Taxonomy of viruses

Taxonomy of Viruses☆
AE Gorbalenya, Leiden University Medical Center, Leiden, The Netherlands; Lomonosov Moscow State University, Moscow, Russia
C Lauber, University of Technology Dresden, Dresden, Germany
S Siddell, University of Bristol, Bristol, United Kingdom
© 2019 Elsevier Inc. All rights reserved.
Introduction
A Short History of Virology From the Perspective of Virus Taxonomy
Virus Taxonomy and the ICTV
ICTV Resources
The ICTV Database, Website and Master Species List (MSL)
The ICTV Report and Associated Communications
The Virus Metadata Resource (VMR)
Current Virus Taxonomy
Taxonomy Development: From an Expert-Based Activity to an Objective, Genomic-Based Framework
How Virus Taxonomy Is Constructed: Scope and Taxa Demarcation
Computational Taxonomy: Approaches, Insights and Obstacles
Virus Taxonomy: Looking Ahead
The Relevance of Virus Taxonomy to Science and Society: Goals and Insights
Classification of Metagenomic Sequences and Funding Virus Taxonomy
What to Accept for Classification: Quality Control of Genome Sequences
A Universal Virus Taxonomy
Virus Taxonomy and Computational Virology: Experts vs Algorithms
Communication of Virus Taxonomy; Classification Portraits and Species Nomenclature
Conclusions
Acknowledgments
References
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The view is often defended that sciences should be built upon clear and sharply defined basal concepts. In actual fact, no science, not even the most exact, begins with
such definitions. The true beginning of scientific activity consists rather in describing phenomena and then in proceeding to group, classify and correlate them.
—Freud S. (1915). “Instincts and their vicissitudes,” in The Standard Edition of the Complete Psychological Works of Sigmund Freud (Vol. 14), ed
Strachey J., editor. (London: The Hogarth Press;), 109–140.
A classification is useful because it starts discussions, has a heuristic value, allows predictions, is useful for teaching purposes, and allows related viruses to be united into
one and the same category.
—Lwoff, A. (1967) Principles of Classification and Nomenclature of Viruses. Nature, 215: 13-14.
Nothing in biology makes sense except in the light of evolution.
—Dobzhansky, T. (1973), “Nothing in Biology Makes Sense Except in the Light of Evolution", American Biology Teacher, 35 (3): 125–129.
Introduction
Classification is the fundament of any science. It helps scientists to establish connections between related objects, operating within a
framework that facilitates the advancement of research and the application and communication of scientific knowledge. In almost
all biological classification systems, there is a general acceptance that it will be predicated on the Darwinian principle of common
descent. For some time virus taxonomy, which is much younger than its host-oriented counterparts, resisted this basic premise, and
an essentially descriptive system was developed by its governing body, the International Committee on the Taxonomy of Viruses, or
ICTV. Gradually, however, phylogenetic relationships and other evolutionary-based analyses have begun to impact on the
delineation of virus taxa, from the species to the family and order ranks. As the methods of inferring deeper relationships in viral
phylogenies become more robust, and virus sampling of the biosphere expands, this approach is now extending to the delineation
☆
Change History: September 2019. AE Gorbalenya, C Lauber and S Siddell rewrote the entire article of C Fauquet on Taxonomy, Classification and
Nomenclature of viruses, published in Encyclopedia of Virology 2008; they produced Table 1 and all four Figures, and compiled Table 2 after the C Fauquet
article.
Reference Module in Biomedical Sciences
https://doi.org/10.1016/B978-0-12-801238-3.99237-7
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Taxonomy of Viruses
of taxa at higher ranks. These include those recently established by the ICTV to encompass virus variation at the largest scale of
evolution, starting from the origins of viruses.
The widespread exploration of viral diversity by viral metagenomics and related high-throughput virus discovery efforts is
happening at a remarkable pace, probably exceeding any other facet of virology. The result is an accumulation of genome sequences
of mostly uncultivated viruses, devoid of phenotypic characterization and not amenable to classification by traditional approaches.
Bridging the dichotomy between phenotype-based taxonomy and an evolutionary-based taxonomy is challenging, but computational virology holds great promise to tackle these challenges. The goal is to relate the multitude of phenotype-devoid viruses with
other, more “conventional” viruses, within a common framework of virus taxonomy. When combined with a meaningful and
usable naming system, this virus taxonomy will then provide the language of communication; in the classroom, in the laboratory, in
the clinic, with the public, and in the agencies that monitor, protect and conserve the environment in which we live (Fauquet, 2008).
A Short History of Virology From the Perspective of Virus Taxonomy
Virology emerged as a science at the end of the 19th century as the study of minuscule agents responsible for plant and animal
infectious diseases. Amongst the first viruses discovered were tobacco mosaic virus, foot and mouth disease virus and yellow fever
virus (reviewed in Oldstone, 2014). About 30 years later, Rivers (Rivers, 1927) was able to list about three dozen diseases that were
thought to be caused by viruses. Accordingly, at this time, mainly eukaryotic viruses were grouped together, essentially based on
visual symptoms of disease and their modes of transmission. This classification predated any formal virus taxonomy but may still be
regarded as its first phase. Subsequently, with the development of the electron microscope in the late 1930s, viruses, and in
particular bacteriophages (Luria et al., 1943), were recognized as particles, and not long afterward nucleic acid and proteins were
firmly established as components of small animal and plant viruses (Crick and Watson, 1956; Schaffer and Schwerdt, 1956). The
introduction of cultured cells for the in vitro propagation of eukaryotic viruses (Enders et al., 1949) accelerated the pace of virus
discovery and the need to classify and name groups of viruses became ever greater. At this point, the emphasis changed to a
classification based upon virion morphology, the biology and genetics of viruses, and the physio-chemical properties of virus
components. This might be looked upon as the second phase of virus classification. The later stages of this phase coincided with the
foundation of the ICTV; spearheaded by leading virologists including Lwoff, Andrewes, and Wildy, and supported by the wider
virology community (reviewed in Adams et al., 2017a).
In a subsequent third phase, virus taxonomy was increasingly dominated by information relating to the genome organization
and replication strategies of viruses, at a time when virus particles were recognized as just one stage of the complex virus life cycle.
With the application of first-generation methods of nucleic acid sequencing (Fiers et al., 1976), the volume of sequence information
increased significantly, and sequence comparison and phylogenetic relationships were introduced (reviewed in Goldbach, 1986;
Strauss and Strauss, 1988; Shukla and Ward, 1988) and became more important in taxonomy, although they were still mostly
considered alongside other phenotypic characters (Francki et al., 1991). Finally, in the first two decades of the 21st century, this
situation has again changed dramatically, with the introduction of affordable, extremely sensitive, and high-throughput sequencing
technologies (Radford et al., 2012). This has led to the discovery of a multitude of novel viruses, the overwhelming majority of
which are only recognized from their genomic information (reviewed in Zhang et al., 2019). The classification of viruses based on
their genome sequence alone may be considered as the fourth and ongoing phase of virus taxonomy.
Virus Taxonomy and the ICTV
For many decades, the classification of viruses was on the periphery of virology. However, as the number of known viruses grew and
their characterization expanded, the need for a unified framework of virus classification was broadly recognized. To this end, the
Virology Division of the International Union of Microbiological Societies (IUMS) created a special committee in 1966 at the
International Congress of Microbiology in Moscow (reviewed in Adams et al., 2017a). Known originally as the International
Committee on Nomenclature of Viruses, it was renamed as the ICTV in 1975. The statutes of the ICTV, which are approved and
legitimized by the IUMS, state that the objectives of the organization are to develop an internationally agreed (official) taxonomy,
including both classification and nomenclature, and to communicate its decisions by holding meetings and publishing reports. The
ICTV also provides guidance and assists practitioners and others with the application of virus taxonomy, although it does not
attempt to police its use.
The ICTV is a voluntary, non-profit organization and currently involves about 150 virologists. Its membership comprises an
Executive Committee (EC), Chairs of Study Groups (currently about 100, in total) as well as National and Life members. The ICTV is
assisted by expert Study Groups and support staff. The ICTV deals with all viruses, regardless of host, and it also regulates the
taxonomy of viroids and satellite nucleic acids.
