Rooting the eutherian tree: the power and pitfalls of phylogenomics

Background  

Ongoing genome sequencing projects have led to a phylogenetic approach based on genome-scale data (phylogenomics), which is beginning to shed light on longstanding unresolved phylogenetic issues. The use of large datasets in phylogenomic analysis results in a global increase in resolution due to a decrease in sampling error. However, a fully resolved tree can still be wrong if the phylogenetic inference is biased.     

Phylogenomic Subsampling and the Search for Phylogenetically Reliable Loci

Phylogenomic subsampling is a procedure by which small sets of loci are selected from large genome-scale data sets and used for phylogenetic inference. This step is often motivated by either computational limitations associated with the use of complex inference methods or as a means of testing the robustness of phylogenetic results by discarding loci that are deemed potentially misleading. Although many alternative methods of phylogenomic subsampling have been proposed, little effort has gone into comparing their behavior across different data sets. Here, I calculate multiple gene properties for a range of phylogenomic data sets spanning animal, fungal, and plant clades, uncovering a remarkable predictability in their patterns of covariance. I also show how these patterns provide a means for ordering loci by both their rate of evolution and their relative phylogenetic usefulness. This method of retrieving phylogenetically useful loci is found to be among the top performing when compared with alternative subsampling protocols. Relatively common approaches such as minimizing potential sources of systematic bias or increasing the clock-likeness of the data are found to fare worse than selecting loci at random. Likewise, the general utility of rate-based subsampling is found to be limited: loci evolving at both low and high rates are among the least effective, and even those evolving at optimal rates can still widely differ in usefulness. This study shows that many common subsampling approaches introduce unintended effects in off-target gene properties and proposes an alternative multivariate method that simultaneously optimizes phylogenetic signal while controlling for known sources of bias.     

A consistent phylogenetic backbone for the fungi

The kingdom of fungi provides model organisms for biotechnology, cell biology, genetics, and life sciences in general. Only when their phylogenetic relationships are stably resolved, can individual results from fungal research be integrated into a holistic picture of biology. However, and despite recent progress, many deep relationships within the fungi remain unclear. Here, we present the first phylogenomic study of an entire eukaryotic kingdom that uses a consistency criterion to strengthen phylogenetic conclusions. We reason that branches (splits) recovered with independent data and different tree reconstruction methods are likely to reflect true evolutionary relationships. Two complementary phylogenomic data sets based on 99 fungal genomes and 109 fungal expressed sequence tag (EST) sets analyzed with four different tree reconstruction methods shed light from different angles on the fungal tree of life. Eleven additional data sets address specifically the phylogenetic position of Blastocladiomycota, Ustilaginomycotina, and Dothideomycetes, respectively. The combined evidence from the resulting trees supports the deep-level stability of the fungal groups toward a comprehensive natural system of the fungi. In addition, our analysis reveals methodologically interesting aspects. Enrichment for EST encoded data-a common practice in phylogenomic analyses-introduces a strong bias toward slowly evolving and functionally correlated genes. Consequently, the generalization of phylogenomic data sets as collections of randomly selected genes cannot be taken for granted. A thorough characterization of the data to assess possible influences on the tree reconstruction should therefore become a standard in phylogenomic analyses.     

tRNA Signatures Reveal a Polyphyletic Origin of SAR11 Strains among Alphaproteobacteria

Molecular phylogenetics and phylogenomics are subject to noise from horizontal gene transfer (HGT) and bias from convergence in macromolecular compositions. Extensive variation in size, structure and base composition of alphaproteobacterial genomes has complicated their phylogenomics, sparking controversy over the origins and closest relatives of the SAR11 strains. SAR11 are highly abundant, cosmopolitan aquatic Alphaproteobacteria with streamlined, A+T-biased genomes. A dominant view holds that SAR11 are monophyletic and related to both Rickettsiales and the ancestor of mitochondria. Other studies dispute this, finding evidence of a polyphyletic origin of SAR11 with most strains distantly related to Rickettsiales. Although careful evolutionary modeling can reduce bias and noise in phylogenomic inference, entirely different approaches may be useful to extract robust phylogenetic signals from genomes. Here we develop simple phyloclassifiers from bioinformatically derived tRNA Class-Informative Features (CIFs), features predicted to target tRNAs for specific interactions within the tRNA interaction network. Our tRNA CIF-based model robustly and accurately classifies alphaproteobacterial genomes into one of seven undisputed monophyletic orders or families, despite great variability in tRNA gene complement sizes and base compositions. Our model robustly rejects monophyly of SAR11, classifying all but one strain as Rhizobiales with strong statistical support. Yet remarkably, conventional phylogenetic analysis of tRNAs classifies all SAR11 strains identically as Rickettsiales. We attribute this discrepancy to convergence of SAR11 and Rickettsiales tRNA base compositions. Thus, tRNA CIFs appear more robust to compositional convergence than tRNA sequences generally. Our results suggest that tRNA-CIF-based phyloclassification is robust to HGT of components of the tRNA interaction network, such as aminoacyl-tRNA synthetases. We explain why tRNAs are especially advantageous for prediction of traits governing macromolecular interactions from genomic data, and why such traits may be advantageous in the search for robust signals to address difficult problems in classification and phylogeny.     

