, Volume 141, Issue 4–6, pp 143–155 | Cite as

Detection of site-specific positive Darwinian selection on pandemic influenza A/H1N1 virus genome: integrative approaches

  • Ramaiah Arunachalam


In the twenty-first century, the first pandemic novel human influenza A/H1N1virus (NIV) outbreak was reported at Mexico and USA on March and early April, 2009 respectively. The outbreak occurred among human populations due to the presence of meager or no immune response against newly emerged viruses. The success of vaccines and drugs depends on their low susceptibility to the formation of escape mutants in virus. Identification of excess, non-synonymous substitutions over synonymous ones is a main indicator of positive Darwinian selection in protein-coding genes of NIVs. The positive Darwinian selection operating on each site of proteins were inferred by computing ω, the ratio of the non-synonymous/synonymous substitutions [dN/dS (or) Ka/Ks], which was calculated by three different methods in terms of codon-based maximum likelihood, branch-site and empirical Bayesian methods under various models. Totally, nine sites from PB2, PB1, HA, M2 and NS1 are inferred as positively selected. The function for amino acid sites of NIVs proteins under positive selection are inferred by comparing the sites with experimentally determined functionally known amino acid sites. Completely 4 positively selected sites of PB1, HA and M2 are found to be involved in B-cell epitopes (BCEs). Interestingly, most of these sites are also involving in T-cell epitopes (TCEs). However, more sites under positive selection forces are involved in TCEs than those of BCEs. Amino acid sites engaged in both BCEs and TCEs should be measured as highly suitable targets, because these sites could induce the strong humoral and cellular immune responses against targets.


Novel influenza A/H1N1 virus Genome Natural selection Amino acid function 



Author thanks Dr. G. Annadurai, MS University, India and Prof. K.G. Sivaramakrishnan, Madras Christian College, Chennai, India for their fruitful comments. Author also thanks Prof. Mark Johnson and Dr. Tiina Salminen for the excellent computing facilities at the Structural Bioinformatics Laboratory (Åbo Akademi University, Finland) funded by Biocenter Finland infrastructure (bioinformatics and translational activities); Sigrid Juselius; Tor, Joe, and Pentti Borg Foundations. Author was partially supported by the Finnish Government Scholarship of Centre for International Mobility (CIMO), Finland [KM-11-7352, 05.05.2011] and University Grants Commission [F.87-5/2009(IC), 28.06.2011], India. No funders had a role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Supplementary material

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© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Sri Paramakalyani Centre for Environmental SciencesManonmaniam Sundaranar UniversityAlwarkurichiIndia
  2. 2.Structural Bioinformatics Laboratory, Department of BiosciencesÅbo Akademi UniversityTurkuFinland

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