; Ishikawa, K.; Koganezawa, H. Nucleotide sequence of RNA2 of Lettuce big-vein virus and evidence for a possible transcription termination/initiation strategy similar to that of rhabdoviruses. J. Gen. Virol. 2004, 85, 2709–2717. [Google Scholar] [CrossRef]
  14. Verbeek, M.; Dullemans, A.M.; van Bekkum, P.J.; van der Vlugt, R.A.A. Evidence for Lettuce big-vein associated virus as the causal agent of a syndrome of necrotic rings and spots in lettuce. Plant Pathol. 2013, 62, 444–451. [Google Scholar] [CrossRef]
  15. Koloniuk, I.; Fránová, J.; Sarkisova, T.; Přibylová, J.; Lenz, O.; Petrzik, K.; Špak, J. Identification and molecular characterization of a novel varicosa-like virus from red clover. Arch. Virol. 2018, 163, 2213–2218. [Google Scholar] [CrossRef] [PubMed]
  16. Sabbadin, F.; Glover, R.; Stafford, R.; Rozado-Aguirre, Z.; Boonham, N.; Adams, I.; Mumford, R.; Edwards, R. Transcriptome sequencing identifies novel persistent viruses in herbicide resistant wild-grasses. Sci. Rep. 2017, 7, srep41987. [Google Scholar] [CrossRef]
  17. Shin, C.; Choi, D.; Hahn, Y. Identification of the genome sequence of Zostera associated varicosavirus 1, a novel negative-sense RNA virus, in the common eelgrass (Zostera marina) transcriptome. Acta Virol. 2022, 65, 373–380. [Google Scholar] [CrossRef]
  18. Sidharthan, V.K.; Chaturvedi, K.K.; Baranwal, V.K. Diverse RNA viruses in a parasitic owering plant (spruce dwarf mistletoe) revealed through RNA-seq data mining. J. Gen. Plant Pathol. 2022, 88, 138–144. [Google Scholar] [CrossRef]
  19. Chen, Y.-M.; Sadiq, S.; Tian, J.-H.; Chen, X.; Lin, X.-D.; Shen, J.-J.; Chen, H.; Hao, Z.-Y.; Wille, M.; Zhou, Z.-C.; et al. RNA viromes from terrestrial sites across China expand environmental viral diversity. Nat. Microbiol. 2022, 7, 1312–1323. [Google Scholar] [CrossRef]
  20. Nabeshima, T.; Abe, J. High-throughput sequencing indicates novel Varicosavirus, Emaravirus and Deltapartitvirus infections in Vitis coignetiae. Viruses 2021, 13, 827. [Google Scholar] [CrossRef]
  21. Zhao, F.; Liu, H.; Qiao, Q.; Wang, Y.; Zhang, D.; Wang, S.; Tian, Y.; Zhang, Z. Complete genome sequence of a novel varicosavirus infecting tall morning glory (Ipomoea purpurea). Arch. Virol. 2021, 166, 3225–3228. [Google Scholar] [CrossRef]
  22. Leebens-Mack, J.H.; Barker, M.S.; Carpenter, E.J. One thousand plant transcriptomes and the phylogenomics of green plants. Nature 2019, 574, 679–685. [Google Scholar]
  23. Wang, Y.; Li, X.; Zhou, W.; Li, T.; Tian, C. De novo assembly and transcriptome characterization of spruce dwarf mistletoe Arceuthobium sichuanense uncovers gene expression profiling associated with plant development. BMC Genom. 2016, 17, 771. [Google Scholar] [CrossRef] [PubMed]
  24. Tang, M.; Zhao, W.; Xing, M.; Zhao, J.; Jiang, Z.; You, J.; Ni, B.; Ni, Y.; Liu, C.; Li, J. Resource allocation strategies among vegetative growth, sexual reproduction, asexual reproduction and defense during growing season of Aconitum kusnezoffii Reichb. Plant J. 2021, 105, 957–977. [Google Scholar] [CrossRef]
  25. Yu, C.; Zhan, X.; Zhang, C.; Xu, X.; Huang, J.; Feng, S.; Shen, C.; Wang, H. Comparative metabolomic analyses revealed the differential accumulation of taxoids, flavonoids and hormones among six Taxaceae trees. Sci. Hortic. 2021, 285, 110196. [Google Scholar] [CrossRef]
  26. Babineau, M.; Mahmood, K.; Mathiassen, S.K.; Kudsk, P.; Kristensen, M. De novo transcriptome assembly analysis of weed Apera spica-venti from seven tissues and growth stages. BMC Genom. 2017, 18, 128. [Google Scholar] [CrossRef] [PubMed]
  27. Rowarth, N.M.; Curtis, B.A.; Einfeldt, A.L.; Archibald, J.M.; Lacroix, C.R.; Gunawardena, A.H. RNA-Seq analysis reveals potential regulators of programmed cell death and leaf remodelling in lace plant (Aponogeton madagascariensis). BMC Plant Biol. 2021, 21, 375. [Google Scholar] [CrossRef] [PubMed]
  28. Jayasena, A.S.; Fisher, M.F.; Panero, J.L.; Secco, D.; Bernath-Levin, K.; Berkowitz, O.; Taylor, N.L.; Schilling, E.E.; Whelan, J.; Mylne, J.S. Stepwise Evolution of a Buried Inhibitor Peptide over 45 My. Mol. Biol. Evol. 2017, 34, 1505–1516. [Google Scholar] [CrossRef]
  29. Weitemier, K.; Straub, S.C.; Fishbein, M.; Bailey, C.D.; Cronn, R.C.; Liston, A. A draft genome and transcriptome of common milkweed (Asclepias syriaca) as resources for evolutionary, ecological, and molecular studies in milkweeds and Apocynaceae. PeerJ 2019, 7, e7649. [Google Scholar] [CrossRef]
  30. Shen, H.; Jin, D.; Shu, J.-P.; Zhou, X.-L.; Lei, M.; Wei, R.; Shang, H.; Wei, H.-J.; Zhang, R.; Liu, L.; et al. Large-scale phylogenomic analysis resolves a backbone phylogeny in ferns. GigaScience 2017, 7, gix116. [Google Scholar] [CrossRef]
  31. An, H.; Qi, X.; Gaynor, M.L.; Hao, Y.; Gebken, S.C.; Mabry, M.E.; McAlvay, A.C.; Teakle, G.R.; Conant, G.C.; Barker, M.S.; et al. Transcriptome and organellar sequencing highlights the complex origin and diversification of allotetraploid Brassica napus. Nat. Commun. 2019, 10, 2878. [Google Scholar] [CrossRef] [Green Version]
