Evidence map›Paper›PMID 30016225›Full record

ArticleThe Journal of general virology2018

Evaluation of the genomic diversity of viruses infecting bacteria, archaea and eukaryotes using a common bioinformatic platform: steps towards a unified taxonomy.

Pakorn Aiewsakun, Evelien M Adriaenssens, Rob Lavigne, Andrew M Kropinski, Peter Simmonds

Open access · hybridAbstract read
In one paragraph

Article in The Journal of general virology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers.

0numbers the graph read from it
0cells of the map it votes in
59citing papers in PubMed
12.3field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

59 citing papers in PubMed, 110 citations in OpenAlex.

  1. Article
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  8. Article
  9. Article
  10. Article
  11. Review
  12. Genetic diversity ofFrontiers in cellular and infection microbiology · 2025
    Article
  13. GRAViTy-V2: a grounded viral taxonomy application.NAR genomics and bioinformatics · 2024
    Article
  14. Review
  15. Article
  16. Novel metagenomics analysis of stony coral tissue loss disease.bioRxiv : the preprint server for biology · 2024
    Article
  17. Article
  18. Efficient Recovery of Complete Gut Viral Genomes by Combined Short- and Long-Read Sequencing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Article
  19. Article
  20. Characterization and genomic analysis of a lyticFrontiers in microbiology · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 5 institutions in 4 countries.

Pakorn Aiewsakun1​Nuffield Department of Medicine, University of Oxford, Peter Medawar Building, South Parks, Oxford, OX1 3SY, UK.
Evelien M Adriaenssens3​Institute of Integrative Biology, University of Liverpool, Biosciences Building, Crown Street, L69 7ZB Liverpool, UK.
Rob Lavigne4​Department of Biosystems, Laboratory of Gene Technology, KU Leuven. Kasteelpark Arenberg 21, Box 2462, 3001 Leuven, Belgium.
Andrew M Kropinski5​Departments of Food Science, and Pathobiology, University of Guelph, 50 Stone Rd E, Guelph, ON, N1G 2W1, Canada.
Peter Simmonds1​Nuffield Department of Medicine, University of Oxford, Peter Medawar Building, South Parks, Oxford, OX1 3SY, UK.
KU Leuven · BEMahidol University · THMedawar Building for Pathogen Research · GBUniversity of Guelph · CAUniversity of Liverpool · GB

Funding

Wellcome TrustWellcome Trust WT108418AIA
6 · The paper itself

Abstract

Genome Relationship Applied to Virus Taxonomy (GRAViTy) is a genetics-based tool that computes sequence relatedness between viruses. Composite generalized Jaccard (CGJ) distances combine measures of homology between encoded viral genes and similarities in genome organizational features (gene orders and orientations). This scoring framework effectively recapitulates the current, largely morphology and phenotypic-based, family-level classification of eukaryotic viruses. Eukaryotic virus families typically formed monophyletic groups with consistent CGJ distance cut-off dividing between and within family divergence ranges. In the current study, a parallel analysis of prokaryotic virus families revealed quite different sequence relationships, particularly those of tailed phage families (Siphoviridae, Myoviridae and Podoviridae), where members of the same family were generally far more divergent and often not detectably homologous to each other. Analysis of the 20 currently classified prokaryotic virus families indeed split them into 70 separate clusters of tailed phages genetically equivalent to family-level assignments of eukaryotic viruses. It further divided several bacterial (Sphaerolipoviridae, Tectiviridae) and archaeal (Lipothrixviridae) families. We also found that the subfamily-level groupings of tailed phages were generally more consistent with the family assignments of eukaryotic viruses, and this supports ongoing reclassifications, including Spounavirinae and Vi1virus taxa as new virus families. The current study applied a common benchmark with which to compare taxonomies of eukaryotic and prokaryotic viruses. The findings support the planned shift away from traditional morphology-based classifications of prokaryotic viruses towards a genome-based taxonomy. They demonstrate the feasibility of a unified taxonomy of viruses into which the vast body of metagenomic viral sequences may be consistently assigned.

Indexed as

Genetic VariationGenome, ViralArchaeaArchaeal VirusesBacteriaBacteriophagesComputational BiologyEukaryotaGenes, ViralGenomicsMetagenomicsPhylogenyVirusesbacteriophageBaltimore classificationeukaryotehidden Markov modelmetagenomicprokaryotetaxontaxonomyvirusvirus classification

Identifiers

PMID30016225
PMCPMC6230767
OpenAlexW2883002901

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.