Phylogenetic extinction rates and comparative methodology

Species are not independent points for comparative analyses because closely related species share more evolutionary history and are therefore more similar to each other than distantly related species. The extent to which independent-contrast analysis reduces type I and type II statistical error in comparison with cross-species analysis depends on the relative branch lengths in the phylogenetic tree: as deeper branches get relatively long, cross-species analyses have more statistical type I and type II error. Phylogenetic trees reconstructed from extant species, under the assumptions of a branching process with speciation (branching) and extinction rates remaining constant through time, will have relatively longer deep branches as the extinction rate increases relative to the speciation rate. We compare the statistical performance of cross-species and independent-contrast analyses with varying relative extinction rates, and conclude that cross-species comparisons have unacceptable statistical performance, particularly when extinction rates are relatively high.     

Phylodynamics and human-mediated dispersal of a zoonotic virus

Understanding the role of humans in the dispersal of predominantly animal pathogens is essential for their control. We used newly developed Bayesian phylogeographic methods to unravel the dynamics and determinants of the spread of dog rabies virus (RABV) in North Africa. Each of the countries studied exhibited largely disconnected spatial dynamics with major geopolitical boundaries acting as barriers to gene flow. Road distances proved to be better predictors of the movement of dog RABV than accessibility or raw geographical distance, with occasional long distance and rapid spread within each of these countries. Using simulations that bridge phylodynamics and spatial epidemiology, we demonstrate that the contemporary viral distribution extends beyond that expected for RABV transmission in African dog populations. These results are strongly supportive of human-mediated dispersal, and demonstrate how an integrated phylogeographic approach will turn viral genetic data into a powerful asset for characterizing, predicting, and potentially controlling the spatial spread of pathogens.     

Phylogenetic Reconstruction of a Known HIV-1 CRF04_cpx Transmission Network Using Maximum Likelihood and Bayesian Methods

The CRF04_cpx strains of HIV-1 accounts for approximately 2–10% of the infected population in Greece, across different transmission risk groups. CRF04_cpx was the lineage documented in an HIV-1 transmission network in Thessalonica, northern Greece. Most of the transmissions occurred through unprotected heterosexual contacts between 1989 and 1993. Blood samples were available for six patients, obtained 6–10 years later, except for one patient sampled in 1991. Our objective was to examine whether the transmission history is compatible with the evolutionary tree of the virus, in partial gag, partial env, and partial gag+env. The inferred phylogenetic tree obtained using maximum likelihood and Bayesian methods in partial gag+env was much closer to the transmission tree than that using either env or gag separately. Our findings suggest that the epidemiological relationships among patients who have been infected by a common source correspond almost exactly to the evolutionary trees of the virus, given that enough phylogenetic signal is present in the alignment. Moreover, we found evidence that recombination is not the most parsimonious explanation for the phylogenetic incongruence between gag and env. For patients with known infection dates, the estimated dates of the coalescent events obtained using molecular clock calculations based on a newly developed Bayesian method in gag + env were in agreement with the actual infection dates.This article contains online supplementary material.Reviewing Editor: Dr. Lauren Ancel-MeyersIsolated sequences from patients belonging to the CRF04_cpx transmission network always correspond to partially characterized gag, env, and gag+env genomic regions.     

Estimating the rate of molecular evolution: incorporating non-contemporaneous sequences into maximum likelihood phylogenies

MOTIVATION: TipDate is a program that will use sequences that have been isolated at different dates to estimate their rate of molecular evolution. The program provides a maximum likelihood estimate of the rate and also the associated date of the most recent common ancestor of the sequences, under a model which assumes a constant rate of substitution (molecular clock) but which accommodates the dates of isolation. Confidence intervals for these parameters are also estimated. Results: The approach was applied to a sample of 17 dengue virus serotype 4 sequences, isolated at dates ranging from 1956 to 1994. The rate of substitution for this serotype was estimated to be 7.91 x 10(-4) substitutions per site per year (95% confidence intervals of 6.07 x 10(-4), 9.86 x 10(-4)). This is compatible with a date of 1922 (95% confidence intervals of 1900-1936) for the most recent common ancestor of these sequences. AVAILABILITY: TipDate can be obtained by WWW from http://evolve.zoo. ox.ac.uk/software. The package includes the source code, manual and example files. Both UNIX and Apple Macintosh versions are available from the same site.     

