To study the origin and evolution of biochemical pathways in
microorganisms, we have developed methods and software for automatic,
large-scale reconstructions of phylogenetic relationships. We define
the complete set of phylogenetic trees derived from the proteome
of an organism as the phylome and introduce the
term phylogenetic connection as a concept that describes the relative
relationships between taxa in a tree. A query system has been incorporated
into the system so as to allow searches for defined categories of
trees within the phylome. As a complement, we have
developed the pyphy system for visualising the results of complex
queries on phylogenetic connections, genomic locations and functional
assignments in a graphical format. Our phylogenomics approach, which
links phylogenetic information to the flow of biochemical pathways within
and among microbial species, has been used to examine more than
8000 phylogenetic trees from seven microbial genomes. The results
have revealed a rich web of phylogenetic connections. However, the
separation of Bacteria and Archaea into two separate domains remains
The constant accumulation of sequence data poses new computational and methodological challenges for phylogenetic inference, since multiple sequence alignments grow both in the horizontal (number of base pairs, phylogenomic alignments) as well as vertical (number of taxa) dimension. Put aside the ongoing controversial discussion about appropriate models, partitioning schemes, and assembly methods for phylogenomic alignments, coupled with the high computational cost to infer these, for many organismic groups, a sufficient number of taxa is often exclusively available from one or just a few genes (e.g., rbcL, matK, rDNA). In this paper we address scalability of Maximum-Likelihood-based phylogeny reconstruction with respect to the number of taxa by example of several large nested single-gene rbcL alignments comprising 400 up to 3,491 taxa. In order to test the effect of taxon sampling, we employ an appropriately adapted taxon jackknifing approach. In contrast to standard jackknifing, this taxon subsampling procedure is not conducted entirely at random, but based on drawing subsamples from empirical taxon-groups which can either be user-defined or determined by using taxonomic information from databases. Our results indicate that, despite an unfavorable number of sequences to number of base pairs ratio, i.e., many relatively short sequences, Maximum Likelihood tree searches and bootstrap analyses scale well on single-gene rbcL alignments with a dense taxon sampling up to several thousand sequences. Moreover, the newly implemented taxon subsampling procedure can be beneficial for inferring higher level relationships and interpreting bootstrap support from comprehensive analysis.
RAxML; phylogenetic inference; many taxon analyses; taxon jackknifing
Most studies inferring species phylogenies use sequences from single copy genes or sets of orthologs culled from gene families. For taxa such as plants, with very high levels of gene duplication in their nuclear genomes, this has limited the exploitation of nuclear sequences for phylogenetic studies, such as those available in large EST libraries. One rarely used method of inference, gene tree parsimony, can infer species trees from gene families undergoing duplication and loss, but its performance has not been evaluated at a phylogenomic scale for EST data in plants.
A gene tree parsimony analysis based on EST data was undertaken for six angiosperm model species and Pinus, an outgroup. Although a large fraction of the tentative consensus sequences obtained from the TIGR database of ESTs was assembled into homologous clusters too small to be phylogenetically informative, some 557 clusters contained promising levels of information. Based on maximum likelihood estimates of the gene trees obtained from these clusters, gene tree parsimony correctly inferred the accepted species tree with strong statistical support. A slight variant of this species tree was obtained when maximum parsimony was used to infer the individual gene trees instead.
Despite the complexity of the EST data and the relatively small fraction eventually used in inferring a species tree, the gene tree parsimony method performed well in the face of very high apparent rates of duplication.
The chætognath transcriptome reveals unusual genomic features in the evolution of this protostome and suggests that it could be used as a model organism for bilaterians.
The chætognaths (arrow worms) have puzzled zoologists for years because of their astonishing morphological and developmental characteristics. Despite their deuterostome-like development, phylogenomic studies recently positioned the chætognath phylum in protostomes, most likely in an early branching. This key phylogenetic position and the peculiar characteristics of chætognaths prompted further investigation of their genomic features.
