NDLI: Predicting the Emergence of H3N2 Influenza Viruses Reveals Contrasted Modes of Evolution of HA and NA Antigens

Content Provider	Springer Nature Link
Author	Sandie, Reatha Aris Brosou, Stéphane
Copyright Year	2013
Abstract	Vaccine design for rapidly changing viruses is based on empirical surveillance of strains circulating in a given season to assess those that will most likely spread during the next season. The choice of which strains to include in the vaccine is critical, as an erroneous decision can lead to a nonimmunized human population that will then be at risk in the face of an epidemic or, worse, a pandemic. Here, we present the first steps toward a very general phylogenetic approach to predict the emergence of novel viruses. Our genomic model builds upon natural features of viral evolution such as selection and recombination / reassortment, and incorporates episodic bursts of evolution and or of recombination. As a proof-of-concept, we assess the performance of this model in a retrospective study, focusing: (i) on the emergence of an unexpected H3N2 influenza strain in 2007, and (ii) on a longitudinal design. Based on the analysis of hemagglutinin (HA) and neuraminidase (NA) genes, our results show a lack of predictive power in both experimental designs, but shed light on the mode of evolution of these two antigens: (i) supporting the lack of significance of recombination in the evolution of this influenza virus, and (ii) showing that HA evolves episodically while NA changes gradually.
Starting Page	1
Ending Page	12
Page Count	12
File Format	PDF
ISSN	00222844
Journal	Journal of Molecular Evolution
Volume Number	78
Issue Number	1
e-ISSN	14321432
Language	English
Publisher	Springer US
Publisher Date	2013-12-17
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Bayesian inference Recombination Punctuated evolution Viral evolution Influenza H3N2 Evolutionary Biology Microbiology Plant Sciences Plant Genetics & Genomics Animal Genetics and Genomics Cell Biology
Content Type	Text
Resource Type	Article
Subject	Genetics Molecular Biology Ecology, Evolution, Behavior and Systematics

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