An approach of orthology detection from homologous sequences under minimum evolution

In the field of phylogenetics and comparative genomics, it is important to establish orthologous relationships when comparing homologous sequences. Due to the slight sequence dissimilarity between orthologs and paralogs, it is prone to regarding paralogs as orthologs. For this reason, several methods based on evolutionary distance, phylogeny and BLAST have tried to detect orthologs with more precision. Depending on their algorithmic implementations, each of these methods sometimes has increased false negative or false positive rates. Here, we developed a novel algorithm for orthology detection that uses a distance method based on the phylogenetic criterion of minimum evolution. Our algorithm assumes that sets of sequences exhibiting orthologous relationships are evolutionarily less costly than sets that include one or more paralogous relationships. Calculation of evolutionary cost requires the reconstruction of a neighbor-joining (NJ) tree, but calculations are unaffected by the topology of any given NJ tree. Unlike tree reconciliation, our algorithm appears free from the problem of incorrect topologies of species and gene trees. The reliability of the algorithm was tested in a comparative analysis with two other orthology detection methods using 95 manually curated KOG datasets and 21 experimentally verified EXProt datasets. Sensitivity and specificity estimates indicate that the concept of minimum evolution could be valuable for the detection of orthologs.     

Tree pattern matching in phylogenetic trees: automatic search for orthologs or paralogs in homologous gene sequence databases

MOTIVATION: Comparative sequence analysis is widely used to study genome function and evolution. This approach first requires the identification of homologous genes and then the interpretation of their homology relationships (orthology or paralogy). To provide help in this complex task, we developed three databases of homologous genes containing sequences, multiple alignments and phylogenetic trees: HOBACGEN, HOVERGEN and HOGENOM. In this paper, we present two new tools for automating the search for orthologs or paralogs in these databases. RESULTS: First, we have developed and implemented an algorithm to infer speciation and duplication events by comparison of gene and species trees (tree reconciliation). Second, we have developed a general method to search in our databases the gene families for which the tree topology matches a peculiar tree pattern. This algorithm of unordered tree pattern matching has been implemented in the FamFetch graphical interface. With the help of a graphical editor, the user can specify the topology of the tree pattern, and set constraints on its nodes and leaves. Then, this pattern is compared with all the phylogenetic trees of the database, to retrieve the families in which one or several occurrences of this pattern are found. By specifying ad hoc patterns, it is therefore possible to identify orthologs in our databases.     

Computational methods for Gene Orthology inference

Accurate inference of orthologous genes is a pre-requisite for most comparative genomics studies, and is also important for functional annotation of new genomes. Identification of orthologous gene sets typically involves phylogenetic tree analysis, heuristic algorithms based on sequence conservation, synteny analysis, or some combination of these approaches. The most direct tree-based methods typically rely on the comparison of an individual gene tree with a species tree. Once the two trees are accurately constructed, orthologs are straightforwardly identified by the definition of orthology as those homologs that are related by speciation, rather than gene duplication, at their most recent point of origin. Although ideal for the purpose of orthology identification in principle, phylogenetic trees are computationally expensive to construct for large numbers of genes and genomes, and they often contain errors, especially at large evolutionary distances. Moreover, in many organisms, in particular prokaryotes and viruses, evolution does not appear to have followed a simple 'tree-like' mode, which makes conventional tree reconciliation inapplicable. Other, heuristic methods identify probable orthologs as the closest homologous pairs or groups of genes in a set of organisms. These approaches are faster and easier to automate than tree-based methods, with efficient implementations provided by graph-theoretical algorithms enabling comparisons of thousands of genomes. Comparisons of these two approaches show that, despite conceptual differences, they produce similar sets of orthologs, especially at short evolutionary distances. Synteny also can aid in identification of orthologs. Often, tree-based, sequence similarity- and synteny-based approaches can be combined into flexible hybrid methods.     

