Bernhard Misof

A Phylogenomic Approach to Resolve the Arthropod Tree of Life

Arthropods were the first animals to conquer land and air. They encompass more than three quarters of all described living species. This extraordinary evolutionary success is based on an astoundingly wide array of highly adaptive body organizations. A lack of robustly resolved phylogenetic relationships, however, currently impedes the reliable reconstruction of the underlying evolutionary processes. Here, we show that phylogenomic data can substantially advance our understanding of arthropod evolution and resolve several conflicts among existing hypotheses. We assembled a data set of 233 taxa and 775 genes from which an optimally informative data set of 117 taxa and 129 genes was finally selected using new heuristics and compared with the unreduced data set. We included novel expressed sequence tag (EST) data for 11 species and all published phylogenomic data augmented by recently published EST data on taxonomically important arthropod taxa. This thorough sampling reduces the chance of obtaining spurious results due to stochastic effects of undersampling taxa and genes. Orthology prediction of genes, alignment masking tools, and selection of most informative genes due to a balanced taxa-gene ratio using new heuristics were established. Our optimized data set robustly resolves major arthropod relationships. We received strong support for a sister group relationship of onychophorans and euarthropods and strong support for a close association of tardigrades and cycloneuralia. Within pancrustaceans, our analyses yielded paraphyletic crustaceans and monophyletic hexapods and robustly resolved monophyletic endopterygote insects. However, our analyses also showed for few deep splits that were recently thought to be resolved, for example, the position of myriapods, a remarkable sensitivity to methods of analyses.

A Monte Carlo Approach Successfully Identifies Randomness in Multiple Sequence Alignments: A More Objective Means of Data Exclusion

Random similarity of sequences or sequence sections can impede phylogenetic analyses or the identification of gene homologies. Additionally, randomly similar sequences or ambiguously aligned sequence sections can negatively interfere with the estimation of substitution model parameters. Phylogenomic studies have shown that biases in model estimation and tree reconstructions do not disappear even with large data sets. In fact, these biases can become pronounced with more data. It is therefore important to identify possible random similarity within sequence alignments in advance of model estimation and tree reconstructions. Different approaches have been already suggested to identify and treat problematic alignment sections. We propose an alternative method that can identify random similarity within multiple sequence alignments (MSAs) based on Monte Carlo resampling within a sliding window. The method infers similarity profiles from pairwise sequence comparisons and subsequently calculates a consensus profile. This consensus profile represents a summary of all calculated single similarity profiles. In consequence, consensus profiles identify dominating patterns of nonrandom similarity or randomness within sections of MSAs. We show that the approach clearly identifies randomness in simulated and real data. After the exclusion of putative random sections, node support drastically improves in tree reconstructions of both data. It thus appears to be a powerful tool to identify possible biases of tree reconstructions or gene identification. The method is currently restricted to nucleotide data but will be extended to protein data in the near future.

Pancrustacean Phylogeny in the Light of New Phylogenomic Data: Support for Remipedia as the Possible Sister Group of Hexapoda

Remipedes are a small and enigmatic group of crustaceans, first described only 30 years ago. Analyses of both morphological and molecular data have recently suggested a close relationship between Remipedia and Hexapoda. If true, the remipedes occupy an important position in pancrustacean evolution and may be pivotal for understanding the evolutionary history of crustaceans and hexapods. However, it is important to test this hypothesis using new data and new types of analytical approaches. Here, we assembled a phylogenomic data set of 131 taxa, incorporating newly generated 454 expressed sequence tag (EST) data from six species of crustaceans, representing five lineages (Remipedia, Laevicaudata, Spinicaudata, Ostracoda, and Malacostraca). This data set includes all crustacean species for which EST data are available (46 species), and our largest alignment encompasses 866,479 amino acid positions and 1,886 genes. A series of phylogenomic analyses was performed to evaluate pancrustacean relationships. We significantly improved the quality of our data for predicting putative orthologous genes and for generating data subsets by matrix reduction procedures, thereby improving the signal to noise ratio in the data. Eight different data sets were constructed, representing various combinations of orthologous genes, data subsets, and taxa. Our results demonstrate that the different ways to compile an initial data set of core orthologs and the selection of data subsets by matrix reduction can have marked effects on the reconstructed phylogenetic trees. Nonetheless, all eight data sets strongly support Pancrustacea with Remipedia as the sister group to Hexapoda. This is the first time that a sister group relationship of Remipedia and Hexapoda has been inferred using a comprehensive phylogenomic data set that is based on EST data. We also show that selecting data subsets with increased overall signal can help to identify and prevent artifacts in phylogenetic analyses.