  32. Bisht, D.S.; Chamola, R.; Nath, M.; Bhat, S.R. Molecular mapping of fertility restorer gene of an alloplasmic CMS system in Brassica juncea containing Moricandia arvensis cytoplasm. Mol. Breed. 2015, 35, 14. [Google Scholar] [CrossRef]
  33. Wu, Q.; Wang, J.; Mao, S.; Xu, H.; Wu, Q.; Liang, M.; Yuan, Y.; Liu, M.; Huang, K. Comparative transcriptome analyses of genes involved in sulforaphane metabolism at different treatment in Chinese kale using full-length transcriptome sequencing. BMC Genom. 2019, 20, 377. [Google Scholar] [CrossRef]
  34. Xu, H.; Bohman, B.; Wong, D.C.J.; Rodriguez-Delgado, C.; Scaffidi, A.; Flematti, G.R.; Phillips, R.D.; Pichersky, E.; Peakall, R. Complex Sexual Deception in an Orchid Is Achieved by Co-opting Two Independent Biosynthetic Pathways for Pollinator Attraction. Curr. Biol. 2017, 27, 1867–1877.e5. [Google Scholar] [CrossRef] [PubMed]
  35. Tai, Y.; Hou, X.; Liu, C.; Sun, J.; Guo, C.; Su, L.; Jiang, W.; Ling, C.; Wang, C.; Wang, H.; et al. Phytochemical and comparative transcriptome analyses reveal different regulatory mechanisms in the terpenoid biosynthesis pathways between Matricaria recutita L. and Chamaemelum nobile L. BMC Genom. 2020, 21, 169. [Google Scholar] [CrossRef]
  36. Lü, P.; Yu, S.; Zhu, N.; Chen, Y.-R.; Zhou, B.; Pan, Y.; Tzeng, D.; Fabi, J.P.; Argyris, J.; Garcia-Mas, J.; et al. Genome encode analyses reveal the basis of convergent evolution of fleshy fruit ripening. Nat. Plants 2018, 4, 784–791. [Google Scholar] [CrossRef]
  37. Li, J.; Milne, R.I.; Ru, D.; Miao, J.; Tao, W.; Zhang, L.; Xu, J.; Liu, J.; Mao, K. Allopatric divergence and hybridization within Cupressus chengiana (Cupressaceae), a threatened conifer in the northern Hengduan Mountains of western China. Mol. Ecol. 2020, 29, 1250–1266. [Google Scholar] [CrossRef]
  38. Huang, C.; Qi, X.; Chen, D.; Qi, J.; Ma, H. Recurrent genome duplication events likely contributed to both the ancient and recent rise of ferns. J. Integr. Plant Biol. 2019, 62, 433–455. [Google Scholar] [CrossRef]
  39. Osuna-Mascaró, C.; de Casas, R.R.; Gómez, J.M.; Loureiro, J.; Castro, S.; Landis, J.B.; Hopkins, R.; Perfectti, F. Hybridization and introgression are prevalent in Southern European Erysimum (Brassicaceae) species. Ann. Bot. 2022. [Google Scholar] [CrossRef] [PubMed]
  40. Young, E.; Carey, M.; Meharg, A.A.; Meharg, C. Microbiome and ecotypic adaption of Holcus lanatus (L.) to extremes of its soil pH range, investigated through transcriptome sequencing. Microbiome 2018, 6, 48. [Google Scholar] [CrossRef]
  41. Nevado, B.; Atchison, G.W.; Hughes, C.E.; Filatov, D.A. Widespread adaptive evolution during repeated evolutionary radiations in New World lupins. Nat. Commun. 2016, 7, 12384. [Google Scholar] [CrossRef] [Green Version]
  42. Wu, F.; Duan, Z.; Xu, P.; Yan, Q.; Meng, M.; Cao, M.; Jones, C.S.; Zong, X.; Zhou, P.; Wang, Y.; et al. Genome and systems biology of Melilotus albus provides insights into coumarins biosynthesis. Plant Biotechnol. J. 2021, 20, 592–609. [Google Scholar] [CrossRef] [PubMed]
  43. Huang, R.; Snedden, W.; DiCenzo, G. Reference nodule transcriptomes for Melilotus officinalis and Medicago sativa cv. Algonquin. Grassl. Res. 2022, 6, e408. [Google Scholar] [CrossRef]
  44. Piñeiro Fernández, L.; Byers, K.J.R.P.; Cai, J.; Sedeek, K.E.M.; Kellenberger, R.T.; Russo, A.; Qi, W.; Aquino Fournier, C.; Schlüter, P.M. A Phylogenomic Analysis of the Floral Transcriptomes of Sexually Deceptive and Rewarding European Orchids, Ophrys and Gymnadenia. Front. Plant Sci. 2019, 10, 1553. [Google Scholar] [CrossRef]
  45. Peery, R.M.; McAllister, C.H.; Cullingham, C.I.; Mahon, E.L.; Arango-Velez, A.; Cooke, J.E. Comparative genomics of the chitinase gene family in lodgepole and jack pines: Contrasting responses to biotic threats and landscape level investigation of genetic differentiation. Botany 2021, 99, 355–378. [Google Scholar] [CrossRef]
  46. Cai, N.; Xu, Y.; Chen, S.; He, B.; Li, G.; Li, Y.; Duan, A. Variation in seed and seedling traits and their relations to geo-climatic factors among populations in Yunnan Pine (Pinus yunnanensis). J. For. Res. 2016, 27, 1009–1017. [Google Scholar] [CrossRef]
  47. Zhao, Z.; Luo, Z.; Yuan, S.; Mei, L.; Zhang, D. Global transcriptome and gene co-expression network analyses on the development of distyly in Primula oreodoxa. Heredity 2019, 123, 784–794. [Google Scholar] [CrossRef] [PubMed]
  48. Pellino, M.; Hojsgaard, D.; Schmutzer, T.; Scholz, U.; Hörandl, E.; Vogel, H.; Sharbel, T.F. Asexual genome evolution in the apomictic Ranunculus auricomus complex: Examining the effects of hybridization and mutation accumulation. Mol. Ecol. 2013, 22, 5908–5921. [Google Scholar]
  49. Yang, Z.; Li, W.; Su, X.; Ge, P.; Zhou, Y.; Hao, Y.; Shu, H.; Gao, C.; Cheng, S.; Zhu, G.; et al. Early Response of Radish to Heat Stress by Strand-Specific Transcriptome and miRNA Analysis. Int. J. Mol. Sci. 2019, 20, 3321. [Google Scholar] [CrossRef]
