Viral adaptation rate is negatively correlated with viral population size in 24 pediatric HIV infections (Spearman’s rank correlation: p < 0.01).

<p>The trend-line was estimated using a weighted regression analysis (weighted regression: b = -0.0054, p < 0.01). The inset illustrates the bootstrap distribution of the slope, estimated from weighted regression, which indicates that the slope is less than zero. Data points are labeled by color according to the disease progression category of each patient as follows: slow non-progressors (SNP, dark blue), moderate non-progressors (MNP, light blue), moderate progressors (MP, orange), and rapid progressors (RP, pink). Error bars representing the uncertainty in our estimate were obtained using the bootstrap procedure described in [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004694#pcbi.1004694.ref025" target="_blank">25</a>]. Specifically, the error bars depict the lower and upper quartile estimates from 250 bootstrap samples.</p

This figure is adapted from Fig 2a in Grenfell et al. [41].

<p>A simple population genetics model predicts that absolute within-host viral adaptation rate varies non-linearly with host immune response, which has a opposing effects on viral population size and the strength of immune selection. The left-hand side of the curve (A) can explain the negative relationship observed in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004694#pcbi.1004694.g002" target="_blank">Fig 2</a>: a weak immune response corresponds to large viral population but lower selective pressure. The shaded parts of the curve indicated by B and C predicts an absence or a positive relationship, respectively, between viral adaptation rate and viral population size.</p

A schematic diagram that outlines the method used to estimate the rate of molecular adaptation in serially-sampled populations.

<p>(A) Viral sequences sampled from an earlier time point (the outgroup alignment) are compared with sequences sampled at a later time point (the main alignment). Mutations on the internal branch leading to the later sample (dark grey) represent nucleotide fixations, while all remaining mutations (light grey) correspond to polymorphisms in the later sample. Replacement (non-synonymous; diamonds) and silent (synonymous; circles) mutations are distinguished. (B) A consensus of the sequences from the earlier time point is used to identify whether fixations and polymorphisms are ancestral or derived. In this example, mutation has occurred in 7 out of 9 sites in the main alignment. (C) Nucleotide site-frequencies (i.e. the frequency of each mutation in the main alignment) are calculated and probabilistically assigned to three site-frequency ranges for both silent and replacement changes. Under neutral evolution, the ratio of replacement to silent changes in the mid site-frequency range, ρ_m/ σ_m, is expected to equal to the corresponding ratio in the high site-frequency range (ρ_h/ σ_h). Excess replacement changes in the high site-frequency range thus represent adaptive substitutions driven by positive selection (<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004694#pcbi.1004694.e002" target="_blank">eq 2</a>). Note that invariant sites in the alignment (i.e. sites 6 and 7 in panel B) are assigned as silent or replacement using the degeneracy of the genetic code (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004694#pcbi.1004694.s006" target="_blank">S2 Table</a> for details). Further, the site-frequency of invariant sites is probabilistically assigned using a Beta-binomial model (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004694#sec002" target="_blank">Materials and Methods</a>).</p

The number of high-frequency replacement polymorphisms (scaled by the number of codons in each alignment and the number of years of observation) is not correlated with viral population size (Spearman’s rank correlation; p > 0.05).

<p>If natural selection were weak compared to genetic drift then a negative correlation would be expected, due to an increased fixation of slightly deleterious mutations in populations of small size. The data points are labeled using the color scheme employed in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004694#pcbi.1004694.g002" target="_blank">Fig 2</a>.</p

Aspects of the evolutionary dynamics of chronic HCV infection.

