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      Towards a unified classification for human respiratory syncytial virus genotypes


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          Since the first human respiratory syncytial virus (HRSV) genotype classification in 1998, inconsistent conclusions have been drawn regarding the criteria that define HRSV genotypes and their nomenclature, challenging data comparisons between research groups. In this study, we aim to unify the field of HRSV genotype classification by reviewing the different methods that have been used in the past to define HRSV genotypes and by proposing a new classification procedure, based on well-established phylogenetic methods. All available complete HRSV genomes (>12,000 bp) were downloaded from GenBank and divided into the two subgroups: HRSV-A and HRSV-B. From whole-genome alignments, the regions that correspond to the open reading frame of the glycoprotein G and the second hypervariable region (HVR2) of the ectodomain were extracted. In the resulting partial alignments, the phylogenetic signal within each fragment was assessed. Maximum likelihood phylogenetic trees were reconstructed using the complete genome alignments. Patristic distances were calculated between all pairs of tips in the phylogenetic tree and summarized as a density plot in order to determine a cutoff value at the lowest point following the major distance peak. Our data show that neither the HVR2 fragment nor the G gene contains sufficient phylogenetic signal to perform reliable phylogenetic reconstruction. Therefore, whole-genome alignments were used to determine HRSV genotypes. We define a genotype using the following criteria: a bootstrap support of 70 per cent for the respective clade and a maximum patristic distance between all members of the clade of ≤0.018 substitutions per site for HRSV-A or ≤0.026 substitutions per site for HRSV-B. By applying this definition, we distinguish twenty-three genotypes within subtype HRSV-A and six genotypes within subtype HRSV-B. Applying the genotype criteria on subsampled data sets confirmed the robustness of the method.

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          Two Methods for Mapping and Visualizing Associated Data on Phylogeny Using Ggtree

          Ggtree is a comprehensive R package for visualizing and annotating phylogenetic trees with associated data. It can also map and visualize associated external data on phylogenies with two general methods. Method 1 allows external data to be mapped on the tree structure and used as visual characteristic in tree and data visualization. Method 2 plots the data with the tree side by side using different geometric functions after reordering the data based on the tree structure. These two methods integrate data with phylogeny for further exploration and comparison in the evolutionary biology context. Ggtree is available from http://www.bioconductor.org/packages/ggtree.
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            Global patterns in monthly activity of influenza virus, respiratory syncytial virus, parainfluenza virus, and metapneumovirus: a systematic analysis

            Influenza virus, respiratory syncytial virus, parainfluenza virus, and metapneumovirus are the most common viruses associated with acute lower respiratory infections in young children (<5 years) and older people (≥65 years). A global report of the monthly activity of these viruses is needed to inform public health strategies and programmes for their control.
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              Consensus statement: Virus taxonomy in the age of metagenomics

              Although viral sequences are important in taxonomy, classification has typically also required biological properties, thus excluding viruses that were identified by metagenomics. The proposals in this Consensus Statement, which are supported by the International Committee on Taxonomy of Viruses (ICTV), enable viruses that are discovered by sequence alone to be incorporated into virus classification.

                Author and article information

                Virus Evol
                Virus Evol
                Virus Evolution
                Oxford University Press
                July 2020
                24 July 2020
                24 July 2020
                : 6
                : 2
                : veaa052
                [v1 ]KU Leuven, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Laboratory of Clinical and Epidemiological Virology , Herestraat 49 box 1040, BE-3000 Leuven, Belgium
                [v2 ] University Hospitals Leuven, Department of Laboratory Medicine and National Reference Centre for Respiratory Pathogens , Herestraat 49, BE-3000 Leuven, Belgium
                Author notes
                Corresponding author: E-mail: kaat.ramaekers@ 123456kuleuven.be
                Author information
                © The Author(s) 2020. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                Page count
                Pages: 11
                Funded by: Institute of Public Health;
                Research Article

                human respiratory syncytial virus,classification,genotypes


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