  50. Zhou, B.; Wang, J.; Lou, H.; Wang, H.; Xu, Q. Comparative transcriptome analysis of dioecious, unisexual floral development in Ribes diacanthum pall. Gene 2019, 699, 43–53. [Google Scholar] [CrossRef] [PubMed]
  51. Wickett, N.J.; Mirarab, S.; Nguyen, N.; Warnow, T.; Carpenter, E.; Matasci, N.; Ayyampalayam, S.; Barker, M.S.; Burleigh, J.G.; Gitzendanner, M.A.; et al. Phylotranscriptomic analysis of the origin and early diversification of land plants. Proc. Natl. Acad. Sci. USA 2014, 111, E4859–E4868. [Google Scholar] [CrossRef] [PubMed]
  52. Meier, S.K.; Adams, N.; Wolf, M.; Balkwill, K.; Muasya, A.M.; Gehring, C.A.; Bishop, J.M.; Ingle, R.A. Comparative RNA -seq analysis of nickel hyperaccumulating and non-accumulating populations of Senecio coronatus (Asteraceae). Plant J. 2018, 95, 1023–1038. [Google Scholar] [CrossRef] [Green Version]
  53. Baloun, J.; Nevrtalova, E.; Kovacova, V.; Hudzieczek, V.; Čegan, R.; Vyskot, B.; Hobza, R. Characterization of the HMA7 gene and transcriptomic analysis of candidate genes for copper tolerance in two Silene vulgaris ecotypes. J. Plant Physiol. 2014, 171, 1188–1196. [Google Scholar] [CrossRef]
  54. Clancy, M.V.; Haberer, G.; Jud, W.; Niederbacher, B.; Niederbacher, S.; Senft, M.; Zytynska, S.E.; Weisser, W.W.; Schnitzler, J.-P. Under fire-simultaneous volatilome and transcriptome analysis unravels fine-scale responses of tansy chemotypes to dual herbivore attack. BMC Plant Biol. 2020, 20, 551. [Google Scholar] [CrossRef] [PubMed]
  55. Zhou, T.; Luo, X.; Yu, C.; Zhang, C.; Zhang, L.; Song, Y.B.; Dong, M.; Shen, C. Transcriptome analyses provide insights into the expression pattern and sequence similarity of several taxol biosynthesis-related genes in three Taxus species. BMC Plant Biol. 2019, 19, 33. [Google Scholar] [CrossRef] [PubMed]
  56. Hodge, B.A.; Paul, P.A.; Stewart, L.R. Occurrence and High-Throughput Sequencing of Viruses in Ohio Wheat. Plant Dis. 2020, 104, 1789–1800. [Google Scholar] [CrossRef]
  57. Yu, X.; Wang, W.; Yang, H.; Zhang, X.; Wang, D.; Tian, X. Transcriptome and comparative chloroplast genome analysis of Vincetoxicum versicolor: Insights into molecular evolution and phylogenetic implication. Front. Genet. 2021, 12, 602528. [Google Scholar] [CrossRef]
  58. Lanver, D.; Müller, A.N.; Happel, P.; Schweizer, G.; Haas, F.B.; Franitza, M.; Pellegrin, C.; Reissmann, S.; Altmüller, J.; Rensing, S.A.; et al. The Biotrophic Development of Ustilago maydis Studied by RNA-Seq Analysis. Plant Cell 2018, 30, 300–323. [Google Scholar] [CrossRef]
  59. Muhire, B.M.; Varsani, A.; Martin, D.P. SDT: A Virus Classification Tool Based on Pairwise Sequence Alignment and Identity Calculation. PLoS ONE 2014, 9, e108277. [Google Scholar] [CrossRef]
  60. Geoghegan, J.L.; Duchêne, S.; Holmes, E.C. Comparative analysis estimates the relative frequencies of co-divergence and cross-species transmission within viral families. PLOS Pathog. 2017, 13, e1006215. [Google Scholar] [CrossRef]
  61. Alvarez-Quinto, R.A.; Lockhart, B.E.L.; Fetzer, J.L.; Olszewski, E.N. Genomic characterization of cycad leaf necrosis virus, the first badnavirus identified in a gymnosperm. Arch. Virol. 2020, 165, 1671–1673. [Google Scholar] [CrossRef] [PubMed]
  62. Koh, S.H.; Li, H.; Admiraal, R.; Jones, M.G.; Wylie, S. Catharanthus mosaic virus: A potyvirus from a gymnosperm, Welwitschia mirabilis. Virus Res. 2015, 203, 41–46. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  63. Han, S.S.; Karasev, A.V.; Ieki, H.; Iwanami, T. Nucleotide sequence and taxonomy of Cycas necrotic stunt virus. Arch. Virol. 2002, 147, 2207–2214. [Google Scholar] [CrossRef] [PubMed]
  64. Rastrojo, A.; Núñez, A.; Moreno, D.A.; Alcamí, A. A New Putative Caulimoviridae Genus Discovered through Air Metagenomics. Microbiol. Resour. Announc. 2018, 7, e00955-18. [Google Scholar] [CrossRef]
  65. Sidharthan, V.K.; Rajeswari, V.; Vanamala, G.; Baranwal, V.K. Revisiting the amalgaviral landscapes in plant transcriptomes expands the host range of plant amalgaviruses. Available SSRN 4210265 2022. [Google Scholar] [CrossRef]
  66. Debat, H.; Bejerman, N. A glimpse into the DNA virome of the unique “living fossil” Welwitschia mirabilis. Gene 2022, 843, 146806. [Google Scholar] [CrossRef]
Figure 1. Left: Maximum-likelihood phylogenetic tree based on the amino acid sequence alignments of the complete L gene of all the varicosaviruses reported thus far and in this study. The scale bar indicates the number of substitutions per site. The node labels indicate fast tree support values. Four cytorhabdoviruses were used as outgroups. Right: Genomic organization of the varicosavirus sequences used in the phylogeny. An asterisk and bold font indicate those viruses identified in this study. The accession numbers of all the viruses are listed in Supplementary Table S1 and Table 1.
