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Natural Selection Determines Synonymous Codon Usage Patterns of Neuraminidase (NA) Gene of the Different Subtypes of Influenza A Virus in Canada

DOI: 10.1155/2014/329049

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Abstract:

Synonymous codon usage patterns of neuraminidase (NA) gene of 64 subtypes (one is a mixed subtype) of influenza A virus found in Canada were analyzed. In total, 1422 NA sequences were analyzed. Among the subtypes, H1N1 is the prevailing one with 516 NCBI accession records, followed by H3N2, H3N8, and H4N6. The year of 2009 has the highest report records for the NA sequences in Canada, corresponding to the 2009 pandemic event. Correspondence analysis on the RSCU values of the four major subtypes showed that they had distinct clustering patterns in the two-dimensional scatter plot, indicating that different subtypes of IAV utilized different preferential codons. This subtype clustering pattern implied the important influence of natural selection, which could be further evidenced by an extremely flattened regression line in the neutrality plot (GC12 versus G3s plot) and a significant phylogenetic signal on the distribution of different subtypes in the clades of the phylogenetic tree ( statistic). In conclusion, different subtypes of IAV showed an evolutionary differentiation on choosing different optimal codons. Natural selection played a deterministic role to structure IAV codon usage patterns in Canada. 1. Introduction Codon usage is not a random event [1]. Codon usage bias has been broadly observed, and different mechanisms have been proposed to explain the bias patterns, for example, mutation pressure, translational efficiency, gene length [2], dinucleotide bias [3], tRNA abundance [4], organ specificity [5], and so on. Codon usage bias patterns have been broadly studied in recent years, especially for virus genomes [3, 6, 7]. In recent years, codon usage patterns have been widely explored for influenza viruses [6, 8–12]. Among the three influenza viruses, influenza A virus (IAV) is the major concern since it has a lot of subtypes. IAV is a genus of Orthomyxoviridae family of viruses, which caused influenza in birds and mammals [6, 13]. Among the eight RNA segments of IAV, hemagglutinin and neuraminidase (NA) genes are the principal concerns. Currently, most of modeling efforts on IAV are focused on Asian regions [6, 8]; little attention is paid on the evolutionary patterns of IAV in local areas of North America. To fill such a knowledge gap, in the present study, I analyzed all the available 1436 NA ORFs for IAV found in Canada to reveal the codon usage patterns of IAV different subtypes in Canada. 2. Materials and Methods 2.1. Sequence Data 1436 NA sequences found in IAV strains of Canada were extracted from NCBI GenBank database

