Comparative study of the hemagglutinin and neuraminidase genes of influenza A virus H3N2, H9N2, and H5N1 subtypes using bioinformatics techniques

Author:

Ahn Insung123,Son Hyeon S.123

Affiliation:

1. Bioinformatics Team, Supercomputing Center, Korea Institute of Science and Technology Information, P.O. Box 122, Yusong-Gu, Daejon 305-806, Korea

2. Laboratory of Computational Biology and Bioinformatics, Institute of Health and Environment, Graduate School of Public Health, Seoul National University, 28 Yongon-Dong, Chongno-Gu, Seoul 110-799, Korea

3. Interdisciplinary Graduate Program in Bioinformatics, College of Natural Science, Seoul National University, San 56-1, Sillim-Dong, Gwanak-Gu, Seoul 151-742, Korea

Abstract

To investigate the genomic patterns of influenza A virus subtypes, such as H3N2, H9N2, and H5N1, we collected 1842 sequences of the hemagglutinin and neuraminidase genes from the NCBI database and parsed them into 7 categories: accession number, host species, sampling year, country, subtype, gene name, and sequence. The sequences that were isolated from the human, avian, and swine populations were extracted and stored in a MySQL®database for intensive analysis. The GC content and relative synonymous codon usage (RSCU) values were calculated using JAVA codes. As a result, correspondence analysis of the RSCU values yielded the unique codon usage pattern (CUP) of each subtype and revealed no extreme differences among the human, avian, and swine isolates. H5N1 subtype viruses exhibited little variation in CUPs compared with other subtypes, suggesting that the H5N1 CUP has not yet undergone significant changes within each host species. Moreover, some observations may be relevant to CUP variation that has occurred over time among the H3N2 subtype viruses isolated from humans. All the sequences were divided into 3 groups over time, and each group seemed to have preferred synonymous codon patterns for each amino acid, especially for arginine, glycine, leucine, and valine. The bioinformatics technique we introduce in this study may be useful in predicting the evolutionary patterns of pandemic viruses.

Publisher

Canadian Science Publishing

Subject

Genetics,Molecular Biology,Applied Microbiology and Biotechnology,General Medicine,Immunology,Microbiology

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