Abstract
BackgroundConsiderable progress has been made in the HCV evolutionary analysis, since the software BEAST was released. However, prior information, especially the prior evolutionary rate, which plays a critical role in BEAST analysis, is always difficult to ascertain due to various uncertainties. Providing a proper prior HCV evolutionary rate is thus of great importance.Methods/Results176 full-length sequences of HCV subtype 1a and 144 of 1b were assembled by taking into consideration the balance of the sampling dates and the even dispersion in phylogenetic trees. According to the HCV genomic organization and biological functions, each dataset was partitioned into nine genomic regions and two routinely amplified regions. A uniform prior rate was applied to the BEAST analysis for each region and also the entire ORF. All the obtained posterior rates for 1a are of a magnitude of 10−3 substitutions/site/year and in a bell-shaped distribution. Significantly lower rates were estimated for 1b and some of the rate distribution curves resulted in a one-sided truncation, particularly under the exponential model. This indicates that some of the rates for subtype 1b are less accurate, so they were adjusted by including more sequences to improve the temporal structure.ConclusionAmong the various HCV subtypes and genomic regions, the evolutionary patterns are dissimilar. Therefore, an applied estimation of the HCV epidemic history requires the proper selection of the rate priors, which should match the actual dataset so that they can fit for the subtype, the genomic region and even the length. By referencing the findings here, future evolutionary analysis of the HCV subtype 1a and 1b datasets may become more accurate and hence prove useful for tracing their patterns.
Highlights
The evolutionary analysis of hepatitis C virus (HCV) genetic sequences has entered a new era since the BEAST software (Bayesian Evolutionary Analysis by Sampling Trees) was released in 2003 [1,2,3]
An applied estimation of the HCV epidemic history requires the proper selection of the rate priors, which should match the actual dataset so that they can fit for the subtype, the genomic region and even the length
The retrospective changes in the HCV-infected population size can be illustrated as a Bayesian Skyline Plot (BSP) [4,5], in which the population size is measured on the vertical axis, while the elapsed time is scaled on the horizontal axis [6,7,8,9,10]
Summary
The evolutionary analysis of hepatitis C virus (HCV) genetic sequences has entered a new era since the BEAST software (Bayesian Evolutionary Analysis by Sampling Trees) was released in 2003 [1,2,3]. Using this software, the retrospective changes in the HCV-infected population size can be illustrated as a Bayesian Skyline Plot (BSP) [4,5], in which the population size is measured on the vertical axis, while the elapsed time is scaled on the horizontal axis [6,7,8,9,10]. If the sequences are sampled over a very short period of time, or at the extreme, a single time point, the evolutionary rate is completely determined by the prior information provided. Providing a proper prior HCV evolutionary rate is of great importance
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