Transcriptomic and genomic data were collected from the chætognath Spadella cephaloptera through the sequencing of expressed sequence tags and genomic bacterial artificial chromosome clones. Transcript comparisons at various taxonomic scales emphasized the conservation of a core gene set and phylogenomic analysis confirmed the basal position of chætognaths among protostomes. A detailed survey of transcript diversity and individual genotyping revealed a past genome duplication event in the chætognath lineage, which was, surprisingly, followed by a high retention rate of duplicated genes. Moreover, striking genetic heterogeneity was detected within the sampled population at the nuclear and mitochondrial levels but cannot be explained by cryptic speciation. Finally, we found evidence for trans-splicing maturation of transcripts through splice-leader addition in the chætognath phylum and we further report that this processing is associated with operonic transcription.
These findings reveal both shared ancestral and unique derived characteristics of the chætognath genome, which suggests that this genome is likely the product of a very original evolutionary history. These features promote chætognaths as a pivotal model for comparative genomics, which could provide new clues for the investigation of the evolution of animal genomes.
Phylogenomic approaches to the resolution of inter-species relationships have become well established in recent years. Often these involve concatenation of many orthologous genes found in the respective genomes followed by analysis using standard phylogenetic models. Genome-scale data promise increased resolution by minimising sampling error, yet are associated with well-known but often inappropriately addressed caveats arising through data heterogeneity and model violation. These can lead to the reconstruction of highly-supported but incorrect topologies. With the aim of obtaining a species tree for 18 species within the ascomycetous yeasts, we have investigated the use of appropriate evolutionary models to address inter-gene heterogeneities and the scalability and validity of supermatrix analysis as the phylogenetic problem becomes more difficult and the number of genes analysed approaches truly phylogenomic dimensions. We have extended a widely-known early phylogenomic study of yeasts by adding additional species to increase diversity and augmenting the number of genes under analysis. We have investigated sophisticated maximum likelihood analyses, considering not only a concatenated version of the data but also partitioned models where each gene constitutes a partition and parameters are free to vary between the different partitions (thereby accounting for variation in the evolutionary processes at different loci). We find considerable increases in likelihood using these complex models, arguing for the need for appropriate models when analyzing phylogenomic data. Using these methods, we were able to reconstruct a well-supported tree for 18 ascomycetous yeasts spanning about 250 million years of evolution.
The frequent exchange of genetic material among prokaryotes means that extracting a majority or plurality phylogenetic signal from many gene families, and the identification of gene families that are in significant conflict with the plurality signal is a frequent task in comparative genomics, and especially in phylogenomic analyses. Decomposition of gene trees into embedded quartets (unrooted trees each with four taxa) is a convenient and statistically powerful technique to address this challenging problem. This approach was shown to be useful in several studies of completely sequenced microbial genomes.
We present here a web server that takes a collection of gene phylogenies, decomposes them into quartets, generates a Quartet Spectrum, and draws a split network. Users are also provided with various data download options for further analyses. Each gene phylogeny is to be represented by an assessment of phylogenetic information content, such as sets of trees reconstructed from bootstrap replicates or sampled from a posterior distribution. The Quartet Decomposition server is accessible at http://quartets.uga.edu.
The Quartet Decomposition server presented here provides a convenient means to perform Quartet Decomposition analyses and will empower users to find statistically supported phylogenetic conflicts.
A novel result of the current research is the development and implementation of a unique functional phylogenomic approach that explores the genomic origins of seed plant diversification. We first use 22,833 sets of orthologs from the nuclear genomes of 101 genera across land plants to reconstruct their phylogenetic relationships. One of the more salient results is the resolution of some enigmatic relationships in seed plant phylogeny, such as the placement of Gnetales as sister to the rest of the gymnosperms. In using this novel phylogenomic approach, we were also able to identify overrepresented functional gene ontology categories in genes that provide positive branch support for major nodes prompting new hypotheses for genes associated with the diversification of angiosperms. For example, RNA interference (RNAi) has played a significant role in the divergence of monocots from other angiosperms, which has experimental support in Arabidopsis and rice. This analysis also implied that the second largest subunit of RNA polymerase IV and V (NRPD2) played a prominent role in the divergence of gymnosperms. This hypothesis is supported by the lack of 24nt siRNA in conifers, the maternal control of small RNA in the seeds of flowering plants, and the emergence of double fertilization in angiosperms. Our approach takes advantage of genomic data to define orthologs, reconstruct relationships, and narrow down candidate genes involved in plant evolution within a phylogenomic view of species' diversification.
