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

View ORCID ProfileEmily J. Goldstein, View ORCID ProfileWilliam T. Harvey, Gavin S. Wilkie, Samantha J. Shepherd, Alasdair R. MacLean, Pablo R. Murcia, Rory N. Gunson
doi: https://doi.org/10.1101/121434
Emily J. Goldstein
1West of Scotland Specialist Virology Centre, Glasgow, United Kingdom
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William T. Harvey
2Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, United Kingdom
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Gavin S. Wilkie
3Medical Research Council-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
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Samantha J. Shepherd
1West of Scotland Specialist Virology Centre, Glasgow, United Kingdom
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Alasdair R. MacLean
1West of Scotland Specialist Virology Centre, Glasgow, United Kingdom
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Pablo R. Murcia
3Medical Research Council-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
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Rory N. Gunson
1West of Scotland Specialist Virology Centre, Glasgow, United Kingdom
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Abstract

Genetic surveillance of seasonal influenza is largely focused upon 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). 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 both methods were highly consistent 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. Inter-subgroup reassortants were identified (9%), including three 3C.3 viruses descended from a single reassortment event, which had persisted in the population. Significant phylogenetic associations with cases of severe acute respiratory illness observed herein warrant further investigation. Severe cases were also more likely to be associated with reassortant viruses (odds ratio: 4.4 (1.3-15.5)) and occur later in the season. These results suggest that increased levels of WGS, linked to clinical and epidemiological data, could improve influenza surveillance.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted March 28, 2017.
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Integrating patient and whole genome sequencing data to provide insights into the epidemiology of seasonal influenza A(H3N2) viruses
Emily J. Goldstein, William T. Harvey, Gavin S. Wilkie, Samantha J. Shepherd, Alasdair R. MacLean, Pablo R. Murcia, Rory N. Gunson
bioRxiv 121434; doi: https://doi.org/10.1101/121434
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Integrating patient and whole genome sequencing data to provide insights into the epidemiology of seasonal influenza A(H3N2) viruses
Emily J. Goldstein, William T. Harvey, Gavin S. Wilkie, Samantha J. Shepherd, Alasdair R. MacLean, Pablo R. Murcia, Rory N. Gunson
bioRxiv 121434; doi: https://doi.org/10.1101/121434

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