Evidence map›Paper›PMID 30039318›Full record

ReviewArchives of virology2018

Virus classification - where do you draw the line?

Peter Simmonds, Pakorn Aiewsakun

Abstract readReview
In one paragraph

Review in Archives of virology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed
–field-weighted citation impact
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

56 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Review
  8. Review
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Review
  17. Article
  18. Article
  19. Review
  20. 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

2 authors.

Peter SimmondsNuffield Department of Medicine, University of Oxford, Peter Medawar Building, South Parks Road, Oxford, OX1 3SY, UK. Peter.Simmonds@ndm.ox.ac.uk.
Pakorn AiewsakunNuffield Department of Medicine, University of Oxford, Peter Medawar Building, South Parks Road, Oxford, OX1 3SY, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High-throughput sequencing (HTS) and its use in recovering and assembling novel virus sequences from environmental, human clinical, veterinary and plant samples has unearthed a vast new catalogue of viruses. Their classification, known by their sequences alone, sets a major challenge to traditional virus taxonomy, especially at the family and species levels, which have been historically based largely on descriptive taxon definitions. These typically entail some knowledge of their phenotypic properties, including replication strategies, virion structure and clinical and epidemiological features, such as host range, geographical distribution and disease outcomes. Little to no information on these attributes is available, however, for viruses identified in metagenomic datasets. If such viruses are to be included in virus taxonomy, their assignments will have to be guided largely or entirely by metrics of genetic relatedness. The immediate problem here is that the International Committee on Taxonomy of Viruses (ICTV), an organisation that authorises the taxonomic classification of viruses, provides little or no guidance on how similar or how divergent viruses must be in order to be considered members of new species or new families. We have recently developed a method for scoring genomic (dis)similarity between viruses (Genome Relationships Applied to Virus Taxonomy - GRAViTy) among the eukaryotic and prokaryotic viruses currently classified by the ICTV. At the family and genus levels, we found large-scale consistency between genetic relationships and their taxonomic assignments for eukaryotic viruses of all genome configurations and genome sizes. Family assignments of prokaryotic viruses have, however, been made at a quite different genetic level, and groupings currently classified as sub-families are a much better match to the eukaryotic virus family level. These findings support the ongoing reorganisation of bacteriophage taxonomy by the ICTV Phage Study Group. A rapid and objective means to explore metagenomic viral diversity and make evidence-based assignments for such viruses at each taxonomic layer is essential. Analysis of sequences by GRAViTy provides evidence that family (and genus) assignments of currently classified viruses are largely underpinned by genomic relatedness, and these features could serve as a guide towards an evidence-based classification of metagenomic viruses in the future.

Indexed as

AnimalsBacteriophagesGenome, ViralHumansPhylogenyVirus DiseasesViruses

Identifiers

PMID30039318
PMCPMC6096723

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.