Parametric and non-parametric masking of randomness in sequence alignments can be improved and leads to better resolved trees

BackgroundMethods of alignment masking, which refers to the technique of excluding alignment blocks prior to tree reconstructions, have been successful in improving the signal-to-noise ratio in sequence alignments. However, the lack of formally well defined methods to identify randomness in sequence alignments has prevented a routine application of alignment masking. In this study, we compared the effects on tree reconstructions of the most commonly used profiling method (GBLOCKS) which uses a predefined set of rules in combination with alignment masking, with a new profiling approach (ALISCORE) based on Monte Carlo resampling within a sliding window, using different data sets and alignment methods. While the GBLOCKS approach excludes variable sections above a certain threshold which choice is left arbitrary, the ALISCORE algorithm is free of a priori rating of parameter space and therefore more objective.ResultsALISCORE was successfully extended to amino acids using a proportional model and empirical substitution matrices to score randomness in multiple sequence alignments. A complex bootstrap resampling leads to an even distribution of scores of randomly similar sequences to assess randomness of the observed sequence similarity. Testing performance on real data, both masking methods, GBLOCKS and ALISCORE, helped to improve tree resolution. The sliding window approach was less sensitive to different alignments of identical data sets and performed equally well on all data sets. Concurrently, ALISCORE is capable of dealing with different substitution patterns and heterogeneous base composition. ALISCORE and the most relaxed GBLOCKS gap parameter setting performed best on all data sets. Correspondingly, Neighbor-Net analyses showed the most decrease in conflict.ConclusionsAlignment masking improves signal-to-noise ratio in multiple sequence alignments prior to phylogenetic reconstruction. Given the robust performance of alignment profiling, alignment masking should routinely be used to improve tree reconstructions. Parametric methods of alignment profiling can be easily extended to more complex likelihood based models of sequence evolution which opens the possibility of further improvements.

Can comprehensive background knowledge be incorporated into substitution models to improve phylogenetic analyses? A case study on major arthropod relationships

BackgroundWhenever different data sets arrive at conflicting phylogenetic hypotheses, only testable causal explanations of sources of errors in at least one of the data sets allow us to critically choose among the conflicting hypotheses of relationships. The large (28S) and small (18S) subunit rRNAs are among the most popular markers for studies of deep phylogenies. However, some nodes supported by this data are suspected of being artifacts caused by peculiarities of the evolution of these molecules. Arthropod phylogeny is an especially controversial subject dotted with conflicting hypotheses which are dependent on data set and method of reconstruction. We assume that phylogenetic analyses based on these genes can be improved further i) by enlarging the taxon sample and ii) employing more realistic models of sequence evolution incorporating non-stationary substitution processes and iii) considering covariation and pairing of sites in rRNA-genes.ResultsWe analyzed a large set of arthropod sequences, applied new tools for quality control of data prior to tree reconstruction, and increased the biological realism of substitution models. Although the split-decomposition network indicated a high noise content in the data set, our measures were able to both improve the analyses and give causal explanations for some incongruities mentioned from analyses of rRNA sequences. However, misleading effects did not completely disappear.ConclusionAnalyses of data sets that result in ambiguous phylogenetic hypotheses demand for methods, which do not only filter stochastic noise, but likewise allow to differentiate phylogenetic signal from systematic biases. Such methods can only rely on our findings regarding the evolution of the analyzed data. Analyses on independent data sets then are crucial to test the plausibility of the results. Our approach can easily be extended to genomic data, as well, whereby layers of quality assessment are set up applicable to phylogenetic reconstructions in general.