The serine repeat antigen (SERA) gene family phylogeny in Plasmodium: the impact of GC content and reconciliation of gene and species trees

Plasmodium falciparum is the parasite responsible for the most acute form of malaria in humans. Recently, the serine repeat antigen (SERA) in P. falciparum has attracted attention as a potential vaccine and drug target, and it has been shown to be a member of a large gene family. To clarify the relationships among the numerous P. falciparum SERAs and to identify orthologs to SERA5 and SERA6 in Plasmodium species affecting rodents, gene trees were inferred from nucleotide and amino acid sequence data for 33 putative SERA homologs in seven different species. (A distance method for nucleotide sequences that is specifically designed to accommodate differing GC content yielded results that were largely compatible with the amino acid tree. Standard-distance and maximum-likelihood methods for nucleotide sequences, on the other hand, yielded gene trees that differed in important respects.) To infer the pattern of duplication, speciation, and gene loss events in the SERA gene family history, the resulting gene trees were then "reconciled" with two competing Plasmodium species tree topologies that have been identified by previous phylogenetic studies. Parsimony of reconciliation was used as a criterion for selecting a gene tree/species tree pair and provided (1) support for one of the two species trees and for the core topology of the amino acid-derived gene tree, (2) a basis for critiquing fine detail in a poorly resolved region of the gene tree, (3) a set of predicted "missing genes" in some species, (4) clarification of the relationship among the P. falciparum SERA, and (5) some information about SERA5 and SERA6 orthologs in the rodent malaria parasites. Parsimony of reconciliation and a second criterion--implied mutational pattern at two key active sites in the SERA proteins-were also seen to be useful supplements to standard "bootstrap" analysis for inferred topologies.     

COCO-CL: hierarchical clustering of homology relations based on evolutionary correlations

MOTIVATION: Determining orthology relations among genes across multiple genomes is an important problem in the post-genomic era. Identifying orthologous genes can not only help predict functional annotations for newly sequenced or poorly characterized genomes, but can also help predict new protein-protein interactions. Unfortunately, determining orthology relation through computational methods is not straightforward due to the presence of paralogs. Traditional approaches have relied on pairwise sequence comparisons to construct graphs, which were then partitioned into putative clusters of orthologous groups. These methods do not attempt to preserve the non-transitivity and hierarchic nature of the orthology relation. RESULTS: We propose a new method, COCO-CL, for hierarchical clustering of homology relations and identification of orthologous groups of genes. Unlike previous approaches, which are based on pairwise sequence comparisons, our method explores the correlation of evolutionary histories of individual genes in a more global context. COCO-CL can be used as a semi-independent method to delineate the orthology/paralogy relation for a refined set of homologous proteins obtained using a less-conservative clustering approach, or as a refiner that removes putative out-paralogs from clusters computed using a more inclusive approach. We analyze our clustering results manually, with support from literature and functional annotations. Since our orthology determination procedure does not employ a species tree to infer duplication events, it can be used in situations when the species tree is unknown or uncertain. CONTACT: jothi@mail.nih.gov, przytyck@mail.nih.gov SUPPLEMENTARY INFORMATION: Supplementary materials are available at Bioinformatics online.     

Phylogeny of the Avian Family Ciconiidae (Storks) Based on CytochromebSequences and DNA–DNA Hybridization Distances

This study is a phylogenetic analysis of the avian family Ciconiidae, the storks, based on two molecular data sets: 1065 base pairs of sequence from the mitochondrial cytochromebgene and a complete matrix of single-copy nuclear DNA–DNA hybridization distances. Sixteen of the nineteen stork species were included in the cytochromebdata matrix, and fifteen in the DNA–DNA hybridization matrix. Both matrices included outgroups from the families Cathartidae (New World vultures) and Threskiornithidae (ibises, spoonbills). Optimal trees based on the two data sets were congruent in those nodes with strong bootstrap support. In the best-fit tree based on DNA–DNA hybridization distances, nodes defining relationships among very recently diverged species had low bootstrap support, while nodes defining more distant relationships had strong bootstrap support. In the optimal trees based on the sequence data, nodes defining relationships among recently diverged species had strong bootstrap support, while nodes defining basal relationships in the family had weak support and were incongruent among analyses. A combinable-component consensus of the best-fit DNA–DNA hybridization tree and a consensus tree based on different analyses of the cytochromebsequences provide the best estimate of relationships among stork species based on the two data sets.     

Iterative orthology prediction uncovers new mitochondrial proteins and identifies C12orf62 as the human ortholog of COX14, a protein involved in the assembly of cytochrome c oxidase

Background

Orthology is a central tenet of comparative genomics and ortholog identification is instrumental to protein function prediction. Major advances have been made to determine orthology relations among a set of homologous proteins. However, they depend on the comparison of individual sequences and do not take into account divergent orthologs.

Results

We have developed an iterative orthology prediction method, Ortho-Profile, that uses reciprocal best hits at the level of sequence profiles to infer orthology. It increases ortholog detection by 20% compared to sequence-to-sequence comparisons. Ortho-Profile predicts 598 human orthologs of mitochondrial proteins from Saccharomyces cerevisiae and Schizosaccharomyces pombe with 94% accuracy. Of these, 181 were not known to localize to mitochondria in mammals. Among the predictions of the Ortho-Profile method are 11 human cytochrome c oxidase (COX) assembly proteins that are implicated in mitochondrial function and disease. Their co-expression patterns, experimentally verified subcellular localization, and co-purification with human COX-associated proteins support these predictions. For the human gene C12orf62, the ortholog of S. cerevisiae COX14, we specifically confirm its role in negative regulation of the translation of cytochrome c oxidase.

Conclusions

Divergent homologs can often only be detected by comparing sequence profiles and profile-based hidden Markov models. The Ortho-Profile method takes advantage of these techniques in the quest for orthologs.     

Bayesian gene/species tree reconciliation and orthology analysis using MCMC

MOTIVATION: Comparative genomics in general and orthology analysis in particular are becoming increasingly important parts of gene function prediction. Previously, orthology analysis and reconciliation has been performed only with respect to the parsimony model. This discards many plausible solutions and sometimes precludes finding the correct one. In many other areas in bioinformatics probabilistic models have proven to be both more realistic and powerful than parsimony models. For instance, they allow for assessing solution reliability and consideration of alternative solutions in a uniform way. There is also an added benefit in making model assumptions explicit and therefore making model comparisons possible. For orthology analysis, uncertainty has recently been addressed using parsimonious reconciliation combined with bootstrap techniques. However, until now no probabilistic methods have been available. RESULTS: We introduce a probabilistic gene evolution model based on a birth-death process in which a gene tree evolves 'inside' a species tree. Based on this model, we develop a tool with the capacity to perform practical orthology analysis, based on Fitch's original definition, and more generally for reconciling pairs of gene and species trees. Our gene evolution model is biologically sound (Nei et al., 1997) and intuitively attractive. We develop a Bayesian analysis based on MCMC which facilitates approximation of an a posteriori distribution for reconciliations. That is, we can find the most probable reconciliations and estimate the probability of any reconciliation, given the observed gene tree. This also gives a way to estimate the probability that a pair of genes are orthologs. The main algorithmic contribution presented here consists of an algorithm for computing the likelihood of a given reconciliation. To the best of our knowledge, this is the first successful introduction of this type of probabilistic methods, which flourish in phylogeny analysis, into reconciliation and orthology analysis. The MCMC algorithm has been implemented and, although not yet being in its final form, tests show that it performs very well on synthetic as well as biological data. Using standard correspondences, our results carry over to allele trees as well as biogeography.     

Interior-branch and bootstrap tests of phylogenetic trees

We have compared statistical properties of the interior-branch and bootstrap tests of phylogenetic trees when the neighbor-joining tree- building method is used. For each interior branch of a predetermined topology, the interior-branch and bootstrap tests provide the confidence values, PC and PB, respectively, that indicate the extent of statistical support of the sequence cluster generated by the branch. In phylogenetic analysis these two values are often interpreted in the same way, and if PC and PB are high (say, > or = 0.95), the sequence cluster is regarded as reliable. We have shown that PC is in fact the complement of the P-value used in the standard statistical test, but PB is not. Actually, the bootstrap test usually underestimates the extent of statistical support of species clusters. The relationship between the confidence values obtained by the two tests varies with both the topology and expected branch lengths of the true (model) tree. The most conspicuous difference between PC and PB is observed when the true tree is starlike, and there is a tendency for the difference to increase as the number of sequences in the tree increases. The reason for this is that the bootstrap test tends to become progressively more conservative as the number of sequences in the tree increases. Unlike the bootstrap, the interior-branch test has the same statistical properties irrespective of the number of sequences used when a predetermined tree is considered. Therefore, the interior-branch test appears to be preferable to the bootstrap test as long as unbiased estimators of evolutionary distances are used. However, when the interior-branch is applied to a tree estimated from a given data set, PC may give an overestimate of statistical confidence. For this case, we developed a method for computing a modified version (P'C) of the PC value and showed that this P'C tends to give a conservative estimate of statistical confidence, though it is not as conservative as PB. In this paper we have introduced a model in which evolutionary distances between sequences follow a multivariate normal distribution. This model allowed us to study the relationships between the two tests analytically.      

Statistical properties of bootstrap estimation of phylogenetic variability from nucleotide sequences. I. Four taxa with a molecular clock.

The statistical properties of sample estimation and bootstrap estimation of phylogenetic variability from a sample of nucleotide sequences are studied by using model trees of three taxa with an outgroup and by assuming a constant rate of nucleotide substitution. The maximum-parsimony method of tree reconstruction is used. An analytic formula is derived for estimating the sequence length that is required if P, the probability of obtaining the true tree from the sampled sequences, is to be equal to or higher than a given value. Bootstrap estimation is formulated as a two-step sampling procedure: (1) sampling of sequences from the evolutionary process and (2) resampling of the original sequence sample. The probability that a bootstrap resampling of an original sequence sample will support the true tree is found to depend on the model tree, the sequence length, and the probability that a randomly chosen nucleotide site is an informative site. When a trifurcating tree is used as the model tree, the probability that one of the three bifurcating trees will appear in > or = 95% of the bootstrap replicates is < 5%, even if the number of bootstrap replicates is only 50; therefore, the probability of accepting an erroneous tree as the true tree is < 5% if that tree appears in > or = 95% of the bootstrap replicates and if more than 50 bootstrap replications are conducted. However, if a particular bifurcating tree is observed in, say, < 75% of the bootstrap replicates, then it cannot be claimed to be better than the trifurcating tree even if > or = 1,000 bootstrap replications are conducted. When a bifurcating tree is used as the model tree, the bootstrap approach tends to overestimate P when the sequences are very short, but it tends to underestimate that probability when the sequences are long. Moreover, simulation results show that, if a tree is accepted as the true tree only if it has appeared in > or = 95% of the bootstrap replicates, then the probability of failing to accept any bifurcating tree can be as large as 58% even when P = 95%, i.e., even when 95% of the samples from the evolutionary process will support the true tree. Thus, if the rate-constancy assumption holds, bootstrapping is a conservative approach for estimating the reliability of an inferred phylogeny for four taxa.     

Reconciling gene and genome duplication events: using multiple nuclear gene families to infer the phylogeny of the aquatic plant family Pontederiaceae

Most plant phylogenetic inference has used DNA sequence data from the plastid genome. This genome represents a single genealogical sample with no recombination among genes, potentially limiting the resolution of evolutionary relationships in some contexts. In contrast, nuclear DNA is inherently more difficult to employ for phylogeny reconstruction because major mutational events in the genome, including polyploidization, gene duplication, and gene extinction can result in homologous gene copies that are difficult to identify as orthologs or paralogs. Gene tree parsimony (GTP) can be used to infer the rooted species tree by fitting gene genealogies to species trees while simultaneously minimizing the estimated number of duplications needed to reconcile conflicts among them. Here, we use GTP for five nuclear gene families and a previously published plastid data set to reconstruct the phylogenetic backbone of the aquatic plant family Pontederiaceae. Plastid-based phylogenetic studies strongly supported extensive paraphyly of Eichhornia (one of the four major genera) but also depicted considerable ambiguity concerning the true root placement for the family. Our results indicate that species trees inferred from the nuclear genes (alone and in combination with the plastid data) are highly congruent with gene trees inferred from plastid data alone. Consideration of optimal and suboptimal gene tree reconciliations place the root of the family at (or near) a branch leading to the rare and locally restricted E. meyeri. We also explore methods to incorporate uncertainty in individual gene trees during reconciliation by considering their individual bootstrap