Understanding the genetic and genomic basis of plant diversification has been a major goal of evolutionary biologists since Darwin first pondered his “abominable mystery,” the rapid diversification of the angiosperms in the fossil record. We develop and deploy a functional phylogenomic approach that helps identify genes and biological processes putatively involved in species diversification. We assembled a matrix of 22,833 orthologs from 150 species to reconstruct seed plant phylogenetic relationships and to identify gene sets with a unique evolutionary signal. Our analysis of overrepresented biological processes in these sets narrowed down possible genetic mechanisms underlying plant adaptation and diversification. The phylogenetic relationships we uncovered support the hypothesis that gnetophytes are closely related to the rest of the gymnosperms at the base of the living seed plants. We also found that genes involved in post-transcriptional silencing via RNA interference (RNAi)—increasingly important in understanding plant evolution—are significantly represented early in angiosperm and gymnosperm divergence, with an apparent loss of specific classes of small interfering RNAs (siRNA) in gymnosperms. Our functional phylogenomic approach can be applied to any taxa with available sequences to enhance our knowledge of the evolutionary processes underlying biodiversity in general.
In the absence of whole genome sequences for many organisms, the use of expressed sequence tags (EST) offers an affordable approach for researchers conducting phylogenetic analyses to gain insight about the evolutionary history of organisms. Reliable alignments for phylogenomic analyses are based on orthologous gene sequences from different taxa. So far, researchers have not sufficiently tackled the problem of the completely automated construction of such datasets. Existing software tools are either semi-automated, covering only part of the necessary data processing, or implemented as a pipeline, requiring the installation and configuration of a cascade of external tools, which may be time-consuming and hard to manage. To simplify data set construction for phylogenomic studies, we set up a web server that uses our recently developed OrthoSelect approach. To the best of our knowledge, our web server is the first web-based EST analysis pipeline that allows the detection of orthologous gene sequences in EST libraries and outputs orthologous gene alignments. Additionally, OrthoSelect provides the user with an extensive results section that lists and visualizes all important results, such as annotations, data matrices for each gene/taxon and orthologous gene alignments. The web server is available at http://orthoselect.gobics.de.
The availability of sequences from whole genomes to reconstruct the tree of life has the potential to enable the development of phylogenomic hypotheses in ways that have not been before possible. A significant bottleneck in the analysis of genomic-scale views of the tree of life is the time required for manual curation of genomic data into multi-gene phylogenetic matrices.
To keep pace with the exponentially growing volume of molecular data in the genomic era, we have developed an automated technique, ASAP (Automated Simultaneous Analysis Phylogenetics), to assemble these multigene/multi species matrices and to evaluate the significance of individual genes within the context of a given phylogenetic hypothesis.
Applications of ASAP may enable scientists to re-evaluate species relationships and to develop new phylogenomic hypotheses based on genome-scale data.
Members of the Roseobacter clade which play a key role in the biogeochemical cycles of the ocean are diverse and abundant, comprising 10–25% of the bacterioplankton in most marine surface waters. The rapid accumulation of whole-genome sequence data for the Roseobacter clade allows us to obtain a clearer picture of its evolution.
In this study about 1,200 likely orthologous protein families were identified from 17 Roseobacter bacteria genomes. Functional annotations for these genes are provided by iProClass. Phylogenetic trees were constructed for each gene using maximum likelihood (ML) and neighbor joining (NJ). Putative organismal phylogenetic trees were built with phylogenomic methods. These trees were compared and analyzed using principal coordinates analysis (PCoA), approximately unbiased (AU) and Shimodaira–Hasegawa (SH) tests. A core set of 694 genes with vertical descent signal that are resistant to horizontal gene transfer (HGT) is used to reconstruct a robust organismal phylogeny. In addition, we also discovered the most likely 109 HGT genes. The core set contains genes that encode ribosomal apparatus, ABC transporters and chaperones often found in the environmental metagenomic and metatranscriptomic data. These genes in the core set are spread out uniformly among the various functional classes and biological processes.