Figure 1. Left: Maximum-likelihood phylogenetic tree based on the amino acid sequence alignments of the complete L gene of all the varicosaviruses reported thus far and in this study. The scale bar indicates the number of substitutions per site. The node labels indicate fast tree support values. Four cytorhabdoviruses were used as outgroups. Right: Genomic organization of the varicosavirus sequences used in the phylogeny. An asterisk and bold font indicate those viruses identified in this study. The accession numbers of all the viruses are listed in Supplementary Table S1 and Table 1.
Pathogens 11 01127 g001
Figure 2. Pairwise identity matrix of the amino acid sequences of the varicosavirus complete L gene open reading frame generated using SDT v1.2 software [59]. GenBank accession numbers are listed in Supplementary Table S1 and Table 1.
Figure 2. Pairwise identity matrix of the amino acid sequences of the varicosavirus complete L gene open reading frame generated using SDT v1.2 software [59]. GenBank accession numbers are listed in Supplementary Table S1 and Table 1.
Pathogens 11 01127 g002
Figure 3. Tanglegram showing the phylogenetic relationships of the varicosaviruses (left), which are linked with the associated plant host(s) shown on the right. Links of well-supported clades of viruses to taxonomically related plant species are indicated in blue, orange, and green. A maximum likelihood phylogenetic tree of rhabdoviruses was constructed based on the conserved amino acid sequence of the complete L protein. Plant host cladograms were generated in phyloT v.2 based on NCBI taxonomy. Internal nodes represent the taxonomic structure of the NCBI taxonomy database, including species, genus, family, order, subclass, and sub-kingdom. Viruses identified in the present study are shown in bold font. The scale bar indicates the number of substitutions per site.
Figure 3. Tanglegram showing the phylogenetic relationships of the varicosaviruses (left), which are linked with the associated plant host(s) shown on the right. Links of well-supported clades of viruses to taxonomically related plant species are indicated in blue, orange, and green. A maximum likelihood phylogenetic tree of rhabdoviruses was constructed based on the conserved amino acid sequence of the complete L protein. Plant host cladograms were generated in phyloT v.2 based on NCBI taxonomy. Internal nodes represent the taxonomic structure of the NCBI taxonomy database, including species, genus, family, order, subclass, and sub-kingdom. Viruses identified in the present study are shown in bold font. The scale bar indicates the number of substitutions per site.
Pathogens 11 01127 g003
Table 1. Summary of the novel varicosaviruses identified from the plant RNA-seq data available in the NCBI database. The acronyms of the best hits are listed in Supplementary Table S1.
Table 1. Summary of the novel varicosaviruses identified from the plant RNA-seq data available in the NCBI database. The acronyms of the best hits are listed in Supplementary Table S1.
Plant HostTaxa/FamilyVirus Name/AbbreviationBioproject ID/
Data Citation
Segment/Coverage Length (nt)Accession NumberProtein IDLength (aa)Highest Scoring Virus-Protein/E-Value/Query Coverage%/Identity% (Blast P)
Trojan fir (Abies nordmannia) Gymnosperm/PinaceaeAbies virus 1/
AbiV1
PRJNA387306/
University of Connecticut, USA
RNA1/30.97X11,287BK061731N
2
3
4
L
430
420
317
163
2050
PiFleV1-N/9e-130/87/50.79
PiFleV1-P2/2e-18/57/28.05
PiFleV1-P3/2e-103/97/47.44
no hits
PiFleV1-L/0.0/98/52.68
Dwarf mistletoe (Arceuthobium sichuanense)dicot/
Santalaceae
Arceuthobium virus 8/
ArcV8
PRJNA307530/
[23]
RNA1/9.31X
RNA2/72.35X
6628
4149
BK061732
BK061733
L
N
2
3
2013
369
453
159
ASaV2-L/0.0/98/100
ZaVV1-N/1e-34/91/28.36
no hits
no hits
Bei Wu Tou (Aconitum kusnezoffii)dicot/
Ranunculaceae
Aconitum virus 1/
AcoV1
PRJNA670255/
[24]
RNA1/10.16X RNA2/105.03X 6483
5561
BK061734
BK061735
L
N
2
3
4
5
2000
424
329
311
204
297
ZaVV1-L/0.0-97/61.18
ZaVV1-N/2e-115/99/43.82
VVV-P2/4e-36/80/32.13
ZaVV1-P3/5e-105/85/54.51
VVV-P4/1e-27/87/33.33
VVV-P5/5e-17/92/26.18
Catkin yew (Amentotaxus argotaenia)Gymnosperm/
Cephalotaxeae
Amentotaxus virus 1/
AmeV1
PRJNA498605/
[25]