The process of establishing a virus taxonomy begins with the submission of a taxonomic proposal, using proposal forms that are
available online (https://ictv.global/files/taxonomy-proposal-templates/). Proposals may deal with establishing, abolishing, or
revising taxa, or, indeed, any matter relevant to virus classification and nomenclature. The ICTV-appointed Study Groups are tasked
with the taxonomic development of specific families or other high-rank taxa, and they are, most often, the authors of taxonomic
proposals; although any virologist may submit a proposal. The Study Groups also develop demarcation criteria to define taxa at
Taxonomy of Viruses
3
different ranks, which are published in past and present ICTV reports and are also available online (https://ictv.global/ictv-reports/
ictv_online_report/). At any time, a complete set of all proposals that have been submitted to the EC, proposals that have been
approved by the EC (and are awaiting ratification), and proposals that have been ratified by the ICTV, are all available for download
from the ICTV website. The proposal review process has been shortened over the years, and, typically, it is now completed within
12 months, if the proposals are uncontroversial.
Once taxonomic proposals have been ratified by the ICTV, a summary article of the ratification cycle is published in the Virology
Division News section of the Archives of Virology. Since 2013, this has been done each year (for recent years see: Adams et al.,
2017b; King et al., 2018; Walker et al., 2019). The authors may also publish a separate account of their proposals. Also, the ICTV EC
publishes, annually, a Newsletter that provides information about ICTV activities, the development of virus taxonomy and related
issues.
ICTV Resources
The ICTV maintains several resources that serve the virology community. Some of the more important resources are
described below.
The ICTV Database, Website and Master Species List (MSL)
Once a taxonomic proposal has been ratified by the ICTV, the information is entered into the ICTV database (Lefkowitz et al., 2018).
The database is relational and each record stores data on a single taxon. The data includes fields such as the taxon name, taxon rank,
and parent taxon, as well as pointers to proposals relating to the taxon. The database can be interrogated at the ICTV website using
the online taxonomy browser (ictv.global/taxonomy browser). The database is also used to generate, each year, a spreadsheet of the
current virus taxonomy. These spreadsheets are known as the Master Species Lists (MSL) and are available for releases dating back to
2008 (https://ictv.global/taxonomy/p/taxonomy_releases/).
The ICTV Report and Associated Communications
While the MSL is the authoritative source of virus classification and nomenclature, the ICTV recognizes that its value is best realized
when it is used by peers, and others, in relation to the viruses that compose the virus taxa. Thus, the ICTV has published, since 1971,
a compendium of all virus taxa existing at the time of publication, plus a list of exemplar viruses corresponding to each species, with
varied information describing the properties and characteristics of virus members of each taxon. These reports also contain a
description of the demarcation criteria used to classify existing taxa, which assists with the classification of novel viruses. The Report
chapters are prepared by the relevant Study Groups under the guidance of an Editorial Board formed by the ICTV EC.
Starting in 2017, the ICTV EC has decided to publish these reports in an online format (https://ictv.global/ictv-reports/ictv_
online_report/). The current Online Report, which is the 10th iteration since 1971, has about 60 chapters (each usually describing a
single family of viruses, or, occasionally an order) and chapters will be added at the rate of about 25 per year until the report is
comprehensive. Also, the ICTV publishes, in the Journal of General Virology, short summaries of report chapters, known as ICTV
Taxonomy Profiles. These profiles are 2–3 pages long and serve as citable references for the Report chapters. They are also an
excellent educational resource for students.
The Online Report chapters provide a thorough, regularly updated description of taxa of each virus family or order. Separate
sections describe each genus in a family and the member species of that genus. They also include a Member Species table, which is
populated from the ICTV database, with information on the exemplar virus of the species, including accession number-based links
to GenBank and RefSeq records. The Member Species tables may also include additional isolates of particular interest; for example,
when members of a species have been informally organized into well-recognized subspecies level groups. This information is
accompanied by tables of viruses that are yet to be classified.
The Virus Metadata Resource (VMR)
Since 2017, the ICTV website presents information on exemplar viruses for each species and, in many cases, additional virus isolates
belonging to a species. This information is found in the VMR (https://ictv.global/taxonomy/vmr/) and includes virus names, virus
name abbreviations, isolate designations, GenBank, and when available corresponding RefSeq accession numbers and hosts. The
choice of virus exemplar isolates, names and abbreviations are not official ICTV designations (they are generally made by the Study
groups), but the VMR is useful as it reinforces the connection between virus taxonomy and viruses.
Current Virus Taxonomy
As with other taxonomies, the ICTV taxonomic system is hierarchical, with the least divergent and most numerous taxa, populating
the species rank at the base of the classification pyramid, and the most divergent taxa, filling the realm rank at its apex (Note that
4
Taxonomy of Viruses
“divergent” refers to intra-taxa divergence of viruses that form these taxa). Fig. 1 shows this hierarchical structure as it exists in June
2019. The 15 available ranks are populated by a total of 6898 taxa. At the moment, 5 ranks are still void of taxa. The naming
convention of the ICTV stipulates that taxa assigned to a particular rank, except for the species rank, should be single words starting
with a capital letter and ending with a given suffix. All taxa names in virology are written in italics to assist with distinguishing
between taxa and viruses, whose names are not written in italics (see below).
The 15-rank (including primary and secondary ranks) system of virus taxonomy was first proposed in 2016 and ratified in 2019,
replacing the 5-rank structure that had served virology for the past 30 years (Siddell et al., 2019). This large-scale change resulted
from the need to accommodate the complexity of virus phylogenetic relationships at almost the full scale of virus variation; from a
lower level, just above that observed between closely related viruses in outbreaks of circulating lineages, to the higher levels that
characterize the ancient relationships of viruses. These higher levels are difficult to study and were, previously, largely ignored for
classification purposes.
This new virus taxonomic structure partitions virus diversity in a way that resembles the taxonomy of hosts. This change will
facilitate cross-talk between virus, animal and plant taxonomies, and, with time, will allow for direct comparison of the ICTV
taxonomy with other virus classification systems, such as the broadly used Baltimore classification of virus replication strategies
(Baltimore, 1971). The number of current ICTV taxa distributed at all ranks according to the Baltimore classification is shown in
Fig. 2. The increase in the number of taxa from the years 2000 to 2019, as reported in the ICTV reports and the yearly ratification
articles since the 9th report, is shown in Fig. 3.
The current taxonomy includes 5560 virus species, with 707 added during the last two ratification cycles; a similarly high rate of
taxa increase was recorded for genera and families, the two other ranks that were “traditionally” used in virus taxonomy. Fig. 3
suggests that the number of recognized virus taxa will increase dramatically within the next few years and beyond. The complete list
of the current species and the parent taxa to which they are assigned can be found in the latest MSL release. The 150 families of the
current taxonomy are listed in Table 1 where the number of superior and inferior member taxa are shown for each family.
It is important to recognize that some aspects of the current virus taxonomy are quite unusual compared to the taxonomies of
pro- and eukaryotes. These virus-specific issues have many origins, including the lack of a universally accepted definition of what
constitutes a virus, the ongoing debate of whether viruses are alive, or not, and differences of opinion regarding the goals of virus
taxonomy.
The official position of the ICTV, which has changed little over many years, treats the units of virus taxonomy (the taxa)
differently from the viruses that are being classified, i.e. the members of the taxonomic units. The ICTV definition of a virus species is
“the lowest taxonomic level in the (classification) hierarchy approved by the ICTV,” and at the same time “a monophyletic group of
viruses whose properties can be distinguished from those of other species by multiple criteria.” This ambiguous, dual definition
stems from a time when the ICTV introduced the species rank to virus classification and viewed virus taxonomy as an operational
Number of taxa
low
Rank of taxa
species
5560
subgenus (…virus)
59
genus (…virus)
1019
subfamily (…virinae)
79
family (…viridae)
150
suborder (…virineae)
7
order (…virales)
14
0
Intra-taxon virus
divergence
subclass (…viricetidae)
6
class (…viricetes)
2
subphylum (…viricotina)
phylum (…viricota)
1
subkingdom (…virites)
0
0
kingdom (…virae)
0
high
subrealm (…vira)
1
realm (…viria)
Fig. 1 The ICTV taxonomic system. The taxonomic hierarchy is depicted as an inverted pyramid comprised of 15 ranks, with the least diverse rank of species at the
base, and the most diverse rank of realm at the apex. The pyramid form implies that the number of taxa will decrease as virus divergence increases, although this
relationship has not yet been clearly defined. The actual number of current taxa at each rank is shown.
