Impact of Taxon Sampling on the Estimation of Rates of Evolution at Sites

Phylogenomic Perspective on the Relationships and Evolutionary History of the Major Otocephalan Lineages

The phylogeny of otocephalan fishes is the subject of broad controversy based on morphological and molecular evidence. The primary unresolved issue pertaining to this lineage relates to the origin of Characiphysi, especially the paraphyly of Characiformes. The considerable uncertainty associated with this lineage has precluded a greater understanding of the origin and evolution of the clade. Herein, a phylogenomic approach was applied to resolve this debate. By analyzing 10 sets of transcriptomic data generated in this study and 12 sets of high-throughput data available in public databases, we obtained 1,110 single-copy orthologous genes (935,265 sites for analysis) from 22 actinopterygians, including 14 otocephalan fishes from six orders: Clupeiformes, Gonorynchiformes, Cypriniformes, Siluriformes, Characiformes, and Gymnotiformes. Based on a selection of 125 nuclear genes screened from single-gene maximum likelihood (ML) analyses and sequence bias testing, well-established relationships among Otocephala were reconstructed. We suggested that Gymnotiformes are more closely related to Characiformes than to Siluriformes and Characiformes are possibly paraphyletic. We also estimated that Otocephala originated in the Early-Late Jurassic, which postdates most previous estimations, and hypothesized scenarios of the early historical biogeographies of major otocephalan lineages.

Framing the Salmonidae family phylogenetic portrait: a more complete picture from increased taxon sampling

Considerable research efforts have focused on elucidating the systematic relationships among salmonid fishes; an understanding of these patterns of relatedness will inform conservation- and fisheries-related issues, as well as provide a framework for investigating evolutionary mechanisms in the group. However, uncertainties persist in current Salmonidae phylogenies due to biological and methodological factors, and a comprehensive phylogeny including most representatives of the family could provide insight into the causes of these difficulties. Here we increase taxon sampling by including nearly all described salmonid species (n = 63) to present a time-calibrated and more complete portrait of Salmonidae using a combination of molecular markers and analytical techniques. This strategy improved resolution by increasing the signal-to-noise ratio and helped discriminate methodological and systematic errors from sources of difficulty associated with biological processes. Our results highlight novel aspects of salmonid evolution. First, we call into question the widely-accepted evolutionary relationships among sub-families and suggest that Thymallinae, rather than Coregoninae, is the sister group to the remainder of Salmonidae. Second, we find that some groups in Salmonidae are older than previously thought and that the mitochondrial rate of molecular divergence varies markedly among genes and clades. We estimate the age of the family to be 59.1 MY (CI: 63.2-58.1 MY) old, which likely corresponds to the timing of whole genome duplication in salmonids. The average, albeit highly variable, mitochondrial rate of molecular divergence was estimated as ~0.31%/MY (CI: 0.27-0.36%/MY). Finally, we suggest that some species require taxonomic revision, including two monotypic genera, Stenodus and Salvethymus. In addition, we resolve some relationships that have been notoriously difficult to discern and present a clearer picture of the evolution of the group. Our findings represent an important contribution to the systematics of Salmonidae, and provide a useful tool for addressing questions related to fundamental and applied evolutionary issues.

A phylogenetic mixture model for the identification of functionally divergent protein residues

MOTIVATION

To understand the evolution of molecular function within protein families, it is important to identify those amino acid residues responsible for functional divergence; i.e. those sites in a protein family that affect cofactor, protein or substrate binding preferences; affinity; catalysis; flexibility; or folding. Type I functional divergence (FD) results from changes in conservation (evolutionary rate) at a site between protein subfamilies, whereas type II FD occurs when there has been a shift in preferences for different amino acid chemical properties. A variety of methods have been developed for identifying both site types in protein subfamilies, both from phylogenetic and information-theoretic angles. However, evaluation of the performance of these methods has typically relied upon a handful of reasonably well-characterized biological datasets or analyses of a single biological example. While experimental validation of many truly functionally divergent sites (true positives) can be relatively straightforward, determining that particular sites do not contribute to functional divergence (i.e. false positives and true negatives) is much more difficult, resulting in noisy 'gold standard' examples.

RESULTS

We describe a novel, phylogeny-based functional divergence classifier, FunDi. Unlike previous approaches, FunDi uses a unified mixture model-based approach to detect type I and type II FD. To assess FunDi's overall classification performance relative to other methods, we introduce two methods for simulating functionally divergent datasets. We find that the FunDi method performs better than several other predictors over a wide variety of simulation conditions.