Estimation of an in vivo fitness landscape experienced by HIV-1 under drug selective pressure useful for prediction of drug resistance evolution during treatment

MOTIVATION: HIV-1 antiviral resistance is a major cause of antiviral treatment failure. The in vivo fitness landscape experienced by the virus in presence of treatment could in principle be used to determine both the susceptibility of the virus to the treatment and the genetic barrier to resistance. We propose a method to estimate this fitness landscape from cross-sectional clinical genetic sequence data of different subtypes, by reverse engineering the required selective pressure for HIV-1 sequences obtained from treatment naive patients, to evolve towards sequences obtained from treated patients. The method was evaluated for recovering 10 random fictive selective pressures in simulation experiments, and for modeling the selective pressure under treatment with the protease inhibitor nelfinavir. RESULTS: The estimated fitness function under nelfinavir treatment considered fitness contributions of 114 mutations at 48 sites. Estimated fitness correlated significantly with the in vitro resistance phenotype in 519 matched genotype-phenotype pairs (R(2) = 0.47 (0.41 - 0.54)) and variation in predicted evolution under nelfinavir selective pressure correlated significantly with observed in vivo evolution during nelfinavir treatment for 39 mutations (with FDR = 0.05). AVAILABILITY: The software is available on request from the authors, and data sets are available from http://jose.med.kuleuven.be/~kdforc0/nfv-fitness-data/.     

BEAGLE: an application programming interface and high-performance computing library for statistical phylogenetics

Phylogenetic inference is fundamental to our understanding of most aspects of the origin and evolution of life, and in recent years, there has been a concentration of interest in statistical approaches such as Bayesian inference and maximum likelihood estimation. Yet, for large data sets and realistic or interesting models of evolution, these approaches remain computationally demanding. High-throughput sequencing can yield data for thousands of taxa, but scaling to such problems using serial computing often necessitates the use of nonstatistical or approximate approaches. The recent emergence of graphics processing units (GPUs) provides an opportunity to leverage their excellent floating-point computational performance to accelerate statistical phylogenetic inference. A specialized library for phylogenetic calculation would allow existing software packages to make more effective use of available computer hardware, including GPUs. Adoption of a common library would also make it easier for other emerging computing architectures, such as field programmable gate arrays, to be used in the future. We present BEAGLE, an application programming interface (API) and library for high-performance statistical phylogenetic inference. The API provides a uniform interface for performing phylogenetic likelihood calculations on a variety of compute hardware platforms. The library includes a set of efficient implementations and can currently exploit hardware including GPUs using NVIDIA CUDA, central processing units (CPUs) with Streaming SIMD Extensions and related processor supplementary instruction sets, and multicore CPUs via OpenMP. To demonstrate the advantages of a common API, we have incorporated the library into several popular phylogenetic software packages. The BEAGLE library is free open source software licensed under the Lesser GPL and available from http://beagle-lib.googlecode.com. An example client program is available as public domain software.     

Heterotachy and tree building: a case study with plastids and eubacteria

The nature of heterotachy at the center of recent controversy over the relative performance of tree-building methods is different from the form of heterotachy that has been inferred in empirical studies. The latter have suggested that proportions of variable sites (p(var)) vary among orthologues and among paralogues. However, the strength of this inference, describing what may be one of the most important evolutionary properties of sequence data, has remained weak. Consequently, other models of sequence evolution have been proposed to explain some long-branch attraction (LBA) problems that could be attributed to differences in p(var). For an empirical case with plastid and eubacterial RNA polymerase sequences, we confirm using capture-recapture estimates and simulations that p(var) can differ among orthologues in anciently diverged evolutionary lineages. We find that parsimony and a least squares distance method that implements an overly simple model of sequence evolution are susceptible to LBA induced by this form of heterotachy. Although homogeneous maximum likelihood inference was found to be robust to model misspecification in our specific example, we caution against assuming that it will always be so.     

The epidemiology and iatrogenic transmission of hepatitis C virus in Egypt: a Bayesian coalescent approach

Hepatitis C virus (HCV) is a leading cause of liver cancer and cirrhosis, and Egypt has possibly the highest HCV prevalence worldwide. In this article we use a newly developed Bayesian inference framework to estimate the transmission dynamics of HCV in Egypt from sampled viral gene sequences, and to predict the public health impact of the virus. Our results indicate that the effective number of HCV infections in Egypt underwent rapid exponential growth between 1930 and 1955. The timing and speed of this spread provides quantitative genetic evidence that the Egyptian HCV epidemic was initiated and propagated by extensive antischistosomiasis injection campaigns. Although our results show that HCV transmission has since decreased, we conclude that HCV is likely to remain prevalent in Egypt for several decades. Our combined population genetic and epidemiological analysis provides detailed estimates of historical changes in Egyptian HCV prevalence. Because our results are consistent with a demographic scenario specified a priori, they also provide an objective test of inference methods based on the coalescent process.