Taxonomy of Viruses
Class I
dsDNA viruses
2075
species
subgenus
genus
subfamily
family
suborder
order
subclass
class
subphylum
phylum
subkingdom
kingdom
subrealm
realm
518
35
41
3
Class II
ssDNA viruses
1043
species
subgenus
genus
subfamily
family
suborder
order
subclass
class
subphylum
phylum
subkingdom
kingdom
subrealm
realm
87
6
15
Class IV
ssRNA+ viruses
1313
59
227
26
48
7
3
1
species
subgenus
genus
subfamily
family
suborder
order
subclass
class
subphylum
phylum
subkingdom
kingdom
subrealm
realm
Class III
dsRNA viruses
232
38
2
10
1
Class V
ssRNA- viruses
625
114
8
29
7
6
2
1
1
species
subgenus
genus
subfamily
family
suborder
order
subclass
class
subphylum
phylum
subkingdom
kingdom
subrealm
realm
species
subgenus
genus
subfamily
family
suborder
order
subclass
class
subphylum
phylum
subkingdom
kingdom
subrealm
realm
Class VI & VII
RT viruses
species
subgenus
genus
subfamily
family
suborder
order
subclass
class
subphylum
phylum
subkingdom
kingdom
subrealm
realm
240
27
2
6
1
Fig. 2 The current ICTV taxa distributed according to the Baltimore classification. Note that this analysis does not include the taxa of the Pospiviroidae or the
Asunviroidae, members of which do not encode proteins.
6000
Number of taxa
5000
4000
3000
2000
species
genus
family
order
phylum
class
1000
realm
0
2001 2003 2005 2007 2009 2011 2013 2015 2017 2019
Year
Fig. 3 The number of taxa recognized by the ICTV since 2000 and the most recent ratification cycle in 2019.
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Taxonomy of Viruses
Table 1
Current families and the taxa to which they are assigned.
Superior ranks
dsDNA Baltimore class I
Order
Order
Order
Order
Order
Order
Order
Order
Order
Order
Family
Inferior ranks
Host
Ackermannviridae
Herelleviridae
Myoviridae
Podoviridae
Siphoviridae
Alloherpesviridae
Herpesviridae
Malacoherpesviridae
Lipothrixviridae
Rudiviridae
Adenoviridae
Ampullaviridae
Ascoviridae
Asfarviridae
Baculoviridae
Bicaudaviridae
Clavaviridae
Corticoviridae
Fuselloviridae
Globuloviridae
Guttaviridae
Hytrosaviridae
Iridoviridae
Lavidaviridae
Marseilleviridae
Mimiviridae
Nimaviridae
Nudiviridae
Ovaliviridae
Papillomaviridae
Phycodnaviridae
Plasmaviridae
Pleolipoviridae
Polydnaviridae
Polyomaviridae
Portogloboviridae
Poxviridae
Sphaerolipoviridae
Tectiviridae
Tristromaviridae
Turriviridae
Unassigned
Unassigned
Unassigned
2 subfamilies, 3 genera, 17 species
5 subfamilies, 11 genera, 58 species
5 subfamilies, 91 genera, 341 species
3 subfamilies, 48 genera, 169 species
11 subfamilies, 210 genera, 735 species
4 genera, 13 species
3 subfamilies. 13 genera, 107 species
2 genera, 2 species
3 genera, 8 species
1 genus, 3 species
5 genera, 74 species
1 genus, 1 species
2 genera, 4 species
1 genus, 1 species
4 genera, 76 species
1 genus, 1 species
1 genus, 1 species
1 genus, 2 species
2 genera, 9 species
1 genus, 2 species
2 genera, 2 species
2 genera, 2 species
2 subfamilies, 6, genera, 19 species
2 genera, 3 species
1 genus, 4 species
2 genera, 2 species
1 genus, 1 species
2 genera, 3 species
1 genus, 1 species
2 subfamilies, 53 genera, 133 species
6 genera, 33 species
1 genus, 1 species
2 genera, 3 species
2 genera, 53 species
4 genera, 98 species
1 genus, 1 species
2 subfamilies, 14 genera, 71 species
3 genera, 7 species
3 genera, 7 species
1 genus. 2 species
1 genus, 2 species
Dinodnavirus (1 species)
Rhizidiovirus (1 species),
Salterprovirus (1 species)
Bacteria
Bacteria
Bacteria
Bacteria
Bacteria
Vertebrates
Vertebrates
Vertebrates
Archaea
Archaea
Vertebrates
Archaea
Invertebrates
Vertebrates, invertebrates
Invertebrates
Archaea
Archaea
Bacteria
Archaea
Archaea
Archaea
Invertebrates
Vertebrates
Protozoa
Protozoa
Protozoa
Invertebrates
Invertebrates
Alphasatellitidae
Anelloviridae
Bacilladnaviridae
Bidnaviridae
Circoviridae
Geminiviridae
Genomoviridae
Inoviridae
Microviridae
Nanoviridae
Parvoviridae
Pleolipoviridae
Smacoviridae
Spiraviridae
Tolecusatellitidae
2 subfamilies, 11 genera, 63 species
14 genera, 76 species
3 genera, 9 species
1 genus, 1 species
2 genera, 87 species
9 genera, 468 species
9 genera, 73 species
7 genera, 33 species
2 subfamilies, 6 genera, 21 species
2 genera, 12 species
2 subfamilies, 13 genera, 80 species
1 genus, 5 species
6 genera, 42 species
1 genus, 1 species
2 genera, 72 species
Plants
Vertebrates
Algae
Invertebrates
Vertebrates
Plants, invertebrates
Vertebrates, invertebrates, plants, fungi
Bacteria
Bacteria
Plants
Vertebrates, Invertebrates
Vertebrates
Algae
Bacteria
Archaea
Invertebrates
Vertebrates
Archaea
Vertebrates
Bacteria, archaea
Bacteria
Archaea
Archaea
Algae
Fungi
Archaea
ssDNA Baltimore class II
Vertebrates, invertebrates
Archaea
Plants
Taxonomy of Viruses
Table 1
7
(Continued)
Superior ranks
Family
Inferior ranks
Host
dsRNA Baltimore class III
Realm
Realm
Realm
Realm
Realm
Realm
Realm
Realm
Realm
Amalgaviridae
Birnaviridae
Chrysoviridae
Cystoviridae
Megabirnaviridae
Partitiviridae
Picobirnaviridae
Quadriviridae
Reoviridae
2 genus, 10 species
4 genera, 6 species
2 genus, 25 species
1 genus, 7 species
1 genus, 1 species
5 genera, 60 species
1 genus, 2 species
1 genus, 1 species
2 subfamilies, 15 genera, 91 species
Realm
Realm
ssRNA(+) Baltimore class IV
Realm, order, suborder
Realm, order, suborder
Totiviridae
Unassigned
5 genera, 28 species
Botybirnavirus, 1 species
Plants, fungi
Vertebrates, invertebrates
Fungi
Bacteria
Fungi
Plants, fungi, protozoa
Vertebrates
fungi
Vertebrates, invertebrates, plants, fungi,
algae
Fungi, protozoa
Abyssoviridae
Arteriviridae
Realm, order, suborder
Coronaviridae
Realm, order, suborder
Realm, order, suborder
Realm, order, suborder
Realm, order, suborder
Realm, order, suborder
Realm, order, suborder
Realm, order
Realm, order
Realm, order
Realm, order
Realm, order
Realm, order
Realm, order
Realm, order
Realm, order
Realm, order
Realm, order
Realm
Realm
Realm
Realm
Realm
Realm
Realm
Realm
Realm
Realm
Realm
Realm
Realm
Realm
Realm
Realm
Realm
Realm
Realm
Realm
Realm
Realm
Realm
Realm
Medioniviridae
Mesoniviridae
Mononiviridae
Euroniviridae
Roniviridae
Tobaniviridae
Dicistroviridae
Iflaviridae
Marnaviridae
Picornaviridae
Polycipiviridae
Secoviridae
Alphaflexiviridae
Betaflexiviridae
Deltaflexiviridae
Gammaflexiviridae
Tymoviridae
Alphatetraviridae
Alvernaviridae
Astroviridae
Barnaviridae
Benyviridae
Botourmiaviridae
Bromoviridae
Caliciviridae
Carmotetraviridae
Closteroviridae
Endornaviridae
Flaviviridae
Hepeviridae
Hypoviridae
Kitaviridae
Leviviridae
Luteoviridae
Matonaviridae
Narnaviridae
Nodaviridae
Permutotetraviridae
Potyviridae
Sarthroviridae
Solemoviridae
1 subfamily, 1 genus, 1 subgenus, 1 species
6 subfamilies, 12 genera, 10 subgenera,
20 species
2 subfamilies, 5 genera, 24 subgenera,
39 species
2 subfamilies, 2 genera, 2 subgenera, 2 species
1 subfamily, 1 genus, 8 subgenera, 9 species