References

[1]  M. Archetti, “Codon usage bias and mutation constraints reduce the level of error minimization of the genetic code,” Journal of Molecular Evolution, vol. 59, no. 2, pp. 258–266, 2004.
[2]  L. Duret and D. Mouchiroud, “Expression pattern and, surprisingly, gene length shape codon usage in Caenorhabditis, Drosophila, and Arabidopsis,” Proceedings of the National Academy of Sciences of the United States of America, vol. 96, no. 8, pp. 4482–4487, 1999.
[3]  P. Tao, L. Dai, M. Luo, F. Tang, P. Tien, and Z. Pan, “Analysis of synonymous codon usage in classical swine fever virus,” Virus Genes, vol. 38, no. 1, pp. 104–112, 2009.
[4]  E. N. Moriyama and J. R. Powell, “Codon usage bias and tRNA abundance in Drosophila,” Journal of Molecular Evolution, vol. 45, no. 5, pp. 514–523, 1997.
[5]  G. P. Holmquist and J. Filipski, “Organization of mutations along the genome: a prime determinant of genome evolution,” Trends in Ecology and Evolution, vol. 9, no. 2, pp. 65–69, 1994.
[6]  X. Liu, C. Wu, and A. Y.-H. Chen, “Codon usage bias and recombination events for neuraminidase and hemagglutinin genes in Chinese isolates of influenza A virus subtype H9N2,” Archives of Virology, vol. 155, no. 5, pp. 685–693, 2010.
[7]  Y. Zhang, Y. Liu, W. Liu et al., “Analysis of synonymous codon usage in Hepatitis A virus,” Virology Journal, vol. 8, p. 174, 2011.
[8]  T. Zhou, W. Gu, J. Ma, X. Sun, and Z. Lu, “Analysis of synonymous codon usage in H5N1 virus and other influenza A viruses,” BioSystems, vol. 81, no. 1, pp. 77–86, 2005.
[9]  E. H. M. Wong, D. K. Smith, R. Rabadan, M. Peiris, and L. L. M. Poon, “Codon usage bias and the evolution of influenza A viruses. Codon Usage Biases of Influenza Virus,” BMC Evolutionary Biology, vol. 10, no. 1, article 253, 2010.
[10]  S. Kryazhimskiy, G. A. Bazykin, and J. Dushoff, “Natural selection for nucleotide usage at synonymous and nonsynonymous sites in influenza A virus genes,” Journal of Virology, vol. 82, no. 10, pp. 4938–4945, 2008.
[11]  X. Gong, S. Fan, Z. Cui, and X. Li, “The CpG suppression of polymerase segments and its impact on codon usage bias in H1N1 influenza virus,” Acta Biophysica Sinica, vol. 27, pp. 537–544, 2011.
[12]  N. Goni, A. Iriarte, V. Comas et al., “Pandemic influenza A virus codon usage revisited: biases, adaptation and implications for vaccine strain development,” Virology Journal, vol. 9, p. 263, 2012.
[13]  K. Fancher and W. Hu, “Codon bias of influenza a viruses and their hosts,” American Journal of Molecular Biology, vol. 1, pp. 174–182, 2011.
[14]  S. Katoh, “MAFFT multiple sequence alignment software version 7: improvements in performance and usability,” Molecular Biology and Evolution, vol. 30, no. 4, pp. 772–780, 2013.
[15]  K. Katoh, K. Misawa, K.-I. Kuma, and T. Miyata, “MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform,” Nucleic Acids Research, vol. 30, no. 14, pp. 3059–3066, 2002.
[16]  P. M. Sharp and W.-H. Li, “Codon usage in regulatory genes in Escherichia coli does not reflect selection for “rare” codons,” Nucleic Acids Research, vol. 14, no. 19, pp. 7737–7749, 1986.
[17]  F. Wright, “The “effective number of codons” used in a gene,” Gene, vol. 87, pp. 23–29, 1990.
[18]  M. Greenacre and O. Nenadic, “Ca: a package for computation and visualization of simple, multiple and joint correspondence analysis,” 2012, http://www.carme-n.org/.
[19]  R Development Core Team, R: A Language and Environment For Statistical Computing, Vienna, Austria, R Foundation for Statistical Computing, Vienna, Austria, 2011, http://www.R-project.org.
[20]  S. P. Blomberg, T. Garland Jr., and A. R. Ives, “Testing for phylogenetic signal in comparative data: behavioral traits are more labile,” Evolution, vol. 57, no. 4, pp. 717–745, 2003.
[21]  R. P. Freckleton, P. H. Harvey, and M. Pagel, “Phylogenetic analysis and comparative data: a test and review of evidence,” American Naturalist, vol. 160, no. 6, pp. 712–726, 2002.
[22]  M. Pagel, “Inferring the historical patterns of biological evolution,” Nature, vol. 401, no. 6756, pp. 877–884, 1999.
[23]  L. Revell, “phytools: an R package for phylogenetic comparative biology (and other things),” Methods in Ecology and Evolution, vol. 3, pp. 217–223, 2012.
[24]  M. N. Price, P. S. Dehal, and A. P. Arkin, “FastTree 2—approximately maximum-likelihood trees for large alignments,” PLoS One, vol. 5, no. 3, Article ID e9490, 2010.
[25]  E. Paradis, J. Claude, and K. Strimmer, “APE: analyses of phylogenetics and evolution in R language,” Bioinformatics, vol. 20, no. 2, pp. 289–290, 2004.
[26]  T. Britton, B. Oxelman, A. Vinnersten, and K. Bremer, “Phylogenetic dating with confidence intervals using mean path lengths,” Molecular Phylogenetics and Evolution, vol. 24, no. 1, pp. 58–65, 2002.
[27]  Q. Liu and Q. Xue, “Comparative studies on codon usage pattern of chloroplasts and their host nuclear genes in four plant species,” Journal of Genetics, vol. 84, no. 1, pp. 55–62, 2005.
[28]  A. Kawabe and N. T. Miyashita, “Patterns of codon usage bias in three dicot and four monocot plant species,” Genes and Genetic Systems, vol. 78, no. 5, pp. 343–352, 2003.

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