Phylogenomics and the flowering plant tree of life

The advances accelerated by next-generation sequencing and long-read sequencing technologies continue to provide an impetus for plant phylogenetic study.In the past decade,a large number of phylogenetic studies adopting hundreds to thousands of genes across a wealth of clades have emerged and ushered plant phylogenetics and evolution into a new era.In the meantime,a roadmap for researchers when making decisions across different approaches for their phylogenomic research design is imminent.This r...     

The evolutionary origin of Xanthomonadales genomes and the nature of the horizontal gene transfer process

Determining the influence of horizontal gene transfer (HGT) on phylogenomic analyses and the retrieval of a tree of life is relevant for our understanding of microbial genome evolution. It is particularly difficult to differentiate between phylogenetic incongruence due to noise and that resulting from HGT. We have performed a large-scale, detailed evolutionary analysis of the different phylogenetic signals present in the genomes of Xanthomonadales, a group of Proteobacteria. We show that the presence of phylogenetic noise is not an obstacle to infer past and present HGTs during their evolution. The scenario derived from this analysis and other recently published reports reflect the confounding effects on bacterial phylogenomics of past and present HGT. Although transfers between closely related species are difficult to detect in genome-scale phylogenetic analyses, past transfers to the ancestor of extant groups appear as conflicting signals that occasionally might make impossible to determine the evolutionary origin of the whole genome.     

Long-Branch Attraction Bias and Inconsistency in Bayesian Phylogenetics

Bayesian inference (BI) of phylogenetic relationships uses the same probabilistic models of evolution as its precursor maximum likelihood (ML), so BI has generally been assumed to share ML''s desirable statistical properties, such as largely unbiased inference of topology given an accurate model and increasingly reliable inferences as the amount of data increases. Here we show that BI, unlike ML, is biased in favor of topologies that group long branches together, even when the true model and prior distributions of evolutionary parameters over a group of phylogenies are known. Using experimental simulation studies and numerical and mathematical analyses, we show that this bias becomes more severe as more data are analyzed, causing BI to infer an incorrect tree as the maximum a posteriori phylogeny with asymptotically high support as sequence length approaches infinity. BI''s long branch attraction bias is relatively weak when the true model is simple but becomes pronounced when sequence sites evolve heterogeneously, even when this complexity is incorporated in the model. This bias—which is apparent under both controlled simulation conditions and in analyses of empirical sequence data—also makes BI less efficient and less robust to the use of an incorrect evolutionary model than ML. Surprisingly, BI''s bias is caused by one of the method''s stated advantages—that it incorporates uncertainty about branch lengths by integrating over a distribution of possible values instead of estimating them from the data, as ML does. Our findings suggest that trees inferred using BI should be interpreted with caution and that ML may be a more reliable framework for modern phylogenetic analysis.     

