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

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

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

Canalization of the evolutionary trajectory of the human influenza virus

Since its emergence in 1968, influenza A (H3N2) has evolved extensively in genotype and antigenic phenotype. Antigenic evolution occurs in the context of a two-dimensional 'antigenic map', while genetic evolution shows a characteristic ladder-like genealogical tree. Here, we use a large-scale individual-based model to show that evolution in a Euclidean antigenic space provides a remarkable correspondence between model behavior and the epidemiological, antigenic, genealogical and geographic patterns observed in influenza virus. We find that evolution away from existing human immunity results in rapid population turnover in the influenza virus and that this population turnover occurs primarily along a single antigenic axis. Thus, selective dynamics induce a canalized evolutionary trajectory, in which the evolutionary fate of the influenza population is surprisingly repeatable and hence, in theory, predictable.Comment: 29 pages, 5 figures, 10 supporting figure

Genesis and pathogenesis of the 1918 pandemic H1N1 influenza A virus

The source, timing, and geographical origin of the 1918–1920 pandemic influenza A virus have remained tenaciously obscure for nearly a century, as have the reasons for its unusual severity among young adults. Here, we reconstruct the origins of the pandemic virus and the classic swine influenza and (postpandemic) seasonal H1N1 lineages using a host-specific molecular clock approach that is demonstrably more accurate than previous methods. Our results suggest that the 1918 pandemic virus originated shortly before 1918 when a human H1 virus, which we infer emerged before ∼1907, acquired avian N1 neuraminidase and internal protein genes. We find that the resulting pandemic virus jumped directly to swine but was likely displaced in humans by ∼1922 by a reassortant with an antigenically distinct H1 HA. Hence, although the swine lineage was a direct descendent of the pandemic virus, the post-1918 seasonal H1N1 lineage evidently was not, at least for HA. These findings help resolve several seemingly disparate observations from 20th century influenza epidemiology, seroarcheology, and immunology. The phylogenetic results, combined with these other lines of evidence, suggest that the highmortality in 1918 among adults aged ∼20 to ∼40 y may have been due primarily to their childhood exposure to a doubly heterosubtypic putative H3N8 virus, which we estimate circulated from ∼1889–1900. All other age groups (except immunologically naive infants) were likely partially protected by childhood exposure to N1 and/or H1-related antigens. Similar processes may underlie age-specific mortality differences between seasonal H1N1 vs. H3N2 and human H5N1 vs. H7N9 infections