Supporting pandemic response using genomics and bioinformatics: A case study on the emergent SARS-CoV-2 outbreak.
COVID-19
PHEIC
alignment-free phylogeny
bioinformatics
genomics
viral evolution
Journal
Transboundary and emerging diseases
ISSN: 1865-1682
Titre abrégé: Transbound Emerg Dis
Pays: Germany
ID NLM: 101319538
Informations de publication
Date de publication:
Jul 2020
Jul 2020
Historique:
received:
19
03
2020
revised:
30
03
2020
accepted:
07
04
2020
pubmed:
20
4
2020
medline:
15
7
2020
entrez:
20
4
2020
Statut:
ppublish
Résumé
Pre-clinical responses to fast-moving infectious disease outbreaks heavily depend on choosing the best isolates for animal models that inform diagnostics, vaccines and treatments. Current approaches are driven by practical considerations (e.g. first available virus isolate) rather than a detailed analysis of the characteristics of the virus strain chosen, which can lead to animal models that are not representative of the circulating or emerging clusters. Here, we suggest a combination of epidemiological, experimental and bioinformatic considerations when choosing virus strains for animal model generation. We discuss the currently chosen SARS-CoV-2 strains for international coronavirus disease (COVID-19) models in the context of their phylogeny as well as in a novel alignment-free bioinformatic approach. Unlike phylogenetic trees, which focus on individual shared mutations, this new approach assesses genome-wide co-developing functionalities and hence offers a more fluid view of the 'cloud of variances' that RNA viruses are prone to accumulate. This joint approach concludes that while the current animal models cover the existing viral strains adequately, there is substantial evolutionary activity that is likely not considered by the current models. Based on insights from the non-discrete alignment-free approach and experimental observations, we suggest isolates for future animal models.
Identifiants
pubmed: 32306500
doi: 10.1111/tbed.13588
pmc: PMC7264654
doi:
Banques de données
GENBANK
['AY274119.3', 'AY291451.1', 'AY502923.1', 'AY502932.1', 'AY559083.1', 'AY559084.1', 'AY559087.1', 'KY417142.1', 'KY417152.1', 'KJ477102.1', 'KT006149.2', 'KT026453.1', 'KT029139.1', 'MG596802.1', 'MG596803.1']
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1453-1462Subventions
Organisme : Commonwealth Scientific and Industrial Research Organisation
Organisme : Coalition for Epidemic Preparedness Innovations
Informations de copyright
© 2020 The Authors. Transboundary and Emerging Diseases published by Blackwell Verlag GmbH.
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