Here we report a new multigene-derived phylogenetic tree of the Roseobacter clade. Of particular interest is the HGT of eleven genes involved in vitamin B12 synthesis as well as key enzynmes for dimethylsulfoniopropionate (DMSP) degradation. These aquired genes are essential for the growth of Roseobacters and their eukaryotic partners.
An automated pipeline for phylogenomic analysis (AMPHORA) is presented that overcomes existing limits to large-scale protein phylogenetic inference.
The explosive growth of genomic data provides an opportunity to make increased use of protein markers for phylogenetic inference. We have developed an automated pipeline for phylogenomic analysis (AMPHORA) that overcomes the existing bottlenecks limiting large-scale protein phylogenetic inference. We demonstrated its high throughput capabilities and high quality results by constructing a genome tree of 578 bacterial species and by assigning phylotypes to 18,607 protein markers identified in metagenomic data collected from the Sargasso Sea.
Phylogenomic pipelines generate a large collection of phylogenetic trees that require manual inspection to answer questions about gene or genome evolution. A notable application of phylogenomics is to photosynthetic organelle (plastid) endosymbiosis. In the case of primary endosymbiosis, a heterotrophic protist engulfed a cyanobacterium, giving rise to the first photosynthetic eukaryote. Plastid establishment precipitated extensive gene transfer from the endosymbiont to the nuclear genome of the 'host'. Estimating the magnitude of this endosymbiotic gene transfer (EGT) and determining the functions of the prokaryotic genes remain controversial issues. We used phylogenomics to study EGT in the model green alga Chlamydomonas reinhardtii. To facilitate this procedure, we developed PhyloSort to rapidly search large collection of trees for monophyletic relationships. Here we present PhyloSort and its application to estimating EGT in Chlamydomonas.
PhyloSort is an open-source tool to sort phylogenetic trees by searching for user specified subtrees that contain a monophyletic group of interest defined by operational taxonomic units in a phylogenomic context. Using PhyloSort, we identified 897 Chlamydomonas genes of putative cyanobacterial origin, of which 531 had bootstrap support values ≥ 50% for the grouping of the algal and cyanobacterial homologs.
PhyloSort can be applied to quantify the number of genes that support different evolutionary hypotheses such as a taxonomic classification or endosymbiotic or horizontal gene transfer events. In our application, we demonstrate that cyanobacteria account for 3.5–6% of the protein-coding genes in the nuclear genome of Chlamydomonas.
The growing availability of complete genomic sequences from diverse species has brought about the need to scale up phylogenomic analyses, including the reconstruction of large collections of phylogenetic trees. Here, we present the third version of PhylomeDB (http://phylomeDB.org), a public database for genome-wide collections of gene phylogenies (phylomes). Currently, PhylomeDB is the largest phylogenetic repository and hosts 17 phylomes, comprising 416 093 trees and 165 840 alignments. It is also a major source for phylogeny-based orthology and paralogy predictions, covering about 5 million proteins in 717 fully-sequenced genomes. For each protein-coding gene in a seed genome, the database provides original and processed alignments, phylogenetic trees derived from various methods and phylogeny-based predictions of orthology and paralogy relationships. The new version of phylomeDB has been extended with novel data access and visualization features, including the possibility of programmatic access. Available seed species include model organisms such as human, yeast, Escherichia coli or Arabidopsis thaliana, but also alternative model species such as the human pathogen Candida albicans, or the pea aphid Acyrtosiphon pisum. Finally, PhylomeDB is currently being used by several genome sequencing projects that couple the genome annotation process with the reconstruction of the corresponding phylome, a strategy that provides relevant evolutionary insights.
