RevBayes: Bayesian Phylogenetic Inference Using Graphical Models and an Interactive Model-Specification Language.

Programs for Bayesian inference of phylogeny currently implement a unique and fixed suite of models. Consequently, users of these software packages are simultaneously forced to use a number of programs for a given study, while also lacking the freedom to explore models that have not been implemented by the developers of those programs. We developed a new open-source software package, RevBayes, to address these problems. RevBayes is entirely based on probabilistic graphical models, a powerful generic framework for specifying and analyzing statistical models. Phylogenetic-graphical models can be specified interactively in RevBayes, piece by piece, using a new succinct and intuitive language called Rev. Rev is similar to the R language and the BUGS model-specification language, and should be easy to learn for most users. The strength of RevBayes is the simplicity with which one can design, specify, and implement new and complex models. Fortunately, this tremendous flexibility does not come at the cost of slower computation; as we demonstrate, RevBayes outperforms competing software for several standard analyses. Compared with other programs, RevBayes has fewer black-box elements. Users need to explicitly specify each part of the model and analysis. Although this explicitness may initially be unfamiliar, we are convinced that this transparency will improve understanding of phylogenetic models in our field. Moreover, it will motivate the search for improvements to existing methods by brazenly exposing the model choices that we make to critical scrutiny. RevBayes is freely available at http://www.RevBayes.com [Bayesian inference; Graphical models; MCMC; statistical phylogenetics.]

Accelerating Bayesian inference for evolutionary biology models.

Bayesian inference is widely used nowadays and relies largely on Markov chain Monte Carlo (MCMC) methods. Evolutionary biology has greatly benefited from the developments of MCMC methods, but the design of more complex and realistic models and the ever growing availability of novel data is pushing the limits of the current use of these methods. We present a parallel Metropolis-Hastings (M-H) framework built with a novel combination of enhancements aimed towards parameter-rich and complex models. We show on a parameter-rich macroevolutionary model increases of the sampling speed up to 35 times with 32 processors when compared to a sequential M-H process. More importantly, our framework achieves up to a twentyfold faster convergence to estimate the posterior probability of phylogenetic trees using 32 processors when compared to the well-known software MrBayes for Bayesian inference of phylogenetic trees. https://bitbucket.org/XavMeyer/hogan. [email protected]. Supplementary data are available at Bioinformatics online

Using Fine-Grained Cycle Stealing to Improve Throughput, Efficiency and Response Time on a Dedicated Cluster while Maintaining Quality of Service

For various reasons, a dedicated cluster is not always fully utilized even when all of its processors are allocated to jobs. This occurs any time that a running job does not use 100% of each of the processors allocated to it. Keeping in mind the needs of both the cluster’s system administrators and its users, we would like to increase the throughput and efficiency of the cluster while maintaining or improving the average turnaround time of the jobs and the quality of service of the “primary” jobs originally scheduled on the cluster. To increase the throughput and efficiency of the cluster, we schedule background jobs to run concurrently with the primary jobs. However, to achieve our goal of maintaining or improving the average turnaround time of the jobs and the quality of service of the primary jobs, we investigate two methods of prioritizing the CPU usage of the primary and background jobs. The first method uses the existing “nice” mechanism in the 2.4 Linux kernel to give background processes a lower priority than primary processes. The second method involves modifying the 2.4 Linux kernel’s CPU scheduler to create a new guest process priority that prevents guest processes from running when primary processes are runnable. Our results come from empirical investigations using real production applications. Production runs using these applications are regularly performed in the dedicated cluster environment that we used for testing. Measurements of various statistics, such as wall time and CPU time, are taken directly from test runs that use these same production applications. This was helpful for comparison to results from models and synthetic applications. We found that using the existing nice mechanism significantly improves the throughput, efficiency and average turnaround time of the cluster but only at the expense of the quality of service of the primary jobs (primary job running times increased 5-25%). On the other hand, we can use the guest process priority to get similar improvements in throughput, efficiency and average turnaround time while not significantly impacting the quality of service of the primary jobs (primary job running times changed less than 1%)

Creation of functional viruses from non-functional cDNA clones obtained from an RNA virus population by the use of ancestral reconstruction