RNA1/109.96X 10,965BK061736N
2
3
4
L
391
431
314
187
2062
ASaV2-N/3e-111/94/45.95
PiFleV1-P2/1e-06/55/26.98
ASaV2-P3/4e-83/94/43.42
no hits
PiFleV1-L/0.0/99/46.16
Common windgrass (Apera spica-venti)monocot/
Poaceae
Apera virus 1/
ApeV1
PRJNA356380/
[26]
RNA1/11.98X
RNA2/110.50X
6516
6552
BK061737
BK061738
L
N
2
3
4
5
2027
447
363
298
196
444
MelRoV1-L/0.0/98/52.12
MelRoV1-N/2e-69/82/34.57
MelRoV1-P2/4e-17/75/26.37
MelRoV1-P3/2e-80/97/41.25
no hits
no hits
Lace plant (Aponogeton madagascariensis)monocot/
Aponogetonaceae
Aponogeton virus 1/
ApoV1
PRJNA591467/
[27]
RNA1/36.42X
RNA2/81.25X
6678
5628
BK061739
BK061740
L
N
2
3
4
2022
435
454
300
174
BrRV1-L/0.0/98/52.7
BrRV1-N/7e-81/88/37
no hits
TfVV-P3/2e-45/96/34
BrRV1-P3/0.003/73/25
Wormwood (Artemisia absinthium)dicot/
Asteraceae
Artemisia virus 1/
ArtV1
PRJNA371565/
[28]
RNA1/33.06X
RNA2/50.30X
7373
4497
BK061741
BK061742
L
N
2
3
2020
453
494
174
BrRV1-L/0.0/98/49.18
BrRV1-N/3e-45/76/28.90
no hits
no hits
Common milkweed (Asclepias syriaca)dicot/
Apocynaceae
Asclepias syriaca virus 3
AscSyV3
PRJNA210776/
[29]
RNA1/37.86X
RNA2/138.94X
6506
6280
BK061743
BK061744
L
N
2
3
4
5
2021
453
370
286
160
393
TfVV-L/0.0/94/42.62
TfVV-N/3e-39/78/32.13
no hits
TfVV-P3/73-32/78/29.26
no hits
no hits
Beautiful tree fern (Asplenium loriceum)Polypodiophyta/
Aspleniaceae
Asplenium virus 1/
AspV1
PRJNA281136/
[30]
RNA1/4.51X
RNA2/8.91X
6287 *
4371 *
BK061745
BK061746
L
N
2
3
4
1957 *
396
490
294
127 *
TfVV-L/0.0/98/43.81
TfVV-N/2e-79/90/37.82
no hits
TfVV-P3/1e-45/87/33.33
no hits
Shortpod mustard (Brassica incanadicot/
Brassicaceae
Brassica virus 2_Inc/
BrV2_Inc
PRJNA428769/
[31]
RNA1/11.89X
RNA2/14.63X
6316
5616
BK061747
BK061748
L
N
2
3
4
2032
591
459
282
141
TfVV-L/0.0/99/41.86
LoPV1-N/1e-31/58/27.93
no hits
TfVV-P3/9e-33/91/29.32
no hits
Indian mustard (Brassica juncea var. rugosa)dicot/
Brassicaceae
Brassica virus 2_Jun/
BrV2_Jun
PRJNA290942/
[32]
RNA1/80.91X
RNA2/950.63X
6316
5537
BK061749
BK061750
L
N
2
3
4
2032
591
459
282
141
TfVV-L/0.0/99/41.57
LoPV1-N/6e-31/58/27.65
no hits
TfVV-P3/1e-32/91/29.32
no hits
Chinese kale
(Brassica oleracea var. alboglabra)
dicot/
Brassicaceae
Brassica virus 2_Ole/
BrV2_Ole
PRJNA525713/
[33]
RNA1/11.03X
RNA2/66.34X
6316
5647
BK061751
BK061752
L
N
2
3
4
2032
591
459
282
141
TfVV-L/0.0/99/41.81
LoPV1-N/7e-32/58/27.93
no hits
TfVV-P3/8e-33/91/29.32
no hits
Crab-lipped spider orchid (Caladenia plicata)monocot/
Orchidaceae
Caladenia virus 1/
CalV1
PRJNA384875/
[34]
RNA1/10.51X
RNA2/52.44X
6454
5011
BK061755
BK061756
L
N
2
3
4
2024
449
468
293
165
BrRV1-L/0.0/98/50.17
BrRV1-N/1e-64/97/32.43
no hits
TfVV-P3/1e-43/86/34.78
BrRV1-P3/3e-07/61/31.13
Conrflower
(Centaurea cyanus)
dicot/
Asteraceae
Centaurea virus 1/
CenV1
PRJNA371565/
[28]
RNA1/63.11X
RNA2/159.93X
6789
4567
BK061757
BK061758
L
N
2
3
2019
469
501
111
BrRV1-L/0.0/98/50.50
BrRV1-N/6e-48/73/30.72
no hits
no hits
Chamomile (Chamaemelum nobile)dicot/
Asteraceae
Chamaemelum virus 1/
ChaV1
PRJNA382469/
[35]
RNA1/21.33X
RNA2/234.84X
6670 *
5957
BK061759
BK061760
L
P6
N
2
3
4
5
1916 *
171
426
346
305
255
330
VVV-L/0.0/99/58.85
no hits
ZaVV1-N/2e-105/95/41.40
VVV-P2/2e-19/84/30.28
VVV-P3/5e-97/94/49.14
ZaVV1-P4/3e-05/70/22.1
VVV-P5/3e-22/85/29.14
Melon (Cucumis melo)dicot/
Cucurbitaceae
Cucumis virus 1/
CucV1
PRJNA381300/
[36]
RNA1/47.79X
RNA2/60.05X
6919
5322
BK061761
BK061762
L
N
2
3
4
2034
341
404
285
119
AMVV1-L/0.0/99/47.47
InPRV-N/4e-77/98/38.71
no hits
TfVV-P3/1e-46/91/34.21
no hits
Chen cypress (Cupressus chengiana)Gymnosperm/
Cupressaceae
Cupressus virus 1/
CupV1
PRJNA556937/
[37]
RNA1/32.13X12143BK061763N
2
3
4
5
L
379
447
313
187
168
2055
ASaV2-N/2e-106/97/44.59
ASaV2-P2/5e-30/67/30.86
ASaV2-P3/2e-100/84/53.38
no hits
no hits
PiFleV1-L/0.0/99/48.68
Tree maidenhair fern (Didymochlaena truncatula) Polypodiophyta/
Hypodeatiaceae
Didymochlaena virus 1/
DidV1
PRJNA422112/
[38]
RNA1/8.88X
RNA2/52.28X
6319
5924
BK061764
BK061765
L
N
2
3
4
5
2044
386
394
292
187
374
TfVV-L/0.0/100/74.17
TfVV-N/0.0/100/72.75
TfVV-P2/7e-74/96/40.26
TfVV-P3/2e-159/99/70.69
TfVV-P4/5e-23/88/30.72
TfVV-P5/0.0/97/64.11
Wallflower (Erysimum bastetanum)dicot/
Brassicaceae
Erysimum virus 1/
EryV1
PRJNA607615/
[39]
RNA1/271.24X
RNA2/516.22X
6676
3980
BK061766
BK061767
L
N
2