1 subfamily, 1 genus, 1 subgenus, 1 species
2 subfamilies, 2 genera, 3 subgenera, 3 species
1 subfamily, 1 genus, 1 subgenus, 2 species
4 subfamilies, 8 genera, 9 subgenera, 11 species
3 genera, 15 species
1 genus, 15 species
7 genus, 20 species
47 genera, 110 species
3 genera, 14 species
1 subfamily, 8 genera, 86 species
7 genera, 56 species
2 subfamilies, 12 genera, 107 species
1 genus, 3 species
1 genus, 1 species
3 genera, 41 species
2 genera, 10 species
1 genus, 1 species
2 genera, 22 species
1 genus, 1 species
1 genus, 4 species
4 genera, 10 species
6 genera, 36 species
11 genera, 13 species
1 genus, 1 species
4 genera, 52 species
2 genera, 24 species
4 genera, 89 species
2 genera, 5 species
1 genus, 4 species
3 genera, 4 species
2 genera, 4 species
3 genera, 45 species
1 genus, 1 species
2 genera, 7 species
2 genera, 9 species
1 genus, 2 species
10 genera, 214 species
1 genus, 1 species
2 genera, 20 species
Invertebrates
Vertebrates
Vertebrates
Invertebrates
Invertebrates
Invertebrates
Invertebrates
Invertebrates
Vertebrates, invertebrates
Invertebrates
Invertebrates
Algae
Vertebrates
Invertebrates
Plants
Plants, fungi
Plants
Plants, fungi
Fungi
Invertebrates, plants
Invertebrates
Algae
Vertebrates
Fungi
Plants
Plants, fungi
Plants
Vertebrates
Invertebrates
Plants
Plants, fungi, protozoa
Vertebrates, invertebrates
Vertebrates
Fungi
Plants
Bacteria
Plants
Vertebrates
Fungi
Vertebrates, invertebrates
Invertebrates
Plants
Invertebrates
Plants
(Continued )
8
Taxonomy of Viruses
Table 1
(Continued)
Superior ranks
Family
Inferior ranks
Host
Realm
Realm
Realm
Realm
Realm
Realm
Realm
Realm
Realm
Realm
ssRNA(-) Baltimore class V
Realm, phylum, subphylum, class,
order
Realm, phylum, subphylum, class,
order
Realm, phylum, subphylum, class,
order
Realm, phylum, subphylum, class,
order
Realm, phylum, subphylum, class,
order
Realm, phylum, subphylum, class,
order
Realm, phylum, subphylum, class,
order
Realm, phylum, subphylum, class,
order
Realm, phylum, subphylum, class,
order
Realm, phylum, subphylum, class,
order
Realm, phylum, subphylum, class,
order
Realm, phylum, subphylum, class,
order
Realm, phylum, subphylum, class,
order
Realm, phylum, subphylum, class,
order
Realm, phylum, subphylum, class,
order
Realm, phylum, subphylum, class,
order
Realm, phylum, subphylum, class,
order
Realm, phylum, subphylum, class,
order
Realm, phylum, subphylum, class,
order
Realm, phylum, subphylum, class,
order
Realm, phylum, subphylum, class,
order
Realm, phylum, subphylum, class,
order
Realm, phylum, subphylum, class,
order
Realm, phylum, subphylum, class,
order
Realm, phylum, subphylum, class,
order
Solinviviridae
Togaviridae
Tombusviridae
Virgaviridae
Unassigned
Unassigned
Unassigned
Unassigned
Unassigned
Unassigned
2 genera, 2 species
1 genera, 31 species
3 subfamilies, 16 genera, 76 species
7 genera, 59 species
Albetovirus, 3 species
Aumaivirus, 1 species
Idaeovirus, 2 species
Papanivirus, 1 species
Sinaivirus, 2 species
Virtovirus, 1 species
Invertebrates
Vertebrates, invertebrates
Plants
Plants
Plants
Plants
Plants
Plants
Invertebrates
Plants
Qinviridae
1 genus, 8 species
Invertebrates
Aspiviridae
1 genus, 7 species
Plants
Chuviridae
1 genus, 29 species
Invertebrates
Artoviridae
1 genus, 7 species
Invertebrates
Bornaviridae
3 genera, 11 species
Vertebrates
Filoviridae
5 genera, 8 species
Vertebrates
Leishbuviridae
1 genus, 1 species
Protozoa
Lispiviridae
1 genus, 6 species
Invertebrates
Mymonaviridae
1 genus, 7 species
Fungi
Nyamiviridae
6 genera, 12 species
Vertebrates, invertebrates
Paramyxoviridae
4 subfamilies, 14 genera, 72 species
Vertebrates
Pneumoviridae
2 genera, 5 species
Vertebrates
Rhabdoviridae
20 genera, 144 species
Vertebrates, invertebrates, plants, fungi
Sunviridae
1 genus, 1 species
Vertebrates
Tospoviridae
1 genus, 18 species
Plants, invertebrates
Xinmoviridae
1 genus, 7 species
Invertebrates
Yueviridae
1 genus, 2 species
Invertebrates
Arenaviridae
4 genera, 43 species
Vertebrates
Cruliviridae
1 genus, 1 species
Invertebrates
Fimoviridae
1 genus, 9 species
Plants
Hantaviridae
4 subfamilies, 7 genera, 47 species
Vertebrates
Mypoviridae
1 genus, 1 species
Invertebrates
Nairoviridae
3 genera, 17 species
Vertebrates, invertebrates
Peribunyaviridae
4 genera, 95 species
Vertebrates, invertebrates
Phasmaviridae
6 genera, 15 species
Invertebrates
Taxonomy of Viruses
Table 1
(Continued)
Superior ranks
Family
Inferior ranks
Host
Realm, phylum, subphylum, class,
order
Realm, phylum, subphylum, class,
order
Realm, phylum, subphylum, class,
order
Realm, phylum, subphylum, class,
order
Realm, phylum, subphylum, class,
order
Realm
ssRNA-RT, Baltimore class VI
Order
Order
Order
Order
dsDNA-RT Baltimore class VII
Order
Phenuiviridae
15 genera 38 species
Vertebrates, Invertebrates, plants
Wupedeviridae
1 genus, 1 species
Plants
Amnoonviridae
1 genus, 1 species
Vertebrates
Orthomyxoviridae
7 genera, 9 species
Vertebrates, invertebrates
Unassigned
Coguvirus, 1 species
Plants
Unassigned
Deltavirus, 1 species
Vertebrates
Belpaoviridae
Metaviridae
Pseudoviridae
Retroviridae
1 genus, 11 species
2 genera, 31 species
3 genera, 34 species
2 subfamilies, 11 genera, 68 species
Invertebrates
Invertebrates, plants, fungi
Invertebrates, plants, algae, fungi
Vertebrates
Caulimoviridae
Hepadnaviridae
8 genera, 81 species
2 genera, 15 species
Plants
Vertebrates
Avsunviroidae
Pospiviroidae
3 genera, 4 species
5 genera, 28 species
Plants
Plants
Not classified
Realm
Realm
9
Note: The families are grouped according to the Baltimore classification. The Asunviroidae and Pospiviroidae families do not fit into the Baltimore scheme as the member viruses do not
encode proteins.
structure for organizing virus-related data (Francki et al., 1991). It may also have been influenced by the fact that, due to the obligate
dependence of viruses on their hosts, there was (and still is) a quasi-philosophical debate about viruses being alive, or not; which
leaves them as a conundrum in the mind of many.
However, this definition, which is not the norm in biology (De Queiroz, 2007), has both practical consequences and theoretical
implications. For example, since the names of many virus species match those of viruses, the ICTV requires that to distinguish taxa
and viruses, virologists always write taxa names with italics. Thus, although a botanist would probably not hesitate to write that
potato blight is caused by Phytophthora infestans, the ICTV would strongly discourage a virologist to write that dengue fever is caused
by Dengue virus, (it should be—dengue fever is caused by dengue virus). As can be seen from this example, there are many instances
where the only way to distinguish the species name and the virus name (and thus a concept from a real object) and use them as
instructed by the ICTV, is by dint of the typography.
