The evolutionary rates and tMRCAs estimated for the 1a and 1b datasets in nine genomic regions and over ORF by root-to-tip regression.

¶<p>In the calendar year. <b>*</b> The evolutionary rate is negative and tMRCA locates in the future.</p

Survey data of 13880 participants in Xiamen, China

Survey data of 13880 participants in Xiamen, Chin

Root-to-tip regression to estimate the tMRCAs and clock rates.

<p>A simple linear regression of the root-to-tip genentic distances against the sampling dates was performed using the Path-o-gen software. The root was determined by maximizing the coefficent of determinant R². The vertical axis measures the genetic distances between the samples and the root while the horizontal axis scales the sampling dates (year). For subtype 1a (A), the mean evolutionary rate (the slope of regression line) is 9.05E-4 substitution/site/year and the tMRCA (the X-intercept) is located at 1941. For subtype 1b (B), the mean evolutionary rate is 4.82E-4 and the tMRCA is located at 1808.</p

The Evolutionary Rates of HCV Estimated with Subtype 1a and 1b Sequences over the ORF Length and in Different Genomic Regions

<div><p>Background</p><p>Considerable 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.</p><p>Methods/Results</p><p>176 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.</p><p>Conclusion</p><p>Among 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.</p></div

The violin plots of the posterior evolutionary rate estimated using the uniform (0, 0.01) rate prior in the nine genomic regions and over the entire ORF of the subtype 1a (A panel) and 1b (B panel) datasets.

<p>Combined with the GTR+I+Γ substitution model and Bayesian skyline coalesent model, the MCMC procedures were run under three clock models, exoponetial, lognormal, and strict, respectively, using BEAST. The vertical axis measures the substitution rate multiplied by 10⁻³ (substitution/site/year). The horizontal axis indicates the nine genomic regions and the entire ORF. The left three panels show the results for the 1a dataset. The right three panels show the results for the 1b dataset. In each panel, two violins are separated in a small case on the right, which indicate the rates estimated for the routinely amplified partial Core-E1 (P-C/E1) and partial NS5B (P-NS5B) regions.</p

The median evolutionary rates and the tMRCAs estimated in the nine genomic regions and over the entire ORF of the subtype 1a and 1b datasets.

<p>Panels A, B, and C show the median evolutionary rates. Panels D, E, and F show the median tMRCAs. The blue columns represent the estimates for 1a. The red columns represent the estimates for 1b. The dash lines indicate the estimates for the entire ORF.</p

Odds ratios (95% confidence intervals) obtained from multivariable adjusted^a multilevel logistic models (model 1–6).

<p>^a All the six models used the same set of covariates: sex, residence, smoking history, dietary habit, alcohol drinking history, exercise practicing, sleep quality and number of chronic disease.</p><p>^bMLO: main lifetime occupation</p><p>Odds ratios (95% confidence intervals) obtained from multivariable adjusted<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0131331#t002fn001" target="_blank">^a</a> multilevel logistic models (model 1–6).</p

Odds ratios (95% confidence intervals) obtained from multivariable adjusted multilevel logistic models regressing health status on age and education (model 7), and age and MLO (model 8) accounting for their interactions.

<p>^aMLO: main lifetime occupation</p><p>Odds ratios (95% confidence intervals) obtained from multivariable adjusted multilevel logistic models regressing health status on age and education (model 7), and age and MLO (model 8) accounting for their interactions.</p

Basic characteristic of 13,880 participants according to the health status.

<p>^a confidence interval.</p><p>^b salt-light: salt intake<6g/day, salt-medium: salt intake 6-18g/day, salt heavy: salt intake >18g/day.</p><p>^c Sleep quality was self-rated.</p><p>Basic characteristic of 13,880 participants according to the health status.</p

Assessment of disability among the elderly in Xiamen of China a representative sample survey sample of 14,292 older adults

Assessment of disability among the elderly in Xiamen of China a representative sample survey sample of 14,292 older adult