AVAILABILITY

http://rogerlab.biochem.dal.ca/Software

CONTACT

andrew.roger@dal.ca

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Linking fold, function and phylogeny: a comparative genomics view on protein (domain) evolution

Domains are the building blocks of all globular proteins and present one of the most useful levels at which protein function can be understood. Through recombination and duplication of a limited set of domains, proteomes evolved and the collection of protein superfamilies in an organism formed. As such, the presence of a shared domain can be regarded as an indicator of similar function and evolutionary history, but it does not necessarily imply it since convergent evolution may give rise to similar gene functions as well as architectures.Through the wealth of sequences and annotation data brought about by genomics, evolutionary links can be sought for via homology relationships and comparative genomics, structural modeling and phylogenetics. The goal hereby is not only to predict the function of newly discovered proteins, but also to spell out their pathway of evolution and, possibly, identify their most likely origin. This can ultimately help to understand protein function and functional relationships of protein families. Additionally, through comparison with transcriptional data, evolutionary data can be linked to gene (and genome) activity and thus allow for the identification of common principles behind fast evolving proteins and relatively stable ones.In this review, we describe the basic principles of studying protein (domain) evolution and illustrate recent developments in molecular evolution and give valuable new insights in the field of comparative genomics. As an example, we include here molecular models of the multiple PDZ domain protein MUPP-1 and present a simple comparative genomic view on its structural course of evolution.

The nature of protein domain evolution: shaping the interaction network

The proteomes that make up the collection of proteins in contemporary organisms evolved through recombination and duplication of a limited set of domains. These protein domains are essentially the main components of globular proteins and are the most principal level at which protein function and protein interactions can be understood. An important aspect of domain evolution is their atomic structure and biochemical function, which are both specified by the information in the amino acid sequence. Changes in this information may bring about new folds, functions and protein architectures. With the present and still increasing wealth of sequences and annotation data brought about by genomics, new evolutionary relationships are constantly being revealed, unknown structures modeled and phylogenies inferred. Such investigations not only help predict the function of newly discovered proteins, but also assist in mapping unforeseen pathways of evolution and reveal crucial, co-evolving inter- and intra-molecular interactions. In turn this will help us describe how protein domains shaped cellular interaction networks and the dynamics with which they are regulated in the cell. Additionally, these studies can be used for the design of new and optimized protein domains for therapy. In this review, we aim to describe the basic concepts of protein domain evolution and illustrate recent developments in molecular evolution that have provided valuable new insights in the field of comparative genomics and protein interaction networks.

Analyzing the relationship between sequence divergence and nodal support using Bayesian phylogenetic analyses

Determining the appropriate gene for phylogeny reconstruction can be a difficult process. Rapidly evolving genes tend to resolve recent relationships, but suffer from alignment issues and increased homoplasy among distantly related species. Conversely, slowly evolving genes generally perform best for deeper relationships, but lack sufficient variation to resolve recent relationships. We determine the relationship between sequence divergence and Bayesian phylogenetic reconstruction ability using both natural and simulated datasets. The natural data are based on 28 well-supported relationships within the subphylum Vertebrata. Sequences of 12 genes were acquired and Bayesian analyses were used to determine phylogenetic support for correct relationships. Simulated datasets were designed to determine whether an optimal range of sequence divergence exists across extreme phylogenetic conditions. Across all genes we found that an optimal range of divergence for resolving the correct relationships does exist, although this level of divergence expectedly depends on the distance metric. Simulated datasets show that an optimal range of sequence divergence exists across diverse topologies and models of evolution. We determine that a simple to measure property of genetic sequences (genetic distance) is related to phylogenic reconstruction ability in Bayesian analyses. This information should be useful for selecting the most informative gene to resolve any relationships, especially those that are difficult to resolve, as well as minimizing both cost and confounding information during project design.

Phylogeny, taxonomy, and evolution of the endothelin receptor gene family

A gene phylogeny provides the natural historical order to classify genes and to understand their functional, structural, and genomic diversity. The gene family of endothelin receptors (EDNR) is responsible for many key physiological and developmental processes of tetrapods and teleosts. This study provides a well-defined gene phylogeny for the EDNR family, which is used to classify its members and to assess their evolution. The EDNR phylogeny supports the recognition of the EDNRA, EDNRB, and EDNRC subfamilies, as well as more lineage-specific duplicates of teleosts and the African clawed frog. The duplications for these nominal genes are related to the various whole-genome amplifications of vertebrates, jawed vertebrates, fishes, and frog. The EDNR phylogeny also identifies several gene losses, including that of EDNRC from placental and marsupial (therian) mammals. When coupled with structural and biochemical information, site-specific analyses of evolutionary rate shifts reveal two distinct patterns of potential functional changes at the sequence level between therian versus non-therian EDNRA and EDNRB (i.e., between groups without and with EDNRC). An analysis of linkage maps and tetrapod synteny further suggests that the loss of therian EDNRC may be related to a chromosomal deletion in its common ancestor.

A simulation test bed for hypotheses of genome evolution

MOTIVATION

Microbial genomes undergo evolutionary processes such as gene family expansion and contraction, variable rates and patterns of sequence substitution and lateral genetic transfer. Simulation tools are essential for both the generation of data under different evolutionary models and the validation of analytical methods on such data. However, meaningful investigation of phenomena such as lateral genetic transfer requires the simultaneous consideration of many underlying evolutionary processes.