More importantly, many virologists consider this distinction between “concept and biological object” as confusing, unhelpful,
or even incorrect. For example, there is considerable evidence for viruses forming populations whose genetic make-up and evolution
are shaped by biological and ecological mechanisms and constraints such as replication, genetic exchange, and selective pressures, in
much the same way as observed in plant or animal species. Then, people argue, that the word “virus species,” as used to mean a unit
of taxonomy or a biological entity should, essentially, be the same thing and any distinction is, at least, confusing. For the time
being, virologists are obliged—from an ICTV perspective—to make it clear from the context, the typography, or the use of different
species and virus names, to what they refer.
A related question of current taxonomy is whether it is a classification of phenotypic and genotypic characters that provides for
unambiguous communication and facilitates comparative studies, or whether it aims to produce a framework that also reflects the
evolutionary history and relatedness of viruses. It seems unlikely that all viruses have a single evolutionary origin (Koonin et al.,
2006; Krupovic et al., 2019), so it will not be possible to produce a fully inclusive Tree of Viruses separate from the Tree of Life (ToL).
Nevertheless, recent analyses indicate that, for example, the major groups of RNA viruses may be monophyletic in respect to their
RNA-dependent RNA polymerase (RdRp), and an evolutionary tree is beginning to emerge (Wolf et al., 2018), although concerns
have been raised about its reliability (Holmes and Duchêne, 2019).
In a pragmatic sense, and in the light of the amount of virus metagenomic data that is now being generated, it is clear that the
only way to classify the majority of viruses in the future (for they will probably never be isolated) is on the basis of genetic and
predicted phenotypic characters, with a large emphasis on phylogenetic relationships. The ICTV has accepted that viruses identified
on the basis of sequence data alone should be classified and named as part of the virosphere-wide (or universal) virus taxonomy
(Adams et al., 2017a), although this will present challenges. This approach has its supporters (Simmonds et al., 2017) and its
opponents (Calisher, 2016; Van Regenmortel, 2019).
10
Taxonomy of Viruses
Taxonomy Development: From an Expert-Based Activity to an Objective, Genomic-Based Framework
How Virus Taxonomy Is Constructed: Scope and Taxa Demarcation
Like its eukaryotic and prokaryotic counterparts, virus taxonomy is, in essence, an exercise in hierarchical clustering: the grouping of
viruses at the lowest taxonomic rank, the species, and the assignment of species to taxa at higher ranks. The most important element
of taxonomy is, therefore, the demarcation criteria used to delineate taxa at any given rank. In virology, this process is regulated by
the ICTV, rather than by a conventional process of peer-review. The framework within which the ICTV operates is defined by their
Statutes and the Code (of Virus Classification and Nomenclature) (https://ictv.global/information/w/ictv-information/383/ictvcode). According to this Code, it is not obligatory to populate all higher taxonomic ranks above species and genus, and taxa should
only be created when there is sufficient information to justify the assignments.
The ICTV Statutes and Code do not, however, define how demarcation criteria should be devised. This flexible approach allows
for the classification of all viruses that are well characterized and those that are newly discovered and await further analysis.
An essential role in this approach is taken by the Study Groups and other specialists, who submit taxonomic proposals, and together
with input from ICTV EC, define demarcation criteria in an expert-based process. Given that expert opinions may differ, and the
highly uneven characterization of different virus groups of unparalleled genetic divergence, it is not surprising that the methodologies and criteria used to demarcate and construct taxonomies in different virus groups can be very different. At one end of the
spectrum, there are classifications that remain largely based upon phenotypic characters, such as the host (e.g. Phycodnaviridae, a
family that includes very large DNA viruses), and at the other extreme, classification may be based almost entirely upon the genome
sequence of virus members (e.g. Papillomaviridae, a family that includes very small DNA viruses). Since no independent golden
standard exists, all these taxonomies with vastly different foundations are “correct” as long as they are approved by the ICTV.
Also, a virus taxonomy constructed along these lines is inevitably prone to revision as methodologies change, as information
accumulates, as different experts arrive at different conclusions and, indeed, sometimes following changes in the membership of the
ICTV. When specialist experts are free to decide which characteristics are chosen to construct taxonomies, and how the different
characters are to be weighted, then there will be differences of opinion, and the balance between “taxonomic stability” (which is
valued by the ICTV) and taxonomic advancement will be delicate. In other words, virus taxonomy is a dynamic, expert-driven,
developmental activity that is based upon the consideration of accumulating knowledge about viruses in relation to the goals that
virus taxonomists set themselves.
Despite this flexibility, three parameters are defined in most taxonomic proposals, irrespective of the authors approach to
taxonomy and whether they deal with phenotypic or genotypic attributes, or both: these are the subset of the virosphere that has to
be classified (or the taxonomy updated); the characters or attributes that have to be considered; and the measure(s) used to establish
and discriminate taxa and ranks.
The traditional, and still dominant choice in virus taxonomy is to limit consideration of viruses to the family (sometimes, order)
level and below; an approach that aligns with the Study Group structure of the ICTV. If a newly identified virus does not belong to
the taxa of any recognized family or order, it must prototype a new taxon at the respective ranks. Thus, new families and orders, and
their included taxa are defined through their relationship with those that already exist. The second parameter, the available
knowledge accumulated about a newly identified virus, is then evaluated by experts in a traditional framework whose core may
be described as “polythetic.” This word was explicitly used in the definition of virus species for two decades, but the approach itself
has also dominated the delineation of taxa at all ranks for many years. According to Marc van Regenmortel, the chief proponent of a
polythetic definition of species, the term “polythetic” means “a set of attributes defining a class, some of which must be possessed by
any member but no one of which is compulsory” (Van Regenmortel, 2018). Finally, experts then select attributes and define the
state of these attributes, either binary (the presence or absence of an attribute) or quantitatively (by measurement) that must be met
for the virus to be classified within a particular taxon. This is the process of implementing taxa demarcation criteria. Note that in this
expert-based polythetic approach exceptions are allowed, and a virus may not satisfy all criteria and still be assigned to a taxon; how
many deviations are permissible is left for experts to decide on a case-to-case basis. A list of principal phenotypic and genetic
attributes employed in the current virus taxonomy is shown in Table 2.
The approach described above was originally developed for the traditional phenotypic-based virus taxonomy and employed up
to about 60 attributes to classify viruses. The more attributes that were used the better, and the more informative the classification
was considered (Gibbs et al., 1966). This traditional framework also accommodated genomic sequence and its characteristics as
valid attributes. Indeed, their inclusion has contributed to the advancement of virus taxonomy from the earliest days of genome
sequencing and comparative genomics. However, the importance of sequence-based attributes has also increased steadily along
with the transition from genomic to (complete) genome sequences and the sophistication of comparative genomics. During the last
decade or so, different computational tools have been developed to improve decision making and to assist with the highthroughput analysis of genomic data in virus taxonomy. They are part of computational virology and their application may be a
part of the traditional taxonomy framework or go beyond current practice, as described below.
Computational Taxonomy: Approaches, Insights and Obstacles
In the current framework, the analysis of virus genome sequences is mainly concerned with one or more of four interconnected
aspects: (1) nucleotide or amino acid sequence distribution, (2) gene or protein content by homology, (3) phylogeny, and (4) pair-
Taxonomy of Viruses
Table 2
11
The principal phenotypic and genetic characters of virus classification.
Virion properties
Morphology (size, shape, envelope, peplomers, capsid symmetry and structure)
Physical properties (mass of virions, buoyant density, sedimentation coefficient, pH/thermal/cation/solvent/detergent/radiation stability)
Genome properties (size, type, polarity, strandedness, linear or circular, segment number, terminal structures, sequence)
Protein properties (number and size, activities; e.g. virion reverse transcriptase, sequence)
Lipids, Carbohydrates,
Genome organization, replication and expression
Replication of nucleic acid
Transcription
Translation and post-translational processing
Sites of virion protein accumulation, virion assembly, maturation and release
Cytopathology
Antigenic properties
Serological relationships
Epitope mapping
Biological properties
Host range (natural and experimental)
Disease association and pathogenicity
Tissue tropism, pathology, histopathology
Transmission
Vectors
Geographic distribution
wise distance. The choice of analysis is often dictated by practical considerations, but it should result ideally in a classification that
conforms with evolution by descent. Both evolutionary inferences and classification may be complicated by many factors including
biased virus sampling, convergence, recombination, and an uneven rate of evolution among lineages and genome regions. And, it
should always be remembered that alignment generation, which underlies many of these analyses, remains a challenging task that
largely defines both the resolution and reliability of downstream inferences.
