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Published online before print November 21, 2007, 10.1101/gr.6969007
Genome Res. 18:178-187, 2008
©2008 by Cold Spring Harbor Laboratory Press; ISSN 1088-9051/08 $5.00
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Methods

Networks of genomic co-occurrence capture characteristics of human influenza A (H3N2) evolution

Xiangjun Du1,2,3, Zhuo Wang1,2,3, Aiping Wu1,2,3, Lin Song1,2, Yang Cao1,2, Haiying Hang1, and Taijiao Jiang1,4

1 National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; 2 Graduate School of the Chinese Academy of Science, Beijing 100080, China

The recent availability of full genomic sequence data for a large number of human influenza A (H3N2) virus isolates over many years provides us an opportunity to analyze human influenza virus evolution by considering all gene segments simultaneously. However, such analysis requires development of new computational models that can capture the complex evolutionary features over the entire genome. By analyzing nucleotide co-occurrence over the entire genome of human H3N2 viruses, we have developed a network model to describe H3N2 virus evolutionary patterns and dynamics. The network model effectively captures the evolutionary antigenic features of H3N2 virus at the whole-genome level and accurately describes the complex evolutionary patterns between individual gene segments. Our analyses show that the co-occurring nucleotide modules apparently underpin the dynamics of human H3N2 evolution and that amino acid substitutions corresponding to nucleotide co-changes cluster preferentially in known antigenic regions of the viral HA. Therefore, our study demonstrates that nucleotide co-occurrence networks represent a powerful method for tracking influenza A virus evolution and that cooperative genomic interaction is a major force underlying influenza virus evolution.

3 These authors contributed equally to this work.

4 Corresponding author.

E-mail taijiao{at}moon.ibp.ac.cn; fax 86 10 64888427.

[Supplemental material is available online at www.genome.org.]

Article published online before print. Article and publication date are available at http://www.genome.org/cgi/doi/10.1101/gr.6969007


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