Identification of Trichosanthes associated rhabdovirus 1, a novel member of the genus Cytorhabdovirus of the family Rhabdoviridae, in the Trichosanthes kirilowii transcriptome

Goh, Chul Jun; Park, D; Hahn, Yoonsoo

doi:10.4149/av_2020_105

Cited by 13 publications

(12 citation statements)

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“…Thus, it is tempting to speculate that some plant rhabdovirus-like sequences may be hidden in published plant transcriptome databases, generated with diverse objectives beyond virus research, where viral RNA was inadvertently copurified with endogenous plant RNA and sequenced. To prove this point, we and others have previously identified the sequences of a small number of plant rhabdoviruses contained in public transcriptome databases [ 8 , 9 , 16 ]; however, an extensive search has not been conducted to date. Therefore, we queried the publicly available plant transcriptome datasets in the transcriptome shotgun assembly (TSA) database hosted at NCBI, which resulted in the identification of 27 novel plant rhabdoviruses.…”

Section: Discussionmentioning

confidence: 99%

“…The scientific interest of the submitters of transcriptome datasets is often limited to a narrow objective within their specific field of study, which leaves a large amount of potentially valuable data not analyzed [ 7 ]. In such transcriptome datasets, viral sequences may be hidden in plain sight; thus, their analysis has become a valuable tool for the discovery of novel viral sequences [ 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 ]. In a recent consensus statement report, Simmonds and colleagues [ 17 ] contended that viruses that are known only from metagenomic data can, should and have been incorporated into the official classification scheme overseen by the International Committee on Taxonomy of Viruses (ICTV).…”

Section: Introductionmentioning

confidence: 99%

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Illuminating the Plant Rhabdovirus Landscape through Metatranscriptomics Data

Bejerman

Dietzgen

Debat

2021

Viruses

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Rhabdoviruses infect a large number of plant species and cause significant crop diseases. They have a negative-sense, single-stranded unsegmented or bisegmented RNA genome. The number of plant-associated rhabdovirid sequences has grown in the last few years in concert with the extensive use of high-throughput sequencing platforms. Here, we report the discovery of 27 novel rhabdovirus genomes associated with 25 different host plant species and one insect, which were hidden in public databases. These viral sequences were identified through homology searches in more than 3000 plant and insect transcriptomes from the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) using known plant rhabdovirus sequences as the query. The identification, assembly and curation of raw SRA reads resulted in sixteen viral genome sequences with full-length coding regions and ten partial genomes. Highlights of the obtained sequences include viruses with unique and novel genome organizations among known plant rhabdoviruses. Phylogenetic analysis showed that thirteen of the novel viruses were related to cytorhabdoviruses, one to alphanucleorhabdoviruses, five to betanucleorhabdoviruses, one to dichorhaviruses and seven to varicosaviruses. These findings resulted in the most complete phylogeny of plant rhabdoviruses to date and shed new light on the phylogenetic relationships and evolutionary landscape of this group of plant viruses. Furthermore, this study provided additional evidence for the complexity and diversity of plant rhabdovirus genomes and demonstrated that analyzing SRA public data provides an invaluable tool to accelerate virus discovery, gain evolutionary insights and refine virus taxonomy.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Illuminating the Plant Rhabdovirus Landscape through Metatranscriptomics Data

Bejerman

Dietzgen

Debat

2021

Viruses

View full text Add to dashboard Cite

show abstract

“…Thus, it is tempting to speculate that some plant rhabdovirus-like sequences may be hidden in published plant transcriptome databases, generated with diverse objectives beyond virus research, where viral RNA was inadvertently co-purified with endogenous plant RNA and sequenced. To prove this point, we and others have previously identified the sequences of a small number of plant rhabdoviruses contained in public transcriptome databases (Debat and Bejerman, 2019; Goh et al, 2020; Sidharthan and Balanwan, 2021); however an extensive search has not been conducted to date. Therefore, we queried the publicly available plant transcriptome datasets at the transcriptome shotgun assembly (TSA) database hosted at NCBI which resulted in the identification of 26 novel plant rhabdoviruses.…”

Section: Discussionmentioning

confidence: 99%

“…The scientific interest of the submitters of transcriptome datasets is often limited to a narrow objective within their specific field of study, which leaves a large amount of potentially valuable data not analyzed (Bejerman et al, 2020b). In such transcriptome datasets, viral sequences may be hidden in plain sight, thus their analysis has become a valuable tool for the discovery of novel viral sequences (Debat and Bejerman, 2019; Goh et al, 2020; Jiang et al, 2019; Kim et al, 2018; Lauber et al, 2019; Longdon et al, 2015; Mushegian et al, 2016; Nibert et al, 2018: Sidharthan and Baranwal, 2021). In a recent consensus statement report, Simmonds and colleagues (2017) contend that viruses that are known only from metagenomic data can, should, and have been incorporated into the official classification scheme overseen by the International Committee on Taxonomy of Viruses (ICTV).…”

Section: Introductionmentioning

confidence: 99%

Illuminating the plant rhabdovirus landscape through metatranscriptomics data

Bejerman

Dietzgen

Debat

2021

Preprint

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Rhabdoviruses infect a large number of plant species and cause significant crop diseases. They have a negative-sense, single-stranded unsegmented or bisegmented RNA genome. The number of plant-associated rhabdovirid sequences has grown in the last few years in concert with the extensive use of high-throughput sequencing platforms. Here we report the discovery of 26 novel rhabdovirus genomes associated with 24 different host plant species and one insect, which were hidden in public databases. These viral sequences were identified through homology searches in more than 3,000 plant and insect transcriptomes from the NCBI Sequence Read Archive (SRA) using known plant rhabdovirus sequences as query. Identification, assembly and curation of raw SRA reads resulted in sixteen viral genome sequences with full-length coding regions and ten partial genomes. Highlights of the obtained sequences include viruses with unique and novel genome organizations among known plant rhabdoviruses. Phylogenetic analysis showed that thirteen of the novel viruses were related to cytorhabdoviruses, one to alphanucleorhabdoviruses, five to betanucleorhabdoviruses, one to dichorhaviruses, and six to varicosaviruses. These findings resulted in the most complete phylogeny of plant rhabdoviruses to date and shed new light on the phylogenetic relationships and evolutionary landscape of this group of plant viruses. Furthermore, this study provides additional evidence for the complexity and diversity of plant rhabdovirus genomes and demonstrates that analyzing SRA public data provides an invaluable tool to accelerate virus discovery, gain evolutionary insights and refine virus taxonomy.

show abstract

“…The negative-sense RNA genomes of rhabdoviruses are used as templates for the transcription of viral gene mRNAs that are translated into proteins (Jackson et al, 2005;Walker et al, 2011). There are conserved regulatory elements in the gene-junction regions of rhabdoviruses, which are responsible for transcription termination/polyadenylation (TTP) of the preceding gene and transcription initiation (TI) of the following gene (Jackson et al, 2005;Goh et al, 2020;Zhou et al, 2020). The TTP and TI elements are separated by an untranscribed spacer that is one or several nucleotides (nt) in length (Goh et al, 2020;Orfanidou et al, 2020;Zhou et al, 2020).…”

Section: Introductionmentioning

confidence: 99%