Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/83926
Title: Rules of co-occurring mutations characterize the antigenic evolution of human influenza A/H3N2, A/H1N1 and B viruses
Authors: Chen, Haifen
Zhou, Xinrui
Zheng, Jie
Kwoh, Chee-Keong
Keywords: Influenza virus
A/H3N2/H1N1 and B
Issue Date: 2016
Source: Chen, H., Zhou, X., Zheng, J., & Kwoh, C.-K. (2016). Rules of co-occurring mutations characterize the antigenic evolution of human influenza A/H3N2, A/H1N1 and B viruses. BMC Medical Genomics, 9(Suppl 3), 229-240.
Series/Report no.: BMC Medical Genomics
Abstract: Background: The human influenza viruses undergo rapid evolution (especially in hemagglutinin (HA), a glycoprotein on the surface of the virus), which enables the virus population to constantly evade the human immune system. Therefore, the vaccine has to be updated every year to stay effective. There is a need to characterize the evolution of influenza viruses for better selection of vaccine candidates and the prediction of pandemic strains. Studies have shown that the influenza hemagglutinin evolution is driven by the simultaneous mutations at antigenic sites. Here, we analyze simultaneous or co-occurring mutations in the HA protein of human influenza A/H3N2, A/H1N1 and B viruses to predict potential mutations, characterizing the antigenic evolution. Methods: We obtain the rules of mutation co-occurrence using association rule mining after extracting HA1 sequences and detect co-mutation sites under strong selective pressure. Then we predict the potential drifts with specific mutations of the viruses based on the rules and compare the results with the “observed” mutations in different years. Results: The sites under frequent mutations are in antigenic regions (epitopes) or receptor binding sites. Conclusions: Our study demonstrates the co-occurring site mutations obtained by rule mining can capture the evolution of influenza viruses, and confirms that cooperative interactions among sites of HA1 protein drive the influenza antigenic evolution.
URI: https://hdl.handle.net/10356/83926
http://hdl.handle.net/10220/42885
DOI: 10.1186/s12920-016-0230-5
DOI (Related Dataset): https://doi.org/10.21979/N9/H73L8Y
Schools: School of Computer Science and Engineering 
Rights: © 2016 The Author(s). Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Journal Articles

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