1. The simplest approach to sequence analysis is to derive certain characteristics separately for each sequence and then to compare
them between sequences. For instance, the abundance of certain combinations of nucleotides, e.g. GC content, or a count of all
possible oligopeptides of a certain size (K-mer methods), also in combination with word position (natural vector of NV
representations), may be used to assist virus classification (Yu et al., 2013; Li et al., 2016). This approach is somewhat limited
and sequence characteristics are more typically defined in analyses that involve two or more sequences in alignment. In this case,
the aim is to trace variation and infer evolution from as many nucleotide and amino acid residues as possible, as described in
points 2 to 4 below.
2. Genome sequences can be used to identify homologous protein clusters and thus define gene content and associated gene order
(synteny). These characteristics have been used in virus taxonomy for decades, serving as markers and denominators of taxa at
different ranks within the expert-based framework (see for instance Le Gall et al., 2008). Recently, this approach was formalized
in VConTACT (Bolduc et al., 2017), which analyzes gene sharing networks, and GRAViTy (Aiewsakun and Simmonds, 2018),
which analyzes gene content and genomic organization signatures that constitute a set of polythetic characteristics. Each of these
tools uses different but sound statistical reasoning to infer virus clustering, which separates them from the expert-based
framework. Also, these analytical tools extend the scope of analysis beyond a single family, and in fact may work most efficiently
when applied to very many virus families. When compared to the results of the current expert-driven taxonomy, these tools were
shown to have both high sensitivity and specificity at family-level assignments in the analysis of eukaryotic viruses (GRAViTy)
and to tolerate frequent gene exchange, which is commonly encountered in the analysis of DNA and RNA phages (VConTACT).
However, the classifications derived by these methods are not hierarchical and the assignment of clusters to a certain rank of
taxonomy (e.g. family) still depends on expert opinion. These tools may, nevertheless, prove very useful when dealing with the
massive amounts of uncharacterized viral sequences discovered by viral metagenomics.
3. Another common approach is to infer unrooted or rooted virus phylogeny, i.e. evolution by descent, by quantifying residue
variation in orthologous proteins and then analyzing tree topology (monophyletic clusters). The most conserved proteins, which
include capsid proteins, polymerase proteins (RNA-directed RNA polymerase, reverse transcriptase, protein-primed family
B DNA polymerases) and others (Krupovic et al., 2019) are used for this purpose in many taxonomic proposals; in fact,
phylogenetic trees, which are, de facto, a taxonomic depiction of position, scope, and relations between different taxa, are almost
an essential component of any taxonomic proposal. In the current framework, experts then assign taxa to monophyletic clusters
in gene-based trees using external information about phenotype or genotype, which then serve as both the demarcation criteria
and markers of respective taxa. However, it should be made clear that as this framework does not ensure the inter-taxa
consistency of demarcation criteria, the accuracy of taxa assignment to a particular rank remains uncertain. To improve this
aspect, the VicTree software uses a multi-rate Poisson Tree Processes (mPTP) method to demarcate species (Modha et al., 2018).
The mPTP (Kapli et al., 2017) approach is part of the growing trend of developing phylogeny-aware tools to assist with species
12
Taxonomy of Viruses
identification of cellular organisms (Mallo and Posada, 2016). Their use in virology is encouraging but complicated by technical
issues whose discussion is beyond the scope of this review.
4. Tree partitioning may also be approached by the analysis of pairwise genetic distances (pagd) between viruses that constitute the
terminal tips of phylogenetic trees; these distances, along with topology, comprise the two major characteristics that are
necessary and sufficient for tree reconstruction (if evolution proceeds according to a molecular clock model, distances alone
may suffice to reconstruct the tree). The utility of this measure for the development of virus taxonomy was recognized early on in
the so-called pairwise sequence comparison analysis (Shukla and Ward, 1988). This approach has been championed by Claude
Fauquet, a long-time ICTV EC member, and was subsequently implemented into a dedicated tool, called PASC (Bao et al., 2014).
Its application to many virus families is available through the National Center for Biotechnology Information (NCBI) web site
(https://www.ncbi.nlm.nih.gov/sutils/pasc/). This and other similar implementations, e.g. the popular SDT software (Muhire
et al., 2014), utilize a frequency distribution of pairwise sequence divergence, commonly measured in % identical nucleotide
residues between virus genomes. This allows for the assignment of new viruses to existing taxa, as well as the demarcation of
ranks and taxa based on divergence thresholds that are imposed a priori upon expert decisions, informed by the density
distribution or external considerations, or both.
A considerable step forward to improve the biological relevance and predictive power of the distance-based methods and address
some technical issues (in particular distance calculations and the reliability of partitioning) has been advanced in such tools as
DEmARC (Lauber and Gorbalenya, 2012a). In this method, the crucial input is evolutionary distances that account for numerous
substitutions at every position in multiple sequence alignments of conserved proteins of a monophyletic virus group. Genetic
distances are connected to virus phylogeny and constitute the single attribute used, implying that there is no room for exceptions in
this framework. The tool devises thresholds on the limits of virus genetic divergence within and between clusters at all possible
levels of classification. It uses quantitative approaches that seek to minimize the cost associated with pairwise distances violating a
threshold and includes a check for the monophyly of clusters. This inference paves the way for an objective selection of classification
ranks and taxa (demarcation criteria).
DEmARC processing is data-driven but not sensitive to even highly-biased virus sampling, which dominates the density
distributions of pair-wise distances that form the basis of the original pagd-based methods. Unlike the conventional taxonomy
framework, DEmARC can be used to establish single-virus taxa and ranks, while simultaneously devising hierarchical classification
and classifying all viruses that belong to these taxa. Once taxa and ranks have been established by DEmARC, the identification of
phenotype and genome-based markers (attributes) that discriminate viruses of one taxon from another may be sought in separate
analyses. Since these markers have not been used in taxa demarcation, they—when identified—provide independent support for the
classification and connect the taxonomy to virus biology. While DEmARC, as with other tools, can assist taxonomy development by
experts within the conventional framework, it also has the potential to guide taxonomy development of large monophyletic
groups—including delineation of all ranks—on its own in a single-attribute phylogenetic framework.
Regardless of their realization, all computational tools in virus taxonomy are used to delineate clusters subsequently recognized
as taxa. The persistence (i.e. stability) of the delineated taxa in the face of novel virus discovery (as has been experienced during
DEmARC-defined taxa expansion within the family Coronaviridae over more than 10 years (https://ictv.global/taxonomy/; Gulyaeva
and Gorbalenya, unpublished)), was interpreted as a consequence of discontinuities of virus genetic variation, most probably due
to the action of various biological and environmental forces (Lauber and Gorbalenya, 2012b). However, it cannot yet be excluded
that the observed clustering of taxa may, in fact, be transitory in nature and will disappear with improved sampling from a much
wider natural virus diversity (Zhang et al., 2018). This concern remains a matter of debate, for the moment (see below).
It is highly likely that, in the longer term, we will see the development of virus taxonomy by researchers as part of a multi-step
computational framework involving network-based methods, pagd and phylogeny-aware approaches, and possibly others, combining the strengths of each approach at the different levels of virus taxonomy.
Virus Taxonomy: Looking Ahead
While broadly considered a branch of traditional science, virus taxonomy is a much younger sibling to its peers in biology, as it was
founded a mere 50 years ago. Accordingly, to date, only about 5500 virus species have been created, a minute fraction of eukaryotic
species known today. Thus, virus taxonomy is at the very beginning of a long road where it faces formidable challenges due to the
specific attributes of viruses and the unique role of the ICTV. Some of these are external, while others are ICTV-centric, and many are
interconnected.
The Relevance of Virus Taxonomy to Science and Society: Goals and Insights
The first and, arguably, the greatest challenge of virus taxonomy is to reassert its relevance to science and society. Unlike biology in
general, virus taxonomy is not a part of research and teaching programs and there have been no regular symposia held over many
years. Papers on virus taxonomy are seldom published in journals devoted to biological systematics and are hardly ever considered
by high profile journals, in contrast to the era of heated discussions that led to the foundation of the ICTV (Gibbs et al., 1966; Lwoff,
1967). While taxonomy in animal and plant biology is largely driven by the efforts of conservationists, often related to concerns
Taxonomy of Viruses
13
about the effects of climate change, viruses are not part of this drive. This is even though viruses are largely responsible for shaping,
for example, the ecology and evolution of marine microbial communities. Indeed, most practitioners of virology recognize
taxonomy as useful, but not critical for either basic or applied research, even when the focus is on matters of high socio-economic
relevance; for example, the study of major human pathogens. Researchers may introduce their papers by referring to the family and
genus of the virus concerned, but they then use the tools of evolutionary biology to describe virus divergence of practical and
theoretical significance.
