Integrating patient and whole-genome sequencing data to provide insights into the epidemiology of seasonal influenza A(H3N2) viruses

Goldstein, E. J., Harvey, W. T., Wilkie, G. S., Shepherd, S. J., MacLean, A. R., Murcia, P. R. and Gunson, R. N. (2017) Integrating patient and whole-genome sequencing data to provide insights into the epidemiology of seasonal influenza A(H3N2) viruses. Microbial Genomics, 4, (doi: 10.1099/mgen.0.000137) (PMID:29310750) (PMCID:PMC5857367)

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Abstract

Genetic surveillance of seasonal influenza is largely focused on sequencing of the haemagglutinin gene. Consequently, our understanding of the contribution of the remaining seven gene segments to the evolution and epidemiological dynamics of seasonal influenza is relatively limited. The increased availability of next-generation sequencing technologies allows rapid and economic whole-genome sequencing (WGS) of influenza virus. Here, 150 influenza A(H3N2) positive clinical specimens with linked epidemiological data, from the 2014/15 season in Scotland, were sequenced directly using both Sanger sequencing of the HA1 region and WGS using the Illumina MiSeq platform. Sequences generated by the two methods were highly correlated, and WGS provided on average >90 % whole genome coverage. As reported in other European countries during 2014/15, all strains belonged to genetic group 3C, with subgroup 3C.2a predominating. Multiple inter-subgroup reassortants were identified, including three 3C.3 viruses descended from a single reassortment event, which had persisted in the population. Cases of severe acute respiratory illness were significantly clustered on phylogenies of multiple gene segments indicating potential genetic factors warranting further investigation. Severe cases were also more likely to be associated with reassortant viruses and to occur later in the season. These results suggest that WGS provides an opportunity to develop our understanding of the relationship between the influenza genome and disease severity and the epidemiological consequences of within-subtype reassortment. Therefore, increased levels of WGS, linked to clinical and epidemiological data, could improve influenza surveillance.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Harvey, Dr William and Wilkie, Dr Gavin and Gunson, Dr Rory and Murcia, Professor Pablo
Authors: Goldstein, E. J., Harvey, W. T., Wilkie, G. S., Shepherd, S. J., MacLean, A. R., Murcia, P. R., and Gunson, R. N.
College/School:College of Medical Veterinary and Life Sciences > Institute of Health and Wellbeing > Public Health
College of Medical Veterinary and Life Sciences > Institute of Infection Immunity and Inflammation
Journal Name:Microbial Genomics
Publisher:Microbiology Society
ISSN:2057-5858
ISSN (Online):2057-5858
Copyright Holders:Copyright © 2017 The Authors
First Published:First published in Microbial Genomics 4
Publisher Policy:Reproduced under a Creative Commons License

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