A comprehensive analysis of bilaterian mitochondrial genomes and phylogeny

About 2800 mitochondrial genomes of Metazoa are present in NCBI RefSeq today, two thirds belonging to vertebrates. Metazoan phylogeny was recently challenged by large scale EST approaches (phylogenomics), stabilizing classical nodes while simultaneously supporting new sister group hypotheses. The use of mitochondrial data in deep phylogeny analyses was often criticized because of high substitution rates on nucleotides, large differences in amino acid substitution rate between taxa, and biases in nucleotide frequencies. Nevertheless, mitochondrial genome data might still be promising as it allows for a larger taxon sampling, while presenting a smaller amount of sequence information. We present the most comprehensive analysis of bilaterian relationships based on mitochondrial genome data. The analyzed data set comprises more than 650 mitochondrial genomes that have been chosen to represent a profound sample of the phylogenetic as well as sequence diversity. The results are based on high quality amino acid alignments obtained from a complete reannotation of the mitogenomic sequences from NCBI RefSeq database. However, the results failed to give support for many otherwise undisputed high-ranking taxa, like Mollusca, Hexapoda, Arthropoda, and suffer from extreme long branches of Nematoda, Platyhelminthes, and some other taxa. In order to identify the sources of misleading phylogenetic signals, we discuss several problems associated with mitochondrial genome data sets, e.g. the nucleotide and amino acid landscapes and a strong correlation of gene rearrangements with long branches.

Morphological and molecular evidence converge upon a robust phylogeny of the megadiverse Holometabola

We present the largest morphological character set ever compiled for Holometabola. This was made possible through an optimized acquisition of data. Based on our analyses and recently published hypotheses based on molecular data, we discuss higher‐level phylogeny and evolutionary changes. We comment on the information content of different character systems and discuss the role of morphology in the age of phylogenomics. Microcomputer tomography in combination with other techniques proved highly efficient for acquiring and documenting morphological data. Detailed anatomical information (356 characters) is now available for 30 representatives of all holometabolan orders. A combination of traditional and novel techniques complemented each other and rapidly provided reliable data. In addition, our approach facilitates documenting the anatomy of model organisms. Our results show little congruence with studies based on rRNA, but confirm most clades retrieved in a recent study based on nuclear genes: Holometabola excluding Hymenoptera, Coleopterida (= Strepsiptera + Coleoptera), Neuropterida excl. Neuroptera, and Mecoptera. Mecopterida (= Antliophora + Amphiesmenoptera) was retrieved only in Bayesian analyses. All orders except Megaloptera are monophyletic. Problems in the analyses are caused by taxa with numerous autapomorphies and/or inapplicable character states due to the loss of major structures (such as wings). Different factors have contributed to the evolutionary success of various holometabolan lineages. It is likely that good flying performance, the ability to occupy different habitats as larvae and adults, parasitism, liquid feeding, and co‐evolution with flowering plants have played important roles. We argue that even in the “age of phylogenomics”, comparative morphology will still play a vital role. In addition, morphology is essential for reconstructing major evolutionary transformations at the phenotypic level, for testing evolutionary scenarios, and for placing fossil taxa.
© The Willi Hennig Society 2010.

Accurate and efficient reconstruction of deep phylogenies from structured RNAs

Ribosomal RNA (rRNA) genes are probably the most frequently used data source in phylogenetic reconstruction. Individual columns of rRNA alignments are not independent as a consequence of their highly conserved secondary structures. Unless explicitly taken into account, these correlation can distort the phylogenetic signal and/or lead to gross overestimates of tree stability. Maximum likelihood and Bayesian approaches are of course amenable to using RNA-specific substitution models that treat conserved base pairs appropriately, but require accurate secondary structure models as input. So far, however, no accurate and easy-to-use tool has been available for computing structure-aware alignments and consensus structures that can deal with the large rRNAs. The RNAsalsa approach is designed to fill this gap. Capitalizing on the improved accuracy of pairwise consensus structures and informed by a priori knowledge of group-specific structural constraints, the tool provides both alignments and consensus structures that are of sufficient accuracy for routine phylogenetic analysis based on RNA-specific substitution models. The power of the approach is demonstrated using two rRNA data sets: a mitochondrial rRNA set of 26 Mammalia, and a collection of 28S nuclear rRNAs representative of the five major echinoderm groups.

How can a character be developmentally constrained despite variation in developmental pathways

A fundamental riddle of evolutionary developmental biology is the conservation of adult morphological patterns (Hall, 1992). Conservative patterns are either called body plans if they concern overall body design, or homologues if they concern parts of the body (Riedl, 1978; Roth, 1982; Sattler, 1984; Van Valen, 1982; Wagner, 1989a, 1989b). An adult pattern is considered conservative if it remains unchanged in spite of changes in function, as indicated by the original definition of homology by Owen, as a similarity of organs regardless of form and function (Owen, 1848). Conservation of anatomical features despite different adaptive pressures is naturally explained by developmental constraints (Wagner, 1986). However, this approach to explain the biological basis of homology is plagued by the fact that developmental pathways are often more variable than the characters that they produce (see Tab. 1) (Hall, 1992; Roth, 1988, 1991; Spemann, 1915; Wagner, 1989b). This is also true for any other application of the concept of developmental constraints. The widely held opinion that early stages of development are conservative because any early perturbation is likely to interfere with later development, is far from absolute, since a vast amount of data in comparative developmental biology speaks to developmental variation (see e.g. the examples in Tab. 1). The question then is, how can developmental constraints on adult variation be reconciled with the fact of developmental variation?

The evolutionary history of holometabolous insects inferred from transcriptome-based phylogeny and comprehensive morphological data

BackgroundDespite considerable progress in systematics, a comprehensive scenario of the evolution of phenotypic characters in the mega-diverse Holometabola based on a solid phylogenetic hypothesis was still missing. We addressed this issue by de novo sequencing transcriptome libraries of representatives of all orders of holometabolan insects (13 species in total) and by using a previously published extensive morphological dataset. We tested competing phylogenetic hypotheses by analyzing various specifically designed sets of amino acid sequence data, using maximum likelihood (ML) based tree inference and Four-cluster Likelihood Mapping (FcLM). By maximum parsimony-based mapping of the morphological data on the phylogenetic relationships we traced evolutionary transformations at the phenotypic level and reconstructed the groundplan of Holometabola and of selected subgroups.ResultsIn our analysis of the amino acid sequence data of 1,343 single-copy orthologous genes, Hymenoptera are placed as sister group to all remaining holometabolan orders, i.e., to a clade Aparaglossata, comprising two monophyletic subunits Mecopterida (Amphiesmenoptera + Antliophora) and Neuropteroidea (Neuropterida + Coleopterida). The monophyly of Coleopterida (Coleoptera and Strepsiptera) remains ambiguous in the analyses of the transcriptome data, but appears likely based on the morphological data. Highly supported relationships within Neuropterida and Antliophora are Raphidioptera + (Neuroptera + monophyletic Megaloptera), and Diptera + (Siphonaptera + Mecoptera). ML tree inference and FcLM yielded largely congruent results. However, FcLM, which was applied here for the first time to large phylogenomic supermatrices, displayed additional signal in the datasets that was not identified in the ML trees.ConclusionsOur phylogenetic results imply that an orthognathous larva belongs to the groundplan of Holometabola, with compound eyes and well-developed thoracic legs, externally feeding on plants or fungi. Ancestral larvae of Aparaglossata were prognathous, equipped with single larval eyes (stemmata), and possibly agile and predacious. Ancestral holometabolan adults likely resembled in their morphology the groundplan of adult neopteran insects. Within Aparaglossata, the adult’s flight apparatus and ovipositor underwent strong modifications. We show that the combination of well-resolved phylogenies obtained by phylogenomic analyses and well-documented extensive morphological datasets is an appropriate basis for reconstructing complex morphological transformations and for the inference of evolutionary histories.