Phylogenomic databases provide orthology predictions for species with fully sequenced genomes. Although the goal seems well-defined, the content of these databases differs greatly. Seven ortholog databases (Ensembl Compara, eggNOG, HOGENOM, InParanoid, OMA, OrthoDB, Panther) were compared on the basis of reference trees. For three well-conserved protein families, we observed a generally high specificity of orthology assignments for these databases. We show that differences in the completeness of predicted gene relationships and in the phylogenetic information are, for the great majority, not due to the methods used, but to differences in the underlying database concepts. According to our metrics, none of the databases provides a fully correct and comprehensive protein classification. Our results provide a framework for meaningful and systematic comparisons of phylogenomic databases. In the future, a sustainable set of ‘Gold standard’ phylogenetic trees could provide a robust method for phylogenomic databases to assess their current quality status, measure changes following new database releases and diagnose improvements subsequent to an upgrade of the analysis procedure.
conceptual comparison; phylogenomic databases; quality assessment; reference gene trees
Phylogenomic analyses recently became popular to address questions about deep metazoan phylogeny. Ribosomal proteins (RP) dominate many of these analyses or are, in some cases, the only genes included. Despite initial hopes, phylogenomic analyses including tens to hundreds of genes still fail to robustly place many bilaterian taxa.
Using the phylogenetic position of myzostomids as an example, we show that phylogenies derived from RP genes and mitochondrial genes produce incongruent results. Whereas the former support a position within a clade of platyzoan taxa, mitochondrial data recovers an annelid affinity, which is strongly supported by the gene order data and is congruent with morphology. Using hypothesis testing, our RP data significantly rejects the annelids affinity, whereas a platyzoan relationship is significantly rejected by the mitochondrial data.
We conclude (i) that reliance of a set of markers belonging to a single class of macromolecular complexes might bias the analysis, and (ii) that concatenation of all available data might introduce conflicting signal into phylogenetic analyses. We therefore strongly recommend testing for data incongruence in phylogenomic analyses. Furthermore, judging all available data, we consider the annelid affinity hypothesis more plausible than a possible platyzoan affinity for myzostomids, and suspect long branch attraction is influencing the RP data. However, this hypothesis needs further confirmation by future analyses.
The vast sequence divergence among different virus groups has presented a great challenge to alignment-based analysis of virus phylogeny. Due to the problems caused by the uncertainty in alignment, existing tools for phylogenetic analysis based on multiple alignment could not be directly applied to the whole-genome comparison and phylogenomic studies of viruses. There has been a growing interest in alignment-free methods for phylogenetic analysis using complete genome data. Among the alignment-free methods, a dynamical language (DL) method proposed by our group has successfully been applied to the phylogenetic analysis of bacteria and chloroplast genomes.
In this paper, the DL method is used to analyze the whole-proteome phylogeny of 124 large dsDNA viruses and 30 parvoviruses, two data sets with large difference in genome size. The trees from our analyses are in good agreement to the latest classification of large dsDNA viruses and parvoviruses by the International Committee on Taxonomy of Viruses (ICTV).
The present method provides a new way for recovering the phylogeny of large dsDNA viruses and parvoviruses, and also some insights on the affiliation of a number of unclassified viruses. In comparison, some alignment-free methods such as the CV Tree method can be used for recovering the phylogeny of large dsDNA viruses, but they are not suitable for resolving the phylogeny of parvoviruses with a much smaller genome size.
The vertebrate tetraspanin family has many features which make it suitable for preserving the imprint of ancient sequence evolution and amenable for phylogenomic analysis. So we believe that an in-depth analysis of the tetraspanin evolution not only provides more complete understanding of tetraspanin biology, but offers new insights into the influence of the two rounds of whole genome duplication (2R-WGD) at the origin of vertebrates.