RESULTS

We have developed EvolSimulator, a software package that combines non-stationary sequence and gene family evolution together with models of lateral genetic transfer, within a customizable birth-death model of speciation and extinction. Here, we examine simulated data sets generated with EvolSimulator using existing statistical techniques from the evolutionary literature, showing in detail each component of the simulation strategy.

AVAILABILITY

Source code, manual and other information are freely available at www.bioinformatics.org.au/evolsim.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Phylogenetic analyses of parasites in the new millennium

Phylogenetic analysis has changed greatly in the last decade, and the most important themes in that change are reviewed here. Sequence data have become the most common source of phylogenetic information. This means that explicit models for evolutionary processes have been developed in a likelihood context, which allow more realistic data analyses. These models are becoming increasingly complex, both for nucleotides and for amino acid sequences, and so all such models need to be quantitatively assessed for each data set, to find the most appropriate one for use in any particular tree-building analysis. Bayesian analysis has been developed for tree-building and is greatly increasing in popularity. This is because a good heuristic strategy exists, which allows large data sets to be analyzed with complex evolutionary models in a practical time. Perhaps the most disappointing aspect of tree interpretation is the ongoing confusion between rooted and unrooted trees, while the effect of taxon and character sampling is often overlooked when constructing a phylogeny (especially in parasitology). The review finishes with a detailed consideration of the analysis of a multi-gene data set for several dozen taxa of Cryptosporidium (Apicomplexa), illustrating many of the theoretical and practical points highlighted in the review.

Using confidence set heuristics during topology search improves the robustness of phylogenetic inference

We examine the impact of likelihood surface characteristics on phylogenetic inference. Amino acid data sets simulated from topologies with branch length features chosen to represent varying degrees of difficulty for likelihood maximization are analyzed. We present situations where the tree found to achieve the global maximum in likelihood is often not equal to the true tree. We use the program covSEARCH to demonstrate how the use of adaptively sized pools of candidate trees that are updated using confidence tests results in solution sets that are highly likely to contain the true tree. This approach requires more computation than traditional maximum likelihood methods, hence covSEARCH is best suited to small to medium-sized alignments or large alignments with some constrained nodes. The majority rule consensus tree computed from the confidence sets also proves to be different from the generating topology. Although low phylogenetic signal in the input alignment can result in large confidence sets of trees, some biological information can still be obtained based on nodes that exhibit high support within the confidence set. Two real data examples are analyzed: mammal mitochondrial proteins and a small tubulin alignment. We conclude that the technique of confidence set optimization can significantly improve the robustness of phylogenetic inference at a reasonable computational cost. Additionally, when either very short internal branches or very long terminal branches are present, confident resolution of specific bipartitions or subtrees, rather than whole-tree phylogenies, may be the most realistic goal for phylogenetic methods.

Characterization and phylogenetic analysis of a cnidarian LMP X-like cDNA

Proteasomes are multisubunit protease complexes which are partly responsible for metabolism of intracellular, ubiquitinylated proteins. Vertebrates have adapted a second and specialized structure responsible for the generation of peptides presented to the adaptive immune system and is thus, commonly referred to as the immunoproteasome. This complex is assembled from paralogous copies of subunits belonging to the constitutive, housekeeping proteasome. The immunoproteasome is more efficient in the generation of peptides for display on major histocompatibility complex (MHC) molecules. Important components of this complex are the paralogous members, LMP X and 7; where the latter replaces the former in the assembly of the immunoproteasome of vertebrates. In this report, we describe an LMP X-like cDNA from an endosymbiont-free gorgonian coral, Swiftia exserta. Cnidarians predate the phylogenetic divergence of protostomes and deuterostomes (P-D split), and are becoming an essential model for our comprehension of immune system evolution. Phylogenetic analyses of available sequences indicates that invertebrate LMP X-like sequences are outgroups to vertebrate LMP X and LMP 7, and is in agreement with previous observations that the duplication event giving rise to the two rapidly diverging lineages of proteasomal subunits occurred before jawed fished divergence.

libcov: a C++ bioinformatic library to manipulate protein structures, sequence alignments and phylogeny

BACKGROUND

An increasing number of bioinformatics methods are considering the phylogenetic relationships between biological sequences. Implementing new methodologies using the maximum likelihood phylogenetic framework can be a time consuming task.

RESULTS

The bioinformatics library libcov is a collection of C++ classes that provides a high and low-level interface to maximum likelihood phylogenetics, sequence analysis and a data structure for structural biological methods. libcov can be used to compute likelihoods, search tree topologies, estimate site rates, cluster sequences, manipulate tree structures and compare phylogenies for a broad selection of applications.

CONCLUSION

Using this library, it is possible to rapidly prototype applications that use the sophistication of phylogenetic likelihoods without getting involved in a major software engineering project. libcov is thus a potentially valuable building block to develop in-house methodologies in the field of protein phylogenetics.