3
1985
439
404
172
BrRV1-L/0.0/99/62-34
BrRV1-N/3e-90/99/33.86
no hits
BrRV1-P3/4e-26/100/31.4
Liverwort (Frullania orientalis)Marchantiophyta/
Frullaniaceae
Frullania virus 1/
FruV1
PRJNA505755/
Fairylake Botanical Garden, China
RNA1/11.60X
RNA2/8.20X
6458
4363
BK061768
BK061769
L
N
2
3
4
2033
372
336
289
148
MgVV-L/0.0/98/54.77
MgVV-N/2e-94/97/43.96
MgVV-P2/8e-05/56/27.27
MgVV-P3/5e-85/89/47.49
MgVV-P4/4e-05/70/29.81
Noug (Guizotia abyssinica)dicot/
Asteraceae
Guizotia virus 1/
GuiV1
PRJNA371565/
[28]
RNA1/153.49X
RNA2/1192.66X
6457
4722
BK061770
BK061771
L
N
2
3
4
2007
434
340
262
307
MelRoV1-L/0.0/98/60.42
MelRoV1-N/3e-103/82/43.96
MelRoV1-P2/7e-22/85/24.53
no hits
no hits
Common velvet grass (Holcus lanatus)monocot/
Poaceae
Holcus virus 1/
HolV1
PRJEB11654/
[40]
RNA1/19.48X
RNA2/29.44X
6571
4397
BK061772
BK061773
L
N
2
3
4
2031
476
286
211
161
AMVV1-L/0.0/98/65.12
LoPV1-N/8e-132/77/51.23
LoPV1-P2/5e-23/56/33.33
LoPV1-P2/8e-12/63/29.76
LoPV1-P3/1e-49/90/51.72
Oxeye daisy (Leucanthemum vulgare) dicot/
Asteraceae
Leucanthemum virus 1/
LeuV1
PRJNA371565/
[28]
RNA1/141.76X
RNA2/229.85X
6763
4775
BK061774
BK061775
L
N
2
3
2021
448
520
167
BrRV1-L/0.0/98/49.63
BrRV1-N/3e-42/71/32.11
no hits
no hits
Downy flax
(Linum hirsutum)
dicot/
Linaceae
Linum virus 1/
LinV1
PRJEB21674/
1000 Plant (1KP) Transcriptomes Initiative
RNA1/26.47X
RNA2/119.90X
5999 *
6330
BK061776
BK061777
L
N
2
3
4
1940 *
450
463
313
260
MelRoV1-L/0.0/94/53.78
MelRoV1-/3e-69/82/33.96
no hits
MelRoV1-P3/7e-81/88/42.39
no hits
Sponge gourd (Luffa aegyptiaca)dicot/
Cucurbitaceae
Luffa virus 1/
LufV1
PRJNA390566/
Mylne, J., The University of Western Australia
RNA1/16.47X
RNA2/11.32X
6693
4961
BK061780
BK061781
L
N
2
3
4
2032
487
366
286
126
LoPV1-L/0.0/99/49.04
InPRV-N/7e-84/86/36.93
no hits
TfVV-P3/3e-53/81/41.7
no hits
Riverbank lupine (Lupinus rivularis)dicot/
Fabaceae
Lupinus virus 1/
LupV1
PRJNA318864/
[41]
RNA1/14.64X
RNA2/97.57X
6688
4042 *
BK061782
BK061783
L
N
2
3
1997
426
497
116 *
ZaVV1-L/0.0/99/56.91
ZaVV1-N/2e-83/99/36.92
ZaVV1-P2/3e-14/39/28.99
no hits
Sweet clover (Melilotus spp)dicot/
Fabaceae
Melilotus virus 1_Alb/
MelV1_Alb
PRJNA647665/
[42]
RNA1/30.69X
RNA2/98.21X
6657
3985
BK061784
BK061785
L
N
2
3
2019
430
393
189
RCaVV-L/0.0/99/64.97
RCaVV-N/5e-80/93/33.5
RCaVV-P2/0.001/42/27.54
RCaVV-P3/8e-25/88/35.12
Sweet clover (Melilotus spp)dicot/
Fabaceae
Melilotus virus 1_Off/
MelV1_Off
PRJNA751393/
[43]
RNA1/12.15X
RNA2/25.36X
6433
3781
BK061786
BK061787
L
N
2
3
2019
430
399
191
RCaVV-L/0.0/99/65.37
RCaVV-N/5e-77/91/33.33
RCaVV-P2/0.002/42/28.14
RCaVV-P3/5e-23/87/34.52
Early spider orchid (Ophrys sphegodes)monocot/
Orchidaceae
Ophrys virus 1/
OphV1
PRJNA574279/
[44]
RNA1/7.72X
RNA2/206.15X
6134 *
5036
BK061788
BK061789
L
N
2
3
4
1988 *
447
466
293
214
MelRoV1-L/0.0/99/56.95
MelRoV1-N/4e-97/96/37.1
MelRoV1-P2/4e-23/54/28.9
MelRoV1-P3/2e-84/91/43.87
MelRoV1-P4/0.009/63/26.39
Purple Grass (Pennisetum violaceum)monocot/
Poaceae
Pennisetum virus 1/
PenV1
PRJNA282366/
Suja George,
M.S Swaminathan Research Foundation, India
RNA1/44.59X
RNA2/112.25X
6284
3407
BK061790
BK061791
L
N
2
3
2033
451
286
151
LoPV1-L/0.0/98/51.27
LoPV1-N/5e-79/75/40.52
no hits
LoPV1-P3/4e-12/83/30.16
Qinghai spruce (Picea crassifolia)Gymosperm/
Pinaceae
Picea virus 1/
PicV1
PRJNA307530/
[23]
RNA1/5.86X11,193BK061792N
2
3
4
L
382
452
318
174
2051
ASaV2-N/0.0/100/100
ASaV2-P2/0.0/100/100
ASaV2-P3/0.0/100/100
ASaV2-P4/0.0/100/100
PiFleV1-L/0.0/99/49.12
Jack pine (Pinus banksiana)Gymosperm/
Pinaceae
Pinus banksiana virus 1/
PiBanV1
PRJNA524866/
[45]
RNA1/97.66X11276BK061793N
2
3
4
L
406
433
317
175
2048
PiFleV1-N/0.0/100/68.72
PiFleV1-P2/3e-48/57/39.2
PiFleV1-P3/1e-161/100/64.78
PiFleV1-P4/3e-17/65/36.84
PiFleV1-L/0.0/99/65.35
Yunnan pine (Pinus yunnanensis)Gymosperm/
Pinaceae
Pinus yunnanensis virus 1/PiYunV1PRJNA507489/
[46]
RNA1/36.47X12,057BK061794N
2
3
4
L
411
440
319
204
2048
PiFleV1-N/0.0/93/70.5
PiFleV1-P2/7e-48/97/35.49
PiFleV1-P3/8e-145/100/62.38
PiFleV1-P4/7e-30/75/38.46
PiFleV1-L/0.0/98/70.33
Spendlor primrose (Primula oreodoxa)dicot/
Primulaceae
Primula virus 1/
PriV1
PRJNA544868/
[47]
RNA1/7.72X
RNA2/149.23X
6352
6283
BK061795
BK061796
L
N
2
3
4
5
2022
435
352
288
145
384
TfVV-L/0.0/98/42.3
TfVV-N/1e-40/74/33.33