A detailed phylogeny of vertebrate tetraspanins was constructed by using multiple lines of information, including sequence-based phylogenetics, key structural features, intron configuration and genomic synteny. In particular, a total of 38 modern tetraspanin ortholog lineages in bony vertebrates have been identified and subsequently classified into 17 ancestral lineages existing before 2R-WGD. Based on this phylogeny, we found that the ohnolog retention rate of tetraspanins after 2R-WGD was three times as the average (a rate similar to those of transcription factors and protein kinases). This high rate didn't increase the tetrapanin family size, but changed the family composition, possibly by displacing vertebrate-specific gene lineages with the lineages conserved across deuterostomes. We also found that the period from 2R-WGD to recent time is controlled by gene losses. Meanwhile, positive selection has been detected on 80% of the branches right after 2R-WGDs, which declines significantly on both magnitude and extensity on the following speciation branches. Notably, the loss of mammalian RDS2 is accompanied by strong positive selection on mammalian ROM1, possibly due to gene loss-induced compensatory evolution.
First, different from transcription factors and kinases, high duplicate retention rate after 2R-WGD didn't increase the tetraspanin family size but just reshaped the family composition. Second, the evolution of tetraspanins right after 2R-WGD had been impacted by a massive wave of gene loss and positive selection on coding sequences. Third, the lingering effect of 2R-WGD on tetraspanin gene loss and positive selection might last for 300-400 million years.
The human phylome, which includes evolutionary relationships of all human proteins and their homologs among thirty-nine fully sequenced eukaryotes, is reconstructed.
Phylogenomics analyses serve to establish evolutionary relationships among organisms and their genes. A phylome, the complete collection of all gene phylogenies in a genome, constitutes a valuable source of information, but its use in large genomes still constitutes a technical challenge. The use of phylomes also requires the development of new methods that help us to interpret them.
We reconstruct here the human phylome, which includes the evolutionary relationships of all human proteins and their homologs among 39 fully sequenced eukaryotes. Phylogenetic techniques used include alignment trimming, branch length optimization, evolutionary model testing and maximum likelihood and Bayesian methods. Although differences with alternative topologies are minor, most of the trees support the Coelomata and Unikont hypotheses as well as the grouping of primates with laurasatheria to the exclusion of rodents. We assess the extent of gene duplication events and their relationship with the functional roles of the protein families involved. We find support for at least one, and probably two, rounds of whole genome duplications before vertebrate radiation. Using a novel algorithm that is independent from a species phylogeny, we derive orthology and paralogy relationships of human proteins among eukaryotic genomes.
Topological variations among phylogenies for different genes are to be expected, highlighting the danger of gene-sampling effects in phylogenomic analyses. Several links can be established between the functions of gene families duplicated at certain phylogenetic splits and major evolutionary transitions in those lineages. The pipeline implemented here can be easily adapted for use in other organisms.
Phylogenetic analyses based on datasets rich in both genes and species (phylogenomics) are becoming a standard approach to resolve evolutionary questions. However, several difficulties are associated with the assembly of large datasets, such as multiple copies of a gene per species (paralogous or xenologous genes), lack of some genes for a given species, or partial sequences. The use of undetected paralogous or xenologous genes in phylogenetic inference can lead to inaccurate results, and the use of partial sequences to a lack of resolution. A tool that selects sequences, species, and genes, while dealing with these issues, is needed in a phylogenomics context.
Here, we present SCaFoS, a tool that quickly assembles phylogenomic datasets containing maximal phylogenetic information while adjusting the amount of missing data in the selection of species, sequences and genes. Starting from individual sequence alignments, and using monophyletic groups defined by the user, SCaFoS creates chimeras with partial sequences, or selects, among multiple sequences, the orthologous and/or slowest evolving sequences. Once sequences representing each predefined monophyletic group have been selected, SCaFos retains genes according to the user's allowed level of missing data and generates files for super-matrix and super-tree analyses in several formats compatible with standard phylogenetic inference software. Because no clear-cut criteria exist for the sequence selection, a semi-automatic mode is available to accommodate user's expertise.