Assessing support for Blaberoidea phylogeny suggests optimal locus quality

Phylogenomics seeks to use next‐generation data to robustly infer an organism's evolutionary history. Yet, the practical caveats of phylogenomics motivate investigation of improved efficiency, particularly when quality of phylogenies are questionable. To achieve improvements, one goal is to maintain or enhance the quality of phylogenetic inference while severely reducing dataset size. We approach this by assessing which kinds of loci in phylogenomic alignments provide the majority of support for a phylogenetic inference of cockroaches in Blaberoidea. We examine locus substitution rate, saturation, evolutionary divergence, rate heterogeneity, stabilizing selection, and a priori information content as traits that may determine optimality. Our controlled experimental design is based on 265 loci for 102 blaberoidean taxa and 22 outgroup species. Loci with high substitution rate, low saturation, low sequence distance, low rate heterogeneity, and strong stabilizing selection derive more support for phylogenetic relationships. We found that some phylogenetic information content estimators may not be meaningful for assessing information content a priori. We use these findings to design concatenated datasets with an optimized subsample of 100 loci. The tree inferred from the optimized subsample alignment was largely identical to that inferred from all 265 loci but with less evidence of long branch attraction, improved statistical support, and potential 4‐6x improvements to computation time. Supported by phylogenetic and morphological evidence, we erect three newly named clades (Anallactinae Evangelista & Wipfler subfam. nov., Orkrasomeria tax. nov. Evangelista, Wipfler, & Béthoux and Hemithyrsocerini Evangelista tribe nov.) and propose other taxonomic modifications. The diagnosis of Pseudophyllodromiidae Grandcolas, 1996 is modified to accommodate Anallactinae and Pseudophyllodromiinae Vickery & Kevan, 1983. The diagnosis of Ectobiidae Brunner von Wattenwyl, 1865 is modified to add novel morphological characters.     

On the importance of homology in the age of phylogenomics

Homology is perhaps the most central concept of phylogenetic biology. Molecular systematists have traditionally paid due attention to the homology statements that are implied by their alignments of orthologous sequences, but some authors have suggested that manual gene-by-gene curation is not sustainable in the phylogenomics era. Here, we show that there are multiple ways to efficiently screen for and detect homology errors in phylogenomic data sets. Application of these screening approaches to two phylogenomic data sets, one for birds and another for mammals, shows that these data are replete with homology errors including alignments of different exons to each other, alignments of exons to introns, and alignments of paralogues to each other. The extent of these homology errors weakens the conclusions of studies based on these data sets. Despite advances in automated phylogenomic pipelines, we contend that much of the long, difficult, and sometimes tedious work of systematics is still required to guard against pervasive homology errors. This conclusion is underscored by recent studies that show that just a few outlier genes can impact phylogenetic results at short, tightly spaced internodes that are deep in the Tree of Life. The view that widespread DNA sequence alignment errors are not a major concern for rigorous systematic research is not tenable. If a primary goal of phylogenomics is to resolve the most challenging phylogenetic problems with the abundant data that are now available, researchers must employ effective procedures to screen for and correct homology errors prior to performing downstream phylogenetic analyses.     

How well do multispecies coalescent methods perform with mitochondrial genomic data? A case study of butterflies and moths (Insecta: Lepidoptera)

Despite the broad adoption of multispecies coalescent (MSC) methods for nuclear phylogenomics, they have yet to be applied to mitochondrial (mt) genomic data. As the potential sources of phylogenomic bias that MSC methods can address, such as incomplete lineage sorting, horizontal gene transfer and gene tree heterogeneity, have been found in mt genomic data, these approaches may improve the accuracy of phylogenetic inference with these data. In the present study, we examined the behaviour of MSC methods in reconstructing the phylogeny of Lepidoptera (butterflies and moths), a group for which mt genomic data are known to have strong resolving power. Traditional concatenation methods of analysing mt genomes for Lepidoptera infer topologies highly congruent with those generated from independent nuclear datasets. Individual mt gene trees performed poorly in recovering consensus relationships at deep levels (i.e. superfamily monophyly and inter-relationships) and only moderately well for shallow relationships (i.e. within Papilionoidea). In contrast, MSC analyses with ASTRAL performed strongly with almost complete concordance to both concatenated mt genome analyses and independent nuclear analyses at both deep and shallow phylogenetic scales. Outgroup choice had a limited impact on tree accuracy, with even phylogenetically distant outgroups still resulting in topologies highly congruent with results from nuclear datasets, although MSC analyses appeared to be marginally more affected by outgroup choice than concatenation analyses. In general, discordance between concatenation and MSC analyses was found at nodes whose resolution varied between previous nuclear phylogenomic studies. The sensitivity of individual relationships to analysis with MSC vs concatenation can thus be used to test the robustness of phylogenetic hypotheses. For insect phylogenetics, MSC is a reliable inference method for mt genomic data and is thus a useful complement to the already widely used concatenation approaches.     