RNA viruses have the highest known mutation rates. Consequently it is likely that a high proportion of individual RNA virus genomes, isolated from an infected host, will contain lethal mutations and be non-functional. This is problematic if the aim is to clone and investigate high-fitness, functional cDNAs and may also pose problems for sequence-based analysis of viral evolution. To address these challenges we have performed a study of the evolution of classical swine fever virus (CSFV) using deep sequencing and analysis of 84 full-length cDNA clones, each representing individual genomes from a moderately virulent isolate. In addition to here being used as a model for RNA viruses generally, CSFV has high socioeconomic importance and remains a threat to animal welfare and pig production. We find that the majority of the investigated genomes are non-functional and only 12% produced infectious RNA transcripts. Full length sequencing of cDNA clones and deep sequencing of the parental population identified substitutions important for the observed phenotypes. The investigated cDNA clones were furthermore used as the basis for inferring the sequence of functional viruses. Since each unique clone must necessarily be the descendant of a functional ancestor, we hypothesized that it should be possible to produce functional clones by reconstructing ancestral sequences. To test this we used phylogenetic methods to infer two ancestral sequences, which were then reconstructed as cDNA clones. Viruses rescued from the reconstructed cDNAs were tested in cell culture and pigs. Both reconstructed ancestral genomes proved functional, and displayed distinct phenotypes in vitro and in vivo. We suggest that reconstruction of ancestral viruses is a useful tool for experimental and computational investigations of virulence and viral evolution. Importantly, ancestral reconstruction can be done even on the basis of a set of sequences that all correspond to non-functional variants

Does the choice of nucleotide substitution models matter topologically?

Background: In the context of a master level programming practical at the computer science department of the Karlsruhe Institute of Technology, we developed and make available an open-source code for testing all 203 possible nucleotide substitution models in the Maximum Likelihood (ML) setting under the common Akaike, corrected Akaike, and Bayesian information criteria. We address the question if model selection matters topologically, that is, if conducting ML inferences under the optimal, instead of a standard General Time Reversible model, yields different tree topologies. We also assess, to which degree models selected and trees inferred under the three standard criteria (AIC, AICc, BIC) differ. Finally, we assess if the definition of the sample size (#sites versus #sites × #taxa) yields different models and, as a consequence, different tree topologies. Results: We find that, all three factors (by order of impact: nucleotide model selection, information criterion used, sample size definition) can yield topologically substantially different final tree topologies (topological difference exceeding 10 %) for approximately 5 % of the tree inferences conducted on the 39 empirical datasets used in our study. Conclusions: We find that, using the best-fit nucleotide substitution model may change the final ML tree topology compared to an inference under a default GTR model. The effect is less pronounced when comparing distinct information criteria. Nonetheless, in some cases we did obtain substantial topological differences

Evolution of genes and repeats in the Nimrod superfamily

The recently identified Nimrod superfamily is characterized by the presence of a special type of EGF repeat, the NIM repeat, located right after a typical CCXGY/W amino acid motif. On the basis of structural features, nimrod genes can be divided into three types. The proteins encoded by Draper-type genes have an EMI domain at the N-terminal part and only one copy of the NIM motif, followed by a variable number of EGF-like repeats. The products of Nimrod B-type and Nimrod C-type genes (including the eater gene) have different kinds of N-terminal domains, and lack EGF-like repeats but contain a variable number of NIM repeats. Draper and Nimrod C-type (but not Nimrod B-type) proteins carry a transmembrane domain. Several members of the superfamily were claimed to function as receptors in phagocytosis and/or binding of bacteria, which indicates an important role in the cellular immunity and the elimination of apoptotic cells. In this paper, the evolution of the Nimrod superfamily is studied with various methods on the level of genes and repeats. A hypothesis is presented in which the NIM repeat, along with the EMI domain, emerged by structural reorganizations at the end of an EGF-like repeat chain, suggesting a mechanism for the formation of novel types of repeats. The analyses revealed diverse evolutionary patterns in the sequences containing multiple NIM repeats. Although in the Nimrod B and Nimrod C proteins show characteristics of independent evolution, many internal NIM repeats in Eater sequences seem to have undergone concerted evolution. An analysis of the nimrod genes has been performed using phylogenetic and other methods and an evolutionary scenario of the origin and diversification of the Nimrod superfamily is proposed. Our study presents an intriguing example how the evolution of multigene families may contribute to the complexity of the innate immune response