SCaFos is able to deal with datasets of hundreds of species and genes, both at the amino acid or nucleotide level. It has a graphical interface and can be integrated in an automatic workflow. Moreover, SCaFoS is the first tool that integrates user's knowledge to select orthologous sequences, creates chimerical sequences to reduce missing data and selects genes according to their level of missing data. Finally, applying SCaFoS to different datasets, we show that the judicious selection of genes, species and sequences reduces tree reconstruction artefacts, especially if the dataset includes fast evolving species.
Phylogenomics refers to the inference of historical relationships among species using genome-scale sequence data and to the use of phylogenetic analysis to infer protein function in multigene families. With rapidly decreasing sequencing costs, phylogenomics is becoming synonymous with evolutionary analysis of genome-scale and taxonomically densely sampled data sets. In phylogenetic inference applications, this translates into very large data sets that yield evolutionary and functional inferences with extremely small variances and high statistical confidence (P value). However, reports of highly significant P values are increasing even for contrasting phylogenetic hypotheses depending on the evolutionary model and inference method used, making it difficult to establish true relationships. We argue that the assessment of the robustness of results to biological factors, that may systematically mislead (bias) the outcomes of statistical estimation, will be a key to avoiding incorrect phylogenomic inferences. In fact, there is a need for increased emphasis on the magnitude of differences (effect sizes) in addition to the P values of the statistical test of the null hypothesis. On the other hand, the amount of sequence data available will likely always remain inadequate for some phylogenomic applications, for example, those involving episodic positive selection at individual codon positions and in specific lineages. Again, a focus on effect size and biological relevance, rather than the P value, may be warranted. Here, we present a theoretical overview and discuss practical aspects of the interplay between effect sizes, bias, and P values as it relates to the statistical inference of evolutionary truth in phylogenomics.
molecular evolution; statistical inference; phylogenetics; evolutionary tree; statistical bias; variance
Thanks to advances in next-generation technologies, genome sequences are now being generated at breadth (e.g. across environments) and depth (thousands of closely related strains, individuals or samples) unimaginable only a few years ago. Phylogenomics – the study of evolutionary relationships based on comparative analysis of genome-scale data – has so far been developed as industrial-scale molecular phylogenetics, proceeding in the two classical steps: multiple alignment of homologous sequences, followed by inference of a tree (or multiple trees). However, the algorithms typically employed for these steps scale poorly with number of sequences, such that for an increasing number of problems, high-quality phylogenomic analysis is (or soon will be) computationally infeasible. Moreover, next-generation data are often incomplete and error-prone, and analysis may be further complicated by genome rearrangement, gene fusion and deletion, lateral genetic transfer, and transcript variation. Here we argue that next-generation data require next-generation phylogenomics, including so-called alignment-free approaches.
Reviewed by Mr Alexander Panchin (nominated by Dr Mikhail Gelfand), Dr Eugene Koonin and Prof Peter Gogarten. For the full reviews, please go to the Reviewers’ comments section.
Phylogenomics; Multiple sequence alignment; Alignment-free methods; k-mers; Homology signal
Congruence is a broadly applied notion in evolutionary biology used to justify multigene phylogeny or phylogenomics, as well as in studies of coevolution, lateral gene transfer, and as evidence for common descent. Existing methods for identifying incongruence or heterogeneity using character data were designed for data sets that are both small and expected to be rarely incongruent. At the same time, methods that assess incongruence using comparison of trees test a null hypothesis of uncorrelated tree structures, which may be inappropriate for phylogenomic studies. As such, they are ill-suited for the growing number of available genome sequences, most of which are from prokaryotes and viruses, either for phylogenomic analysis or for studies of the evolutionary forces and events that have shaped these genomes. Specifically, many existing methods scale poorly with large numbers of genes, cannot accommodate high levels of incongruence, and do not adequately model patterns of missing taxa for different markers. We propose the development of novel incongruence assessment methods suitable for the analysis of the molecular evolution of the vast majority of life and support the investigation of homogeneity of evolutionary process in cases where markers do not share identical tree structures.