no hits
TfVV-P3/2e-28/75/29.55
no hits
no hits
Goldilocks buttercup (Ranunculus auricomus)dicot/
Ranunculaceae
Ranunculus virus 1/
RanV1
PRJNA217403/
[48]
RNA1/29.64X
RNA2/163.27X
6481
6269
BK061797
BK061798
L
N
2
3
4
5
2034
529
438
307
200
330
MelRoV1-L/0.0/98/49.85
MelRoV1-N/2e-65/63/34.63
MelRoV1.P2/4e-08/26/27.83
ZaVV1-P3/2e-59/79/42.86
no hits
no hits
Radish
(Raphanus sativus)
dicot/
Brassicaceae
Raphanus virus 1/
RapV1
PRJNA539856/
[49]
RNA1/165.02X
RNA2/521.73X
6410
4144
BK061799
BK061800
L
N
2
3
2016
439
411
175
BrRV1-L0.0/99/68.31
BrRV1-N/1e-135/100/46.94
BrRV1-P2/5e-14/61/28.57
BrRV1-P3/6e-34/98/37.5
Siberian currant (Ribes diacanthum)dicot/
Grossulariaceae
Ribes virus 1/
RibV1
PRJNA407394/
[50]
RNA1/6.29X
RNA2/33.97X
6323
5201
BK061801
BK061802
L
N
2
3
4
2017
372
402
301
194
SpV1-L/0.0/98/47.29
TfVV-N/1e-60/90/36.01no hits
TfVV-P3/2e-45/82/33.33
no hits
Japanese umbrella pine
(Sciadopitys verticillata)
Gymnosperm/
Sciadopityaceae
Sciadopitys virus 1_Chi/
SciV1_Chi
PRJNA396655/
Institute of Botany, CAS, China
RNA1/98.99X11,224BK061803N
2
3
4
L
389
466
315
168
2054
ASaV2-N/1e-111/95/43.13
ASaV2-P2/1e-22/60/30.14
ASaV2-P3/4e-104/95/48.23
PiFleV1-P4/3e-05/67/26.32
PiFleV1-L/0.0/99/46.13
Japanese umbrella pine
(Sciadopitys verticillata)
Gymnosperm/
Sciadopityaceae
Sciadopitys virus 1_Can/
SciV1_Can
PRJEB4921/
[51]
RNA1/14.02X11,132BK061804N
2
3
4
L
389
466
314
168
2071
ASaV2-N/1e-111/95/43.67
ASaV2-P2/8e-22/60/29.87
ASaV2-P3/2e-105/95/48.23
PiFleV1-P4/7e-07/80/25.93
PiFleV1-L/0.0/99/45.88
Wooly grassland senecio (Senecio coronatus) dicot/
Asteraceae
Senecio virus 1/
SenV1
PRJNA312157/
[52]
RNA1/10.59X
RNA2/93.61X
6173 *
5617
BK061805
BK061806
L
N
2
3
4
5
2031 *
376
345
294
147
370
LBVaV-L/0.0/98/42.8
PhPV1/2e-132/98/51.98
no hits
PhPV1-P3/9e-124/87/56.64
no hits
XVV-L/2e-08/29/30
Bladder campion (Silene vulgaris)dicot/
Caryophyllaceae
Silene virus 1/
SilV1
PRJNA104951/
[53]
RNA1/29.59X
RNA2/77.05X
6391
4363
BK061807
BK061808
L
N
2
3
2019
445
509
179
SpV1-0.0/99/59.91
SpV1-N/4e-65/91/33.99
SpV1-P2/2e-13/61/24.07
BrRV1-P3/0.001/97/24.29
Broadhead daisy (Streptoglossa macrocephala)dicot/
Asteraceae
Streptoglossa virus 1/
StrV1
PRJNA371565/
[28]
RNA1/131.33X
RNA2/140.03X
6776
5130
BK061813
BK061814
L
N
2
3
4
2023
449
333
287
162
LoPV1-L/0.0/99/49.09
InPRV-N3e-86/99/36.01
no hits
PhPV1-P3/2e-43/91/32.2
no hits
Tansy
(Tanacetum vulgare)
dicot/
Asteraceae
Tanacetum virus 1/
TanV1
PRJNA646340/
[54]
RNA1/10.19X
RNA2/239.11X
6888
4608
BK061815
BK061816
L
N
2
3
2020
447
505
176
BrRV1-L/0.0/98/49.03
BrRV1-L/8e-52/88/30.56
no hits
RCaVV-P3/3e-05/73/30.60
Hybrid yew
(Taxus media)
Gymnosperm/
Taxaceae
Taxus virus 1/
TaxV1
PRJNA497542/
[55]
RNA1/57.28X11,174BK061817N
2
3
4
L
382
417
310
201
2057
ASaV2-N/7e-111/96/43.55
ASaV2-P2/1e-18/68/26.28
ASaV2-P3/3e-94/93/45.25
no hits
PiFleV1-L/0.0/98/46.81
Chinese nutmeg yew (Torreya grandis)Gymnosperm/
Taxaceae
Torreya virus 1/
TorV1
PRJNA498605
[25]
RNA1/59.04X10,253BK061818N
2
3
4
L
379
339
283
152
2002
TfVV-N/2e-57/93/32.5
no hits
TfVV-P3/4e-28-67/36.27
no hits
TfVV-L/0.0/97/35.4
Liverwort
(Treubia lacunosa)
Marchantiophyta/
Treubiaceae
Treubia virus 1/
TreV1
PRJNA505755/
Fairylake Botanical Garden, China
RNA1/364.20X
RNA2/350.53X
6684
4940
BK061819
BK061820
L
N
2
3
4
2040
392
395
288
153
TfVV-L/0.0/99/54.2
TfVV-N/3e-116/99/46.27
TfVV-P2/0.015/56/24.34
TfVV-P31e-114/85/55.07
no hits
Wheat
(Triticum aestivum)
monocot/
Poaceae
Triticum virus 1/
TriV1
PRJNA558380/
[56]
RNA1/10.25X
RNA2/16.64X
6290
4103
BK061821
BK061822
L
N
2
3
2019
430
451
179
RCaVV-L/0.0/99/72.58
RCaVV-N/8e-135/99/46.26
RCaVV-P2/2e-32/67/30.70
RCaVV-P3/1e-48/100/44.13
Variegated swallow-wort (Vincetoxicum versicolor)dicot/
Apocynaceae
Vincetoxicum virus 1/
VinV1
PRJNA599262/
[57]
RNA1/56.05X
RNA2/140.76X
6598
4655
BK061823
BK061824
L
N
2
3
4
2037
430
356
307
174
MelRoV1-L/0.0/99/48.19
ZaVV1-N/7e-63/76/35
MelRoV1-P2/2e-08/68/21.15
MelRoV1-P3/63-51/80/36.44
no hits
Corn (Zea mays)monocot/
Poaceae
Zea virus 1/
ZeaV1
PRJNA407369/
[58]
RNA1/6.25X
RNA2/40.88X
6345
4607
BK061825
BK061826
L
N
2
3
4
2037
483
353
286
158
AMVV1-L/0.0/99/49.07
AMVV1-N/2e-90/76/40.92
LoPV1-P2/4e-08/63/24.89
TfVV-P3/6e-48/94/31.11
LoPV1-P3/1e-09/86/29.2
* partial sequence.