Partitioned Gene-Tree Analyses and Gene-Based Topology Testing Help Resolve Incongruence in a Phylogenomic Study of Host-Specialist Bees (Apidae: Eucerinae)

Incongruence among phylogenetic results has become a common occurrence in analyses of genome-scale data sets. Incongruence originates from uncertainty in underlying evolutionary processes (e.g., incomplete lineage sorting) and from difficulties in determining the best analytical approaches for each situation. To overcome these difficulties, more studies are needed that identify incongruences and demonstrate practical ways to confidently resolve them. Here, we present results of a phylogenomic study based on the analysis 197 taxa and 2,526 ultraconserved element (UCE) loci. We investigate evolutionary relationships of Eucerinae, a diverse subfamily of apid bees (relatives of honey bees and bumble bees) with >1,200 species. We sampled representatives of all tribes within the group and >80% of genera, including two mysterious South American genera, Chilimalopsis and Teratognatha. Initial analysis of the UCE data revealed two conflicting hypotheses for relationships among tribes. To resolve the incongruence, we tested concatenation and species tree approaches and used a variety of additional strategies including locus filtering, partitioned gene-trees searches, and gene-based topological tests. We show that within-locus partitioning improves gene tree and subsequent species-tree estimation, and that this approach, confidently resolves the incongruence observed in our data set. After exploring our proposed analytical strategy on eucerine bees, we validated its efficacy to resolve hard phylogenetic problems by implementing it on a published UCE data set of Adephaga (Insecta: Coleoptera). Our results provide a robust phylogenetic hypothesis for Eucerinae and demonstrate a practical strategy for resolving incongruence in other phylogenomic data sets.     

Bayesian model adequacy and choice in phylogenetics

Bayesian inference is becoming a common statistical approach to phylogenetic estimation because, among other reasons, it allows for rapid analysis of large data sets with complex evolutionary models. Conveniently, Bayesian phylogenetic methods use currently available stochastic models of sequence evolution. However, as with other model-based approaches, the results of Bayesian inference are conditional on the assumed model of evolution: inadequate models (models that poorly fit the data) may result in erroneous inferences. In this article, I present a Bayesian phylogenetic method that evaluates the adequacy of evolutionary models using posterior predictive distributions. By evaluating a model's posterior predictive performance, an adequate model can be selected for a Bayesian phylogenetic study. Although I present a single test statistic that assesses the overall (global) performance of a phylogenetic model, a variety of test statistics can be tailored to evaluate specific features (local performance) of evolutionary models to identify sources failure. The method presented here, unlike the likelihood-ratio test and parametric bootstrap, accounts for uncertainty in the phylogeny and model parameters.     

A bi-organellar phylogenomic study of Pandanales: inference of higher-order relationships and unusual rate-variation patterns

We used a bi-organellar phylogenomic approach to address higher-order relationships in Pandanales, including the first molecular phylogenetic study of the panama-hat family, Cyclanthaceae. Our genus-level study of plastid and mitochondrial gene sets includes a comprehensive sampling of photosynthetic lineages across the order, and provides a framework for investigating clade ages, biogeographic hypotheses and organellar molecular evolution. Using multiple inference methods and both organellar genomes, we recovered mostly congruent and strongly supported relationships within and between families, including the placement of fully mycoheterotrophic Triuridaceae. Cyclanthaceae and Pandanaceae plastomes have slow substitution rates, contributing to weakly supported plastid-based relationships in Cyclanthaceae. While generally slowly evolving, mitochondrial genomes exhibit sporadic rate elevation across the order. However, we infer well-supported relationships even for slower evolving mitochondrial lineages in Cyclanthaceae. Clade age estimates across photosynthetic lineages are largely consistent with previous studies, are well correlated between the two organellar genomes (with slightly younger inferences from mitochondrial data), and support several biogeographic hypotheses. We show that rapidly evolving non-photosynthetic lineages may bias age estimates upwards at neighbouring photosynthetic nodes, even using a relaxed clock model. Finally, we uncovered new genome structural variants in photosynthetic taxa at plastid inverted repeat boundaries that show promise as interfamilial phylogenetic markers.     

Time Clustered Sampling Can Inflate the Inferred Substitution Rate in Foot-And-Mouth Disease Virus Analyses

With the emergence of analytical software for the inference of viral evolution, a number of studies have focused on estimating important parameters such as the substitution rate and the time to the most recent common ancestor (t _MRCA) for rapidly evolving viruses. Coupled with an increasing abundance of sequence data sampled under widely different schemes, an effort to keep results consistent and comparable is needed. This study emphasizes commonly disregarded problems in the inference of evolutionary rates in viral sequence data when sampling is unevenly distributed on a temporal scale through a study of the foot-and-mouth (FMD) disease virus serotypes SAT 1 and SAT 2. Our study shows that clustered temporal sampling in phylogenetic analyses of FMD viruses will strongly bias the inferences of substitution rates and t _MRCA because the inferred rates in such data sets reflect a rate closer to the mutation rate rather than the substitution rate. Estimating evolutionary parameters from viral sequences should be performed with due consideration of the differences in short-term and longer-term evolutionary processes occurring within sets of temporally sampled viruses, and studies should carefully consider how samples are combined.     

A new view of insect-crustacean relationships II. Inferences from expressed sequence tags and comparisons with neural cladistics

The enormous diversity of Arthropoda has complicated attempts by systematists to deduce the history of this group in terms of phylogenetic relationships and phenotypic change. Traditional hypotheses regarding the relationships of the major arthropod groups (Chelicerata, Myriapoda, Crustacea, and Hexapoda) focus on suites of morphological characters, whereas phylogenomics relies on large amounts of molecular sequence data to infer evolutionary relationships. The present discussion is based on expressed sequence tags (ESTs) that provide large numbers of short molecular sequences and so provide an abundant source of sequence data for phylogenetic inference. This study presents well-supported phylogenies of diverse arthropod and metazoan outgroup taxa obtained from publicly-available databases. An in-house bioinformatics pipeline has been used to compile and align conserved orthologs from each taxon for maximum likelihood inferences. This approach resolves many currently accepted hypotheses regarding internal relationships between the major groups of Arthropoda, including monophyletic Hexapoda, Tetraconata (Crustacea + Hexapoda), Myriapoda, and Chelicerata sensu lato (Pycnogonida + Euchelicerata). "Crustacea" is a paraphyletic group with some taxa more closely related to the monophyletic Hexapoda. These results support studies that have utilized more restricted EST data for phylogenetic inference, yet they differ in important regards from recently published phylogenies employing nuclear protein-coding sequences. The present results do not, however, depart from other phylogenies that resolve Branchiopoda as the crustacean sister group of Hexapoda. Like other molecular phylogenies, EST-derived phylogenies alone are unable to resolve morphological convergences or evolved reversals and thus omit what may be crucial events in the history of life. For example, molecular data are unable to resolve whether a Hexapod-Branchiopod sister relationship infers a branchiopod-like ancestry of the Hexapoda, or whether this assemblage originates from a malacostracan-like ancestor, with the morphologically simpler Branchiopoda being highly derived. Whereas this study supports many internal arthropod relationships obtained by other sources of molecular data, other approaches are required to resolve such evolutionary scenarios. The approach presented here turns out to be essential: integrating results of molecular phylogenetics and neural cladistics to infer that Branchiopoda evolved simplification from a more elaborate ancestor. Whereas the phenomenon of evolved simplification may be widespread, it is largely invisible to molecular techniques unless these are performed in conjunction with morphology-based strategies.     

Assessment of phylogenomic and orthology approaches for phylogenetic inference

MOTIVATION: Phylogenomics integrates the vast amount of phylogenetic information contained in complete genome sequences, and is rapidly becoming the standard for reliably inferring species phylogenies. There are, however, fundamental differences between the ways in which phylogenomic approaches like gene content, superalignment, superdistance and supertree integrate the phylogenetic information from separate orthologous groups. Furthermore, they all depend on the method by which the orthologous groups are initially determined. Here, we systematically compare these four phylogenomic approaches, in parallel with three approaches for large-scale orthology determination: pairwise orthology, cluster orthology and tree-based orthology. RESULTS: Including various phylogenetic methods, we apply a total of 54 fully automated phylogenomic procedures to the fungi, the eukaryotic clade with the largest number of sequenced genomes, for which we retrieved a golden standard phylogeny from the literature. Phylogenomic trees based on gene content show, relative to the other methods, a bias in the tree topology that parallels convergence in lifestyle among the species compared, indicating convergence in gene content. CONCLUSIONS: Complete genomes are no guarantee for good or even consistent phylogenies. However, the large amounts of data in genomes enable us to carefully select the data most suitable for phylogenomic inference. In terms of performance, the superalignment approach, combined with restrictive orthology, is the most successful in recovering a fungal phylogeny that agrees with current taxonomic views, and allows us to obtain a high-resolution phylogeny. We provide solid support for what has grown to be a common practice in phylogenomics during its advance in recent years. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

Bayesian Inference of Reticulate Phylogenies under the Multispecies Network Coalescent

The multispecies coalescent (MSC) is a statistical framework that models how gene genealogies grow within the branches of a species tree. The field of computational phylogenetics has witnessed an explosion in the development of methods for species tree inference under MSC, owing mainly to the accumulating evidence of incomplete lineage sorting in phylogenomic analyses. However, the evolutionary history of a set of genomes, or species, could be reticulate due to the occurrence of evolutionary processes such as hybridization or horizontal gene transfer. We report on a novel method for Bayesian inference of genome and species phylogenies under the multispecies network coalescent (MSNC). This framework models gene evolution within the branches of a phylogenetic network, thus incorporating reticulate evolutionary processes, such as hybridization, in addition to incomplete lineage sorting. As phylogenetic networks with different numbers of reticulation events correspond to points of different dimensions in the space of models, we devise a reversible-jump Markov chain Monte Carlo (RJMCMC) technique for sampling the posterior distribution of phylogenetic networks under MSNC. We implemented the methods in the publicly available, open-source software package PhyloNet and studied their performance on simulated and biological data. The work extends the reach of Bayesian inference to phylogenetic networks and enables new evolutionary analyses that account for reticulation.     

A model of horizontal gene transfer and the bacterial phylogeny problem

How much horizontal gene transfer (HGT) between species influences bacterial phylogenomics is a controversial issue. This debate, however, lacks any quantitative assessment of the impact of HGT on phylogenies and of the ability of tree-building methods to cope with such events. I introduce a Markov model of genome evolution with HGT, accounting for the constraints on time -- an HGT event can only occur between concomitantly living species. This model is used to simulate multigene sequence data sets with or without HGT. The consequences of HGT on phylogenomic inference are analyzed and compared to other well-known phylogenetic artefacts. It is found that supertree methods are quite robust to HGT, keeping high levels of performance even when gene trees are largely incongruent with each other. Gene tree incongruence per se is not indicative of HGT. HGT, however, removes the (otherwise observed) positive relationship between sequence length and gene tree congruence to the estimated species tree. Surprisingly, when applied to a bacterial and a eukaryotic multigene data set, this criterion rejects the HGT hypothesis for the former, but not the latter data set.     

Developing a series of conservative anchor markers and their application to phylogenomics of Laurasiatherian mammals

The availability of numerous universal markers and suitable phylogenetic analysis methods are both very important for phylogenomics inference. Based on PCR amplification, a total of 122 markers, which were amplified in 19 representative species, were developed for Laurasiatherian phylogenomics. Subsequently, we illustrated the utility of these newly developed markers using a subset of eight markers. We showed that both 'supermatrix' and 'supertree' trees generated similar topology, which accorded with the current understanding of the Laurasiatherian phylogeny in most aspects. Thus, markers developed here would be likely to make a contribution to resolving evolutionary relationships and inferring evolutionary histories of the Laurasiatherian mammals in the future.     

Phylomat: an automated protein motif analysis tool for phylogenomics

Recent progress in genomics, proteomics, and bioinformatics enables unprecedented opportunities to examine the evolutionary history of molecular, cellular, and developmental pathways through phylogenomics. Accordingly, we have developed a motif analysis tool for phylogenomics (Phylomat, http://alg.ncsa.uiuc.edu/pmat) that scans predicted proteome sets for proteins containing highly conserved amino acid motifs or domains for in silico analysis of the evolutionary history of these motifs/domains. Phylomat enables the user to download results as full protein or extracted motif/domain sequences from each protein. Tables containing the percent distribution of a motif/domain in organisms normalized to proteome size are displayed. Phylomat can also align the set of full protein or extracted motif/domain sequences and predict a neighbor-joining tree from relative sequence similarity. Together, Phylomat serves as a user-friendly data-mining tool for the phylogenomic analysis of conserved sequence motifs/domains in annotated proteomes from the three domains of life.