incongruence; lateral gene transfer; microbial evolution; phylogenetic networks; phylogenomics
The GeneTrees phylogenomics system pursues comparative genomic analyses from the perspective of gene phylogenies for individual genes. The GeneTrees project has the goal of providing detailed evolutionary models for all protein-coding gene components of the fully sequenced genomes. Currently, a database of alignments and trees for all protein sequences for 325 fully sequenced and annotated prokaryote genomes is available. The prokaryote database contains 890 000 protein sequences organized into over 100 000 alignments, each described by a phylogenetic tree. An original homology group discovery tool assembles sets of related proteins from all versus all pairwise alignments. Multiple alignments for each homology group are stored and subjected to phylogenetic tree inference. A graphical web interface provides visual exploration of the GeneTrees database. Homology groups can be queried by sequence identifiers or annotation terms. Genomes can be browsed visually on a gene map of each chromosome or plasmid. Phylogenetic trees with support values are displayed in conjunction with the associated sequence alignment. A variety of classes of information can be selected to label the tree tips to aid in visual evaluation of annotation and gene function. This web interface is available at .
The entire evolutionary history of life can be studied using myriad sequences generated by genomic research. This includes the appearance of the first cells and of superkingdoms Archaea, Bacteria, and Eukarya. However, the use of molecular sequence information for deep phylogenetic analyses is limited by mutational saturation, differential evolutionary rates, lack of sequence site independence, and other biological and technical constraints. In contrast, protein structures are evolutionary modules that are highly conserved and diverse enough to enable deep historical exploration.
Here we build phylogenies that describe the evolution of proteins and proteomes. These phylogenetic trees are derived from a genomic census of protein domains defined at the fold family (FF) level of structural classification. Phylogenomic trees of FF structures were reconstructed from genomic abundance levels of 2,397 FFs in 420 proteomes of free-living organisms. These trees defined timelines of domain appearance, with time spanning from the origin of proteins to the present. Timelines are divided into five different evolutionary phases according to patterns of sharing of FFs among superkingdoms: (1) a primordial protein world, (2) reductive evolution and the rise of Archaea, (3) the rise of Bacteria from the common ancestor of Bacteria and Eukarya and early development of the three superkingdoms, (4) the rise of Eukarya and widespread organismal diversification, and (5) eukaryal diversification. The relative ancestry of the FFs shows that reductive evolution by domain loss is dominant in the first three phases and is responsible for both the diversification of life from a universal cellular ancestor and the appearance of superkingdoms. On the other hand, domain gains are predominant in the last two phases and are responsible for organismal diversification, especially in Bacteria and Eukarya.
The evolution of functions that are associated with corresponding FFs along the timeline reveals that primordial metabolic domains evolved earlier than informational domains involved in translation and transcription, supporting the metabolism-first hypothesis rather than the RNA world scenario. In addition, phylogenomic trees of proteomes reconstructed from FFs appearing in each of the five phases of the protein world show that trees reconstructed from ancient domain structures were consistently rooted in archaeal lineages, supporting the proposal that the archaeal ancestor is more ancient than the ancestors of other superkingdoms.
When analyzing protein sequences using sequence similarity searches, orthologous sequences (that diverged by speciation) are more reliable predictors of a new protein's function than paralogous sequences (that diverged by gene duplication). The utility of phylogenetic information in high-throughput genome annotation ("phylogenomics") is widely recognized, but existing approaches are either manual or not explicitly based on phylogenetic trees.
Here we present RIO (Resampled Inference of Orthologs), a procedure for automated phylogenomics using explicit phylogenetic inference. RIO analyses are performed over bootstrap resampled phylogenetic trees to estimate the reliability of orthology assignments. We also introduce supplementary concepts that are helpful for functional inference. RIO has been implemented as Perl pipeline connecting several C and Java programs. It is available at http://www.genetics.wustl.edu/eddy/forester/. A web server is at http://www.rio.wustl.edu/. RIO was tested on the Arabidopsis thaliana and Caenorhabditis elegans proteomes.
The RIO procedure is particularly useful for the automated detection of first representatives of novel protein subfamilies. We also describe how some orthologies can be misleading for functional inference.