In the wider context, virus “species” are rarely mentioned, seldom studied, and, if noticed at all, are looked upon as insignificant.
And why would it be otherwise for a “man-made concept,” as the major unit of virus taxonomy is described by the ICTV? In this
mindset, there may be little appreciation of, for example, the potential consequences of eradicating pathogenic viruses of a “species”
with the prospect of closely related siblings emerging as replacement pathogens; a scenario that has been well described for
polioviruses and coxsackie A viruses of the species Enterovirus C (Jiang et al., 2007). Likewise, there is no public outcry about the
growing backlog of non-classified viruses in GenBank, which relies on the ICTV to “classify” virus genome sequences, and bridges
virus taxonomy to researchers and the public.
Tellingly, NCBI and some other major organizations have now developed specialized databases for a limited number of major
human pathogens of virus origin (e.g. HIV, influenza viruses, and some dozen others). These databases inform us about virus
population variation, which then guides research on virus-host interactions and the development of measures to control and
counteract virus infections. In this framework, viruses are treated unequivocally as biological entities, and, by extension, the largescale variation of viruses, that has to be partitioned in virus taxonomy, must also be recognized as evolutionary in origin.
The lack of willingness by ICTV to embrace viruses as biological entities, and to seek a classification of biologically meaningful
ranks and taxa, is a missed opportunity to connect virus taxonomy to matters of primary importance for society and science, such as
measuring biodiversity, the study of ecosystems described by the taxonomies of cellular life forms, and the control of pathogens.
To resolve this issue will be a giant step toward meeting the major challenge facing virus taxonomy.
Classification of Metagenomic Sequences and Funding Virus Taxonomy
The recent advent of metagenomics holds some promise of improving the connection between virus taxonomy, science, and society.
With no pathogenic or other phenotypic profile available for the vast majority of viruses identified in metagenomic samples, despite
their obvious importance as regulators of marine and terrestrial ecosystems (Suttle, 2016; Williamson et al., 2017; Gregory et al.,
2019), their taxonomic assignment and nomenclature will be amongst the few attributes that link the acquired sequences to the
available knowledge base. Metagenomics is attracting significant interest, and funds, because the role of microbiomes (including
viruses) in the wellbeing of individual organisms (including humans) and their ecosystems are becoming increasingly evident.
It might be hoped that funding to support metagenomic research, with its numerous insights and high impact, may be extended to
include the development of virus taxonomy. This is important because, at present, the lack of a dedicated funding stream
downgrades virus taxonomy to a non-essential research activity. It is not clear how long virologists can sustain the development
of virus taxonomy in their spare time, with the ICTV receiving small donations to cover a bare minimum of the cost incurred by the
EC. This is a second challenge facing the virus taxonomy community.
What to Accept for Classification: Quality Control of Genome Sequences
With high-throughput next generation sequencing employed as a major tool of metagenomics, the rate of virus discovery has
exploded in recent years and will keep accelerating. The ICTV has already revised its procedures to improve the speed at which
taxonomic proposals are processed and must try to shorten the taxonomic ratification cycle further. While attempting to adapt and
fulfill its role in new circumstances, the choices of the ICTV are, as mentioned above, constrained by limited and uncertain funding.
Also, one aspect that is not within the control of the ICTV, but is nevertheless of paramount importance, is the quality of the
sequence data used in virus classification. The ICTV stipulates that to propose a new species taxon, it must be accompanied by a
(nearly) genomic sequence of an exemplar virus.
Generally speaking, when the number of exemplar viruses was relatively few, this requirement was fulfilled (note, however, that
there are several “historical” species with exemplar virus for which there is no available sequence data). But, in the case of virus
sequences derived from metagenomic samples, this problem is exacerbated. First, it is particularly challenging to assure that a
derived sequence represents a virus genome as accurately as sequence determined and validated through the traditional pipeline.
Common concerns include (1) artificial chimeras of closely related viruses that coinfect the same hosts; (2) that all segments of
multi-segment virus come from the same virus and they represent the virus in its entirety. The same concerns also apply to the
mining of virus metagenomic data from historical transcript shotgun assembly (TSA) databases or primary sequencing data
repositories like the Sequence Read Archive (SRA). The ICTV will need to work with the research community to develop standards
and mechanisms for the quality assurance of metagenomic sequences. Encouragingly, there have been significant recent developments in this direction, with the introduction of standards for reporting sequences of uncultivated virus genomes (Roux
et al., 2018).
14
Taxonomy of Viruses
A Universal Virus Taxonomy
The fourth challenge is that, compared to other taxonomies, virus taxonomy faces a much more daunting task when it comes to the
partitioning of divergence. Viruses are likely to infect all life forms, but, unlike their hosts, they may employ single or doublestranded RNA or DNA, as their genomes; emphasizing, once again their exceptional diversity. Furthermore, it has been pointed out
that the divergence of most conserved proteins found within a single order of ssRNA + viruses (the Nidovirales) exceeds that found
within the complete ToL (Gorbalenya and Lauber, 2017). This scale of residue replacement may not be the exception but rather it
may reflect a fundamental feature of viruses: high mutation and substitution rates, short replication cycle, and large progeny
population. The accurate reconstruction of deep relationships presents a test for evolutionary biology; and in particular, the field of
phylogenomics, whose tools and algorithms were developed for, and are routinely used in the analysis of microevolution. And it
may be that the deficiency of tools is not simply because of a lack of interest or effort. Some believe that these types of challenges
may require fundamentally new approaches (Holmes, 2011). Even if it becomes possible to reconstruct deep phylogenetic
relationships, the attribution of these relationships to viruses may remain debatable. This is especially true if evolutionary
reconstructions have to be based on only the most conserved proteins, which could be very few or even unique, as is the case
now for the Riboviria realm taxon. In this respect, virologists may have to learn from the ongoing polemic about gene- vs speciesbased phylogeny in cellular life forms (Mallo and Posada, 2016).
Allied to the sheer magnitude of the task is the question of whether or not it is possible, or even desirable, to strive for a universal
classification of viruses in a single framework. Different communities are now developing separate taxonomies of bacterial and
eukaryotic life forms and their subsets and, given that viruses may be even more diverse than their hosts in certain respects,
developing separate taxonomies for the major virus groups may also look like a sensible approach. On the other hand and given the
lack of theoretical arguments to the contrary, we may never know whether a common taxonomy framework for viruses is feasible
and informative unless we try. If it is, indeed, attainable, there will still be obstacles. The first is alluded to above and is the
recognition that taxa have been created and are still established using approaches with variable contributions from the analyses of
phenotype and genotype. At the extremes are the traditional approach that is essentially descriptive and based on phenotypic
characters, and the sequence-only approach that is based on the inclusion of viruses in groups (or logical classes) delineated by
quantitative genome-centric measures. Do we have to decide between one or the other approach? Can we run both approaches in
parallel? Are the approaches synergistic? And what is the effect of selecting one or more types of attributes on the resulting taxonomy
and its implications? These and other questions must be addressed.
A further challenge we will face in striving for a universal taxonomy is the question of uniformity regarding measures to describe
divergence and in the delineation of demarcation criteria. At present, the ICTV does not prescribe which demarcation criteria are
used to delineate taxa, nor does it recommend the use of any particular methodology, nor does it prescribe any quantitative
guidelines when, for example, phenetic or phylogenetic approaches are taken. As an illustration of the differences that exist, recent
analyses have shown that bacterial viruses are significantly more divergent, at all taxonomic levels than the comparable eukaryotic
virus groupings. Whether this difference reflects genuine differences in the evolution of respective virus groups, or the operational
differences of respective Study Groups, or a result of the particular measure used, or inconsistencies in taxa delimitation, is
unresolved. Problems such as this will have to be recognized and addressed by individual ICTV Study Groups (Aiewsakun et al.,
2018) but the question remains whether or not the ICTV as a whole wishes to address the issue.
Virus Taxonomy and Computational Virology: Experts vs Algorithms
The accelerating rate of virus discovery, which often identifies highly divergent viruses with no close relatives that can be identified
in public databases and metagenomic samples, makes it inevitable that expert decisions in virus taxonomy will increasingly depend
on computational analyses. Most Study Groups rely to a significant degree on such analyses already, and the expanding number of
newly discovered viral genomes will soon make it impossible to proceed with taxonomic updates without the assistance of efficient
computational frameworks. Also, since the growing number of virus families will include viruses exclusively identified through
metagenomics, the “experts” called upon to form the respective Study Groups will need enhanced computational skills. The
available analyses include semi-automatic sequence alignment methods, tools for the functional prediction of highly divergent
viral proteins, algorithms for objective sequence-based demarcation of viral taxa, and phylogeny reconstruction programs that can
cope with very large data sets. The application of these and other methods, as well as innovative IT solutions that make these
developments accessible to all virologists, will be key to the success of virus taxonomy in the future.
