Bayesian coalescent inference of hepatitis A virus populations: evolutionary rates and patterns | Zendy

Gonzalo Moratorio | Zendy; Mauro CostaMattioli | Zendy; Rosina Piovani | Zendy; Héctor Romero | Zendy; Héctor Musto | Zendy; Juan Cristina | Zendy

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Bayesian coalescent inference of hepatitis A virus populations: evolutionary rates and patterns

Author(s) -

Gonzalo Moratorio,

Mauro CostaMattioli,

Rosina Piovani,

Héctor Romero,

Héctor Musto,

Juan Cristina

Publication year - 2007

Publication title -

journal of general virology

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.55

H-Index - 167

eISSN - 1465-2099

pISSN - 0022-1317

DOI - 10.1099/vir.0.83038-0

Subject(s) - coalescent theory , biology , markov chain monte carlo , virology , bayesian probability , hepatitis a virus , bayesian inference , picornaviridae , inference , genetics , evolutionary biology , virus , statistics , phylogenetics , poliovirus , gene , mathematics , artificial intelligence , computer science

Hepatitis A virus (HAV) is a hepatotropic member of the family Picornaviridae. Previous studies suggested that HAV may evolve more slowly than other members of the family. To estimate HAV substitution rates precisely, we used a Bayesian Markov chain Monte Carlo (MCMC) approach on temporally sampled HAV VP1 full-length sequences from strains isolated in France. A mean rate of evolutionary change of 9.76 x 10(-4) nucleotide substitution per site per year was found. The results also revealed that the synonymous rate found for HAV is lower than that of other members of the family. Bayesian skyline plots revealed a sharp decline in the effective number of infections in 1996, coinciding with the introduction of HAV vaccine.

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