Toward unified molecular surveillance of RSV: A proposal for genotype definition
File(s)
Published version
Author(s)
Type
Journal Article
Abstract
Background
Human respiratory syncytial virus (RSV) is classified into antigenic subgroups A and B. Thirteen genotypes have been defined for RSV‐A and 20 for RSV‐B, without any consensus on genotype definition.
Methods
We evaluated clustering of RSV sequences published in GenBank until February 2018 to define genotypes by using maximum likelihood and Bayesian phylogenetic analyses and average p‐distances.
Results
We compared the patterns of sequence clustering of complete genomes; the three surface glycoproteins genes (SH, G, and F, single and concatenated); the ectodomain and the 2nd hypervariable region of G gene. Although complete genome analysis achieved the best resolution, the F, G, and G‐ectodomain phylogenies showed similar topologies with statistical support comparable to complete genome. Based on the widespread geographic representation and large number of available G‐ectodomain sequences, this region was chosen as the minimum region suitable for RSV genotyping. A genotype was defined as a monophyletic cluster of sequences with high statistical support (≥80% bootstrap and ≥0.8 posterior probability), with an intragenotype p‐distance ≤0.03 for both subgroups and an intergenotype p‐distance ≥0.09 for RSV‐A and ≥0.05 for RSV‐B. In this work, the number of genotypes was reduced from 13 to three for RSV‐A (GA1‐GA3) and from 20 to seven for RSV‐B (GB1‐GB7). Within these, two additional levels of classification were defined: subgenotypes and lineages. Signature amino acid substitutions to complement this classification were also identified.
Conclusions
We propose an objective protocol for RSV genotyping suitable for adoption as an international standard to support the global expansion of RSV molecular surveillance.
Human respiratory syncytial virus (RSV) is classified into antigenic subgroups A and B. Thirteen genotypes have been defined for RSV‐A and 20 for RSV‐B, without any consensus on genotype definition.
Methods
We evaluated clustering of RSV sequences published in GenBank until February 2018 to define genotypes by using maximum likelihood and Bayesian phylogenetic analyses and average p‐distances.
Results
We compared the patterns of sequence clustering of complete genomes; the three surface glycoproteins genes (SH, G, and F, single and concatenated); the ectodomain and the 2nd hypervariable region of G gene. Although complete genome analysis achieved the best resolution, the F, G, and G‐ectodomain phylogenies showed similar topologies with statistical support comparable to complete genome. Based on the widespread geographic representation and large number of available G‐ectodomain sequences, this region was chosen as the minimum region suitable for RSV genotyping. A genotype was defined as a monophyletic cluster of sequences with high statistical support (≥80% bootstrap and ≥0.8 posterior probability), with an intragenotype p‐distance ≤0.03 for both subgroups and an intergenotype p‐distance ≥0.09 for RSV‐A and ≥0.05 for RSV‐B. In this work, the number of genotypes was reduced from 13 to three for RSV‐A (GA1‐GA3) and from 20 to seven for RSV‐B (GB1‐GB7). Within these, two additional levels of classification were defined: subgenotypes and lineages. Signature amino acid substitutions to complement this classification were also identified.
Conclusions
We propose an objective protocol for RSV genotyping suitable for adoption as an international standard to support the global expansion of RSV molecular surveillance.
Date Issued
2020-05-01
Date Acceptance
2019-12-15
Citation
Influenza and Other Respiratory Viruses, 2020, 14 (3), pp.274-285
ISSN
1750-2640
Publisher
Wiley Open Access
Start Page
274
End Page
285
Journal / Book Title
Influenza and Other Respiratory Viruses
Volume
14
Issue
3
Copyright Statement
© 2020 The Authors. Influenza and Other Respiratory Viruses published by John Wiley & Sons Ltd
This is an open access article under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
This is an open access article under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Sponsor
National Institute for Health Research
National Institute for Health Research
National Institute for Health Research
Asthma UK
Imperial College Healthcare NHS Trust- BRC Funding
GlaxoSmithKline Services Unlimited
National Institute for Health Research
Medical Research Council (MRC)
Imperial College Healthcare NHS Trust- BRC Funding
National Institute for Health Research
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000511025000001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Grant Number
NF-SI-0513-10150
HPRU-2012-10064
RDA06 79560
Asthma UK Centre
RDA02
PO 3000941762
RDF04
MR/T50256X/1
RDC04
NIHR201385
Subjects
Science & Technology
Life Sciences & Biomedicine
Infectious Diseases
Virology
average genetic distance
genotypes
global molecular surveillance
human orthopneumovirus
human respiratory syncytial virus
lineages
phylogenetic analysis
subgenotypes
RESPIRATORY SYNCYTIAL VIRUS
GROUP-A
CIRCULATION PATTERNS
GENETIC DIVERSITY
BUENOS-AIRES
G-PROTEIN
SUBGROUP
EVOLUTION
SELECTION
ALIGNMENT
Publication Status
Published
Date Publish Online
2020-02-05