Viral variant visualizer (VVV): A novel bioinformatic tool for rapid and simple visualization of viral genetic diversity.
Bioinformatic pipeline
NGS
Viral population
Journal
Virus research
ISSN: 1872-7492
Titre abrégé: Virus Res
Pays: Netherlands
ID NLM: 8410979
Informations de publication
Date de publication:
02 01 2021
02 01 2021
Historique:
received:
15
05
2020
revised:
13
09
2020
accepted:
15
10
2020
pubmed:
21
10
2020
medline:
17
12
2020
entrez:
20
10
2020
Statut:
ppublish
Résumé
Here a bioinformatic pipeline VVV has been developed to analyse viral populations in a given sample from Next Generation Sequencing (NGS) data. To date, handling large amounts of data from NGS requires the expertise of bioinformaticians, both for data processing and result analysis. Consequently, VVV was designed to help non-bioinformaticians to perform these tasks. By providing only the NGS data file, the developed pipeline generated consensus sequences and determined the composition of the viral population for an avian Metapneumovirus (AMPV) and three different animal coronaviruses (Porcine Epidemic Diarrhea Virus (PEDV), Turkey Coronavirus (TCoV) and Infectious Bronchitis Virus (IBV)). In all cases, the pipeline produced viral consensus genomes corresponding to known consensus sequence and made it possible to highlight the presence of viral genetic variants through a single graphic representation. The method was validated by comparing the viral populations of an AMPV field sample, and of a copy of this virus produced from a DNA clone. VVV demonstrated that the cloned virus population was homogeneous (as designed) at position 2934 where the wild-type virus demonstrated two variant populations at a ratio of almost 50:50. A total of 18, 10, 3 and 28, viral genetic variants were detected for AMPV, PEDV, TCoV and IBV respectively. The simplicity of this pipeline makes the study of viral genetic variants more accessible to a wide variety of biologists, which should ultimately increase the rate of understanding of the mechanisms of viral genetic evolution.
Identifiants
pubmed: 33080244
pii: S0168-1702(20)31108-4
doi: 10.1016/j.virusres.2020.198201
pii:
doi:
Substances chimiques
RNA, Viral
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Validation Study
Langues
eng
Sous-ensembles de citation
IM
Pagination
198201Informations de copyright
Copyright © 2020 Elsevier B.V. All rights reserved.