<p>(a), (b), and (c) show various analyses of HCV gene sequences (E1E2 region) sampled longitudinally from a single infected individual (Pt11 in <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1002656#ppat.1002656-Farci2" target="_blank">[7]</a>). Sequences were obtained from serum at twelve occasions over 15 years. All results are placed on the same time scale (top). (a) The phylogeny of the sampled sequences was reconstructed using a molecular clock model, such that branch lengths represent time (calculated using BEAST v1.6.2 <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1002656#ppat.1002656-Drummond1" target="_blank">[30]</a>). To aid explanation, branches have been grouped into four lineages, indicated by colour. Lineages 3 and 4 co-exist between months 30 and 145. Lineage 4 was present in the patient but undetected at months 65, 116, 132, 145. (b) The average diversity of sequences obtained at each sampling time (mean pairwise genetic distance; calculated using MEGA v4 <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1002656#ppat.1002656-Tamura1" target="_blank">[31]</a>). The vertical scale represents mean substitutions per site. Sample diversity is notably higher at month 82 because both lineages 3 and 4 are detected. (c) An estimate of the genetic diversity of the whole viral quasispecies through time. This figure was calculated using the Bayesian skyline plot method in BEAST <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1002656#ppat.1002656-Drummond1" target="_blank">[30]</a>, <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1002656#ppat.1002656-Drummond2" target="_blank">[32]</a>, which takes into account both sampled and unsampled lineages. The shaded area shows the 95% uncertainty range around the estimate (solid line). (d) A new evolutionary model of HCV infection, as applied to the patient data shown in (a), (b), and (c). Each cartoon represents the state of infection at a different time, as indicated by the shaded areas. Circles represent different sub-populations of HCV-infected cells within the liver (or other sites of extra-hepatic replication), coloured to correspond to the lineages in (a). Solid arrows indicate the fluctuating detection of HCV lineages in serum through time.</p

Phylogenetic structure.

<p>A maximum clade credibility phylogeny is shown for one representative subject from each patient group (HCV untreated, HCV treated, and HIV). Branches are scaled by time. Superimposed on each phylogeny, on the same timescale, is the estimated Bayesian skyline plot for that subject. The light grey line indicates the mean skyline plot estimate of effective population size through time. The darker grey areas indicate the 95% highest posterior density credible interval for that estimate. The distance between dotted vertical lines indicates one year. (a) Patient U3 from the HCV untreated group. (b) Patient T1 from the treated HCV group. (c) Patient H2 from the HIV cohort.</p

Estimation of evolutionary rates for codon partitions.

<p>Evolutionary rates for the two codon partitions (1+2 cp and 3cp) were estimated separately for each subject. Black squares indicate the mean evolutionary rate for 1+2cp sites, and white squares indicate the mean evolutionary rate for 3cp sites. The 95% HPD intervals for each estimate are indicated by vertical error bars.</p

Ratio of 1+2cp and 3cp rates for each patient from the three different patient cohorts.

<p>Ratio of 1+2cp and 3cp rates for each patient from the three different patient cohorts.</p

Estimation of evolutionary rates.

<p>(a) Estimated mean viral evolutionary rate for each subject in the three groups (HCV untreated, HCV treated, and HIV). (b) Estimated coefficient of variation (COV) of the relaxed molecular clock, for each subject. Filled circles indicate estimates obtained under a molecular clock with a log-normal distribution of among-branch rates. Open circles indicate estimates obtained under a molecular clock with a skew-normal rate distribution of among-branch rates. The 95% highest posterior density (HPD) intervals for each estimate are indicated by vertical error bars.</p

Per-sample summary statistics.

<p>(a) Mean pairwise nucleotide diversity (MPD) for each time-point and each subject. The relative width of each circle represents MPD. Each column represents the values for one subject (U1-7, T1-8 and H1-9). The y-axis show the time of sampling. For subjects U1-7 and H1-9, time zero is the known (or closely estimated) date of infection. For subjects T1-8, time zero equals the date of the first sample. (b) The distribution of MPD values is shown for each group of patients. Panels (c), (d) and (e) show Tajima’s D estimates for each time-point and each subject. The different colours indicate different patients. The estimates above 2 and below -2 (indicated by dashed horizontal lines) correspond to significant deviation from neutrality. (c) Untreated HCV subjects U1-7. (d) Treated HCV subjects T1-8. (e) HIV subjects H1-9.</p