New insights into the hepatitis E virus genotype 3 phylodynamics and evolutionary history.

Hepatitis E virus (HEV) is an emergent hepatotropic virus endemic mainly in Asia and other developing areas. However, in the last decade it has been increasingly reported in high-income countries. Human infecting HEV strains are currently classified into four genotypes (1-4). Genotype 3 (HEV-3) is the prevalent virus genotype and the mostly associated with autochthonous and sporadic cases of HEV in developed areas. The evolutionary history of HEV worldwide remains largely unknown. In this study we reconstructed the spatiotemporal and population dynamics of HEV-3 at global scale, but with particular emphasis in South America, where case reports have increased dramatically in the last years. To achieve this, we applied a Bayesian coalescent-based approach to a comprehensive data set comprising 97 GenBank HEV-3 sequences for which the location and sampling date was documented. Our phylogenetic analyses suggest that the worldwide genetic diversity of HEV-3 can be grouped into two main Clades (I and II) with a Ƭmrca dated in approximately 320years ago (95% HPD: 420-236years) and that a unique independent introduction of HEV-3 seems to have occurred in Uruguay, where most of the human HEV cases in South America have been described. The phylodynamic inference indicates that the population size of this virus suffered substantial temporal variations after the second half of the 20th century. In this sense and conversely to what is postulated to date, we suggest that the worldwide effective population size of HEV-3 is not decreasing and that frequently sources of error in its estimates stem from assumptions that the analyzed sequences are derived from a single panmictic population. Novel insights on the global population dynamics of HEV are given. Additionally, this work constitutes an attempt to further describe in a Bayesian coalescent framework, the phylodynamics and evolutionary history of HEV-3 in the South American region.

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

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.

Inferring parameters shaping amino acid usage in prokaryotic genomes via Bayesian MCMC methods.

Molar content of guanine plus cytosine (G + C) and optimal growth temperature (OGT) are main factors characterizing the frequency distribution of amino acids in prokaryotes. Previous work, using multivariate exploratory methods, has emphasized ascertainment of biological factors underlying variability between genomes, but the strength of each identified factor on amino acid content has not been quantified. We combine the flexibility of the phylogenetic mixed model (PMM) with the power of Bayesian inference via Markov Chain Monte Carlo (MCMC) methods, to obtain a novel evolutionary picture of amino acid usage in prokaryotic genomes. We implement a Bayesian PMM which incorporates the feature that evolutionary history makes observed data interdependent. As in previous studies with PMM, we present a variance partition; however, attention is also given to the posterior distribution of "systematic effects" that may shed light about the relative importance of and relationships between evolutionary forces acting at the genomic level. In particular, we analyzed influences of G + C, OGT, and respiratory metabolism. Estimates of G + C effects were significant for amino acids coded by G + C or molar content of adenine plus thymine (A + T) in first and second bases. OGT had an important effect on 12 amino acids, probably reflecting complex patterns of protein modifications, to cope with varying environments. The effect of respiratory metabolism was less clear, probably due to the already reported association of G + C with aerobic metabolism. A "heritability" parameter was always high and significant, reinforcing the importance of accommodating phylogenetic relationships in these analyses. "Heritable" component correlations displayed a pattern that tended to cluster "pure" G + C (A + T) in first and second codon positions, suggesting an inherited departure from linear regression on G + C.