In addition to the development of innovative software, promoting further research in this area will be critical. This research
should include the development and testing of alternative classifications, as a way to assure the quality of any new taxonomy,
resolve disputes between rivaling proposals and improve the connectivity to other fields. Consequently, virus taxonomy will need to
attract more scientists working at the intersection of virology, computational biology, and bioinformatics, i.e. computational
virologists.
Communication of Virus Taxonomy; Classification Portraits and Species Nomenclature
Virus taxonomy is communicated to peers and the public through many channels that have been described above. Regardless of
which vehicle is used, there are two aspects—visual presentation and species nomenclature—that are central to the communication
of taxonomies.
Taxonomy of Viruses
15
Until very recently, virus taxonomy has been presented often as a table populated by a visual depiction of virions of different
shapes and sizes. This has sufficed to reflect the virus diversity that has been classified and the taxonomic structure that has been
implemented. However, given the many developments detailed elsewhere in this article, this needs to be reconsidered. Unlike its
host-oriented taxonomic counterparts, virus taxonomy lacks a broadly recognizable depiction of its end-points. This may be due
partly to the unparalleled virus diversity and partly because virus taxonomy is yet to embrace fully an evolutionary framework.
Regardless of its origins, this deficiency complicates the communication of advances in virus taxonomy to peers and the public and
needs to be addressed. As an example of one approach to this problem, a circular depiction of virus taxonomy has been developed
for monophyletic groups, in which virus sampling and phylogeny, and inter-virus distance are related (Fig. 4). This form of
depiction conveys a wealth of information that is not available in a phylogenetic tree, but its realization requires specialized
software and computational analysis of virus divergence that is beyond the tools commonly used at this time. This issue needs to be
addressed.
Another important aspect of communication relates to the nomenclature of virus species names. In contrast to most biological
classification systems, where a Linnaean binomial system of naming is used (for example, Homo sapiens), there is no common
framework for naming virus species. They are named in a multitude of ways, including elements of disease manifestation, the
geography of isolation, host species, or more recently, as an acknowledgment of the contribution made by eminent virologists. The
species naming issue has been revisited by the ICTV EC on many occasions, and the differences of opinions have been impossible to
reconcile. Currently, proposals have been made to change the naming of virus species to a binomial system (Dutilh et al., 2019) (for
a discussion see Lwoff, 1967; Van Regenmortel, 2019). Arguments in favor of this move are that a binomial system would
contribute to bringing virus taxonomy into line with most of biology, and it may reduce the considerable degree of confusion
concerning the ICTV distinction between the virus species as a taxon and viruses circulating in nature and studied in the laboratory.
Moreover, it would facilitate database handling and communication of virus taxonomy.
However, this proposed change would be most meaningful, and extend beyond the realm of virus taxonomists, if it were
connected to the recognition of virus species as biological entities, which is not seen as a current priority. It is also worth noting that,
given the small number of taxa described in virology and the rudimentary understanding of their stability, it may just be too early to
revise the current, disjointed framework of virus species names and replace it with a systematic nomenclature that could last a
reasonable period of time, and be appreciated by the broad community. It remains to be seen whether it is possible to make such a
radical change given the reservations above and a virus nomenclature that has evolved over 50 years of use.
Conclusions
Taxonomy is recognized as a traditional biological discipline that was born many centuries ago. Modern taxonomy is most closely
associated with the pioneering work of Carl Linnaeus (1707–78), which was, essentially, concerned with the hierarchical classification of animals and plants based upon phenotypic characteristics, together with the implementation of a standardized binomial
nomenclature (Linnæus, 1758). However, after embracing the concepts of selection, genetics, and phylogeny, taxonomy is now
being transformed into a branch of evolutionary science (Mallo and Posada, 2016). The extension of taxonomy to include viruses is
relatively recent and was a largely independent development, having been propelled by the needs of virology and virologists,
without particular regard to other taxonomic counterparts (although, see Lwoff, 1967). Even today, the Code of Virus Taxonomy
and Nomenclature states that the “Nomenclature of viruses is independent of other biological nomenclature” and “Virus taxon
nomenclature is recognized as an exception in the proposed International Code of Bionomenclature.”
While sharing its ultimate goal with its older taxonomic cousins—namely organizing the observed natural diversity in a
meaningful manner—virus taxonomy remains a singular exercise, which has been only loosely connected to evolutionary research
for many varied and, at least partially interconnected reasons: (1) the history of virus discovery, starting from pathogens that cause
symptoms in close temporal proximity to primary infection and now dominated by the analysis of metagenomic sequences mostly
lacking any connection to host and disease, (2) the lack of any shared virus trait whose variation could be quantified to determine a
virosphere-wide taxonomy, either separately or as part of the ToL; (3) the ambivalent place of viruses in science, as neither fully
physical or biological entities; (4) the ICTV’s commitment to the distinction of the species as a man-made operational unit of
taxonomy, rather than a separately evolving metapopulation lineage—as is the case elsewhere in biology; (5) and the autonomous
role of the ICTV in matters of virus taxonomy. Whatever the reasons, these factors combine to give testament to the immense
challenges facing virus taxonomy.
Many recent developments in virus taxonomy, including the expansion of its coverage to include the full range of virus
divergence and the introduction of the specialized computational tools of comparative genomics and phylogenetics, should
contribute to bridging the gap between virus taxonomy, evolutionary studies, and other taxonomic counterparts. This connectivity,
together with outreach to the broader virology community and the public remains, however, tenuous. Converting virus taxonomy
into a vigorous research discipline will be conditional on many new developments and will depend on the recognition of peers and
funding agencies that virus taxonomy can have a major impact on science and society. Increasing confidence in the scientific
foundations and the stability of virus taxa and ranks (as well as the associated nomenclature) may be key factors on this journey.
Finally, the maturity of virus taxonomy will be tested by its ability to reveal biologically meaningful structure in the virosphere, at all
levels of divergence and across all hosts; far beyond the currently recognized taxa, and well into the second semi-centennial of ICTV
existence.
16
Taxonomy of Viruses
Fig. 4 The current five-ranks taxonomy of the families Coronaviridae and Tobaniviridae, along with the density of virus sampling per species are depicted in a
circular form. Intervirus genetic divergence increases linearly from the perimeter toward the center of the circle. The delimited taxa are depicted in curved rectangles
that are colored according to rank: species (orange), subgenus (steel blue), genus (purple), subfamily (pale green), and family (marine blue). Each color is presented
as a light or dark shade that depicts the limits of intragroup genetic divergence, according to a distance threshold (light) and the maximum observed intra-rank
genetic divergence (dark). The height of the taxon rectangles conforms to the two-family-wide distance thresholds for each rank. Outside the species circle, the
relative density of virus sampling per species is shown in gray from low sampling (light gray) to high sampling (dark gray), which is in the range of 1 (least sampled
species) to 365 (most sampled species, PEDV). For each species, acronym of exemplar virus is provided; full names of these viruses are available at the ictv.global/
vmr. For a detailed description of the format, see (Lauber and Gorbalenya, 2012b).
Acknowledgments
AEG and SGS are previous and current Vice-Presidents of the ICTV but the opinions expressed in this article are solely those of the
authors. AEG work cited in this review was supported by grants from Leiden University Medical Center, Leiden University Fund, and
the EU FP7 and Horizon2000 Programs. We thank Anastasia Gulyaeva and Igor Sidorov for assistance with the production of Fig. 4.
Taxonomy of Viruses
17
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Relevant Websites
https://ictv.global/files/taxonomy-proposal-templates/—International Committee on Taxonomy of Viruses.
https://ictv.global/ictv-reports/ictv_online_report/—International Committee on Taxonomy of Viruses.
https://ictv.global/taxonomy/—International Committee on Taxonomy of Viruses.
https://ictv.global/taxonomy/p/taxonomy_releases/—International Committee on Taxonomy of Viruses.
https://ictv.global/taxonomy/vmr/—International Committee on Taxonomy of Viruses.
https://ictv.global/information/w/ictv-information/383/ictv-code—International Committee on Taxonomy of Viruses.
https://www.ncbi.nlm.nih.gov/sutils/pasc/—National Center for Biotechnology Information.