Table 2. Consensus varicosavirus gene junction sequences.
Table 2. Consensus varicosavirus gene junction sequences.
Virus *3′ end mRNAIntergenic Spacer5′ end mRNA
AbiV1CU(N)5UUUUUGCUCU
ArcV8AU(N)5UUUUUGCUCU
AcoV1AU(N)5UUUUUGCUCU
AmeV1CU(N)5UUUUUGCUCU
ApeV1AU(N)5UUUUUGCUCU
ApoV1AU(N)5UUUUUGCUCU
ArtV1AU(N)5UUUUUGCUCU
AscSyV3AU(N)5UUUUUGCUCU
AspV1AU(N)5UUUUUGCUCU
BrV2AU(N)5UUUUUGCUCU
CalV1AU(N)5UUUUUGCUCU
CenV1AU(N)5UUUUUGCUCU
ChaV1AU(N)5UUUUUGCUCU
CucV1AU(N)5UUUUUGCUCU
CupV1CU(N)5UUUUUGCUCU
DidV1AU(N)5UUUUUGCUCU
EryV1AU(N)5UUUUUGCUCU
FruV1AU(N)5UUUUUGCUCU
GuiV1AU(N)5UUUUUGCUCU
HolV1AU(N)5UUUUUGCUCU
LeuV1AU(N)5UUUUUGCUCU
LinV1AU(N)5UUUUUGCUCU
LufV1AU(N)5UUUUUGCUCU
LupV1AU(N)5UUUUUGCUCU
MelV1AU(N)5UUUUUGCUCU
OphV1AU(N)5UUUUUGCUCU
PenV1AU(N)5UUUUUGCUCU
PicV1CU(N)5UUUUUGCUCU
PiBanV1CU(N)5UUUUUGCUCU
PiYunV1CU(N)5UUUUUGCUCU
PriV1AU(N)5UUUUUGCUCU
RanV1AU(N)5UUUUUGCUCU
RapV1AU(N)5UUUUUGCUCU
RibV1AU(N)5UUUUUGCUCU
SciV1CU(N)5UUUUUGCUCU
SenV1AU(N)5UUUUUGCUCU
SilV1AU(N)5UUUUUGCUCU
StrV1AU(N)5UUUUUGCUCU
TanV1AU(N)5UUUUUGCUCU
TaxV1CU(N)5UUUUUGCUCU
TorV1AU(N)5UUUUUGCUCU
TreV1AU(N)5UUUUUGCUCU
TriV1AU(N)5UUUUUGCUCU
VinV1AU(N)5UUUUUGCUCU
ZeaV1AU(N)5UUUUUGCUCU
AAnV1AU(N)5UUUUUGCUCU
AMVV1AU(N)5UUUUUGCUCU
BrV1AU(N)5UUUUUGCUCA
LBVaVAU(N)5UUUUUGCUCU
LoV1AU(N)5UUUUUGCUCU
MelRoV1AU(N)5UUUUUGCUCU
MGVVAU(N)5UUUUUGCUCU
MgVVAU(N)5UUUUUGCUCU
PhPiV1AU(N)5UUUUUGCUCU
PiFleV1GU(N)5UUUUUGCUCU
RCaVVAU(N)5UUUUUGCUCU
SpV1AU(N)5UUUUUGCUCU
TfVVAU(N)5UUUUUGCUCU
VVVAU(N)5UUUUUGCUCU
XVVAU(N)5UUUUUGCUCU
ZaVV1AU(N)5UUUUUGCUCU
The consensus gene junction sequences of the viruses identified in this study are highlighted in light grey. * Names and abbreviations of newly identified viruses are listed in Table 1; while the names and abbreviations of known viruses are listed in Supplementary Table S1.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Bejerman, N.; Dietzgen, R.G.; Debat, H. Unlocking the Hidden Genetic Diversity of Varicosaviruses, the Neglected Plant Rhabdoviruses. Pathogens 2022, 11, 1127. https://doi.org/10.3390/pathogens11101127

AMA Style

Bejerman N, Dietzgen RG, Debat H. Unlocking the Hidden Genetic Diversity of Varicosaviruses, the Neglected Plant Rhabdoviruses. Pathogens. 2022; 11(10):1127. https://doi.org/10.3390/pathogens11101127

Chicago/Turabian Style

Bejerman, Nicolas, Ralf G. Dietzgen, and Humberto Debat. 2022. "Unlocking the Hidden Genetic Diversity of Varicosaviruses, the Neglected Plant Rhabdoviruses" Pathogens 11, no. 10: 1127. https://doi.org/10.3390/pathogens11101127

APA Style

Bejerman, N., Dietzgen, R. G., & Debat, H. (2022). Unlocking the Hidden Genetic Diversity of Varicosaviruses, the Neglected Plant Rhabdoviruses. Pathogens, 11(10), 1127. https://doi.org/10.3390/pathogens11101127

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop