Modeling the association of space, time, and host species with variation of the HA, NA, and NS genes of H5N1 highly pathogenic avian influenza viruses isolated from birds in Romania in 2005-2007.

Modeling the association of space, time, and host species with variation of the HA, NA, and NS genes of H5N1 highly pathogenic avian influenza viruses isolated from birds in Romania in 2005-2007. Alkhamis, M., Perez, A., Batey, N., Howard, W., Baillie, G., Watson, S., Franz, S., Focosi-Snyman, R., Onita, I., Cioranu, R., Turcitu, M., Kellam, P., Brown, I. H., & Breed, A. C. Avian diseases, 57(3):612–621, September, 2013.
doi abstract bibtex

Molecular characterization studies of a diverse collection of avian influenza viruses (AIVs) have demonstrated that AIVs' greatest genetic variability lies in the HA, NA, and NS genes. The objective here was to quantify the association between geographical locations, periods of time, and host species and pairwise nucleotide variation in the HA, NA, and NS genes of 70 isolates of H5N1 highly pathogenic avian influenza virus (HPAIV) collected from October 2005 to December 2007 from birds in Romania. A mixed-binomial Bayesian regression model was used to quantify the probability of nucleotide variation between isolates and its association with space, time, and host species. As expected for the three target genes, a higher probability of nucleotide differences (odds ratios [ORs] \textgreater 1) was found between viruses sampled from places at greater geographical distances from each other, viruses sampled over greater periods of time, and viruses derived from different species. The modeling approach in the present study maybe useful in further understanding the molecular epidemiology of H5N1 HPAI virus in bird populations. The methodology presented here will be useful in predicting the most likely genetic distance for any of the three gene segments of viruses that have not yet been isolated or sequenced based on space, time, and host species during the course of an epidemic.

@article{alkhamis_modeling_2013,
	title = {Modeling the association of space, time, and host species with variation of the {HA}, {NA}, and {NS} genes of {H5N1} highly pathogenic avian influenza viruses isolated from birds in {Romania} in 2005-2007.},
	volume = {57},
	issn = {0005-2086 0005-2086},
	doi = {10.1637/10494-011713-Reg.1},
	abstract = {Molecular characterization studies of a diverse collection of avian influenza viruses (AIVs) have demonstrated that AIVs' greatest genetic variability lies in  the HA, NA, and NS genes. The objective here was to quantify the association between geographical locations, periods of time, and host species and pairwise nucleotide variation in the HA, NA, and NS genes of 70 isolates of H5N1 highly pathogenic avian influenza virus (HPAIV) collected from October 2005 to December  2007 from birds in Romania. A mixed-binomial Bayesian regression model was used to quantify the probability of nucleotide variation between isolates and its association with space, time, and host species. As expected for the three target  genes, a higher probability of nucleotide differences (odds ratios [ORs] {\textgreater} 1) was found between viruses sampled from places at greater geographical distances from  each other, viruses sampled over greater periods of time, and viruses derived from different species. The modeling approach in the present study maybe useful in further understanding the molecular epidemiology of H5N1 HPAI virus in bird populations. The methodology presented here will be useful in predicting the most likely genetic distance for any of the three gene segments of viruses that have not yet been isolated or sequenced based on space, time, and host species during  the course of an epidemic.},
	language = {eng},
	number = {3},
	journal = {Avian diseases},
	author = {Alkhamis, Mohammad and Perez, Andres and Batey, Nicole and Howard, Wendy and Baillie, Greg and Watson, Simon and Franz, Stephanie and Focosi-Snyman, Raffaella and Onita, Iuliana and Cioranu, Raluca and Turcitu, Mihai and Kellam, Paul and Brown, Ian H. and Breed, Andrew C.},
	month = sep,
	year = {2013},
	pmid = {24283126},
	pmcid = {PMC3980047},
	keywords = {*Genetic Variation, Animals, Bayes Theorem, Birds, Geography, Hemagglutinin Glycoproteins, Influenza Virus/*genetics/metabolism, Influenza A Virus, H5N1 Subtype/*genetics/metabolism, Influenza in Birds/virology, Models, Theoretical, Molecular Epidemiology/*methods, Neuraminidase/*genetics/metabolism, Regression Analysis, Romania, Sequence Analysis, RNA/veterinary, Species Specificity, Time Factors, Viral Nonstructural Proteins/*genetics/metabolism, Viral Proteins/*genetics/metabolism},
	pages = {612--621},
}

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