Global phylogeography and evolution of chelonid fibropapilloma-associated herpesvirus

A global phylogeny for chelonid fibropapilloma-associated herpesvirus (CFPHV), the most likely aetiological agent of fibropapillomatosis (FP) in sea turtles, was inferred, using dated sequences, through Bayesian Markov chain Monte Carlo analysis and used to estimate the virus evolutionary rate independent of the evolution of the host, and to resolve the phylogenetic positions of new haplotypes from Puerto Rico and the Gulf of Guinea. Four phylogeographical groups were identified: eastern Pacific, western Atlantic/eastern Caribbean, mid-west Pacific and Atlantic. The latter comprises the Gulf of Guinea and Puerto Rico, suggesting recent virus gene flow between these two regions. One virus haplotype from Florida remained elusive, representing either an independent lineage sharing a common ancestor with all other identified virus variants or an Atlantic representative of the lineage giving rise to the eastern Pacific group. The virus evolutionary rate ranged from 1.62x10(-4) to 2.22x10(-4) substitutions per site per year, which is much faster than what is expected for a herpesvirus. The mean time for the most recent common ancestor of the modern virus variants was estimated at 192.90-429.71 years ago, which, although more recent than previous estimates, still supports an interpretation that the global FP pandemic is not the result of a recent acquisition of a virulence mutation(s). The phylogeographical pattern obtained seems partially to reflect sea turtle movements, whereas altered environments appear to be implicated in current FP outbreaks and in the modern evolutionary history of CFPHV.DNER-PR; US NMFS (NMFS-NOAA) [NA08NMF4720436]; US-Fish and Wildlife Service (USFWS); Sociedad Chelonia; WIDECAST; US Environmental Protection Agency (US-EPA); Lisbon Oceanarium, Portugal; Interdisciplinary Research Center for Animal Health of the Faculty of Veterinary Medicine of the Technical University of Lisbon (FMV/TUL)info:eu-repo/semantics/publishedVersio

πBUSS:a parallel BEAST/BEAGLE utility for sequence simulation under complex evolutionary scenarios

Background: Simulated nucleotide or amino acid sequences are frequently used to assess the performance of phylogenetic reconstruction methods. BEAST, a Bayesian statistical framework that focuses on reconstructing time-calibrated molecular evolutionary processes, supports a wide array of evolutionary models, but lacked matching machinery for simulation of character evolution along phylogenies. Results: We present a flexible Monte Carlo simulation tool, called piBUSS, that employs the BEAGLE high performance library for phylogenetic computations within BEAST to rapidly generate large sequence alignments under complex evolutionary models. piBUSS sports a user-friendly graphical user interface (GUI) that allows combining a rich array of models across an arbitrary number of partitions. A command-line interface mirrors the options available through the GUI and facilitates scripting in large-scale simulation studies. Analogous to BEAST model and analysis setup, more advanced simulation options are supported through an extensible markup language (XML) specification, which in addition to generating sequence output, also allows users to combine simulation and analysis in a single BEAST run. Conclusions: piBUSS offers a unique combination of flexibility and ease-of-use for sequence simulation under realistic evolutionary scenarios. Through different interfaces, piBUSS supports simulation studies ranging from modest endeavors for illustrative purposes to complex and large-scale assessments of evolutionary inference procedures. The software aims at implementing new models and data types that are continuously being developed as part of BEAST/BEAGLE.Comment: 13 pages, 2 figures, 1 tabl

Molecular footprint of drug-selective pressure in a human immunodeficiency virus transmission chain

Known human immunodeficiency virus (HIV) transmission histories are invaluable models for investigating the evolutionary and transmission dynamics of the virus and to assess the accuracy of phylogenetic reconstructions. Here we have characterized an HIV-1 transmission chain consisting of nine infected patients, almost all of whom were treated with antiviral drugs at later stages of infection. Partial pol and env gp41 regions of the HIV genome were directly sequenced from plasma viral RNA for at least one sample from each patient. Phylogenetic analyses in pol using likelihood methods inferred an evolutionary history not fully compatible with the known transmission history. This could be attributed to parallel evolution of drug resistance mutations resulting in the incorrect clustering of multidrug-resistant virus. On the other hand, a fully compatible phylogenetic tree was reconstructed from the env sequences. We were able to identify and quantify the molecular footprint of drug-selective pressure in pol using maximum likelihood inference under different codon substitution models. An increased fixation rate of mutations in the HIV population of the multidrug-resistant patient was demonstrated using molecular clock modeling. We show that molecular evolutionary analyses, guided by a known transmission history, can reveal the presence of confounding factors like natural selection and caution should be taken when accurate descriptions of HIV evolution are required.status: publishe

SPREAD: spatial phylogenetic reconstruction of evolutionary dynamics

Summary: SPREAD is a user-friendly, cross-platform application to analyze and visualize Bayesian phylogeographic reconstructions incorporating spatial–temporal diffusion. The software maps phylogenies annotated with both discrete and continuous spatial information and can export high-dimensional posterior summaries to keyhole markup language (KML) for animation of the spatial diffusion through time in virtual globe software. In addition, SPREAD implements Bayes factor calculation to evaluate the support for hypotheses of historical diffusion among pairs of discrete locations based on Bayesian stochastic search variable selection estimates. SPREAD takes advantage of multicore architectures to process large joint posterior distributions of phylogenies and their spatial diffusion and produces visualizations as compelling and interpretable statistical summaries for the different spatial projections

Adaptive MCMC in Bayesian phylogenetics: an application to analyzing partitioned data in BEAST

Advances in sequencing technology continue to deliver increasingly large molecular sequence datasets that are often heavily partitioned in order to accurately model the underlying evolutionary processes. In phylogenetic analyses, partitioning strategies involve estimating conditionally independent models of molecular evolution for different genes and different positions within those genes, requiring a large number of evolutionary parameters that have to be estimated, leading to an increased computational burden for such analyses. The past two decades have also seen the rise of multi-core processors, both in the central processing unit (CPU) and Graphics processing unit processor markets, enabling massively parallel computations that are not yet fully exploited by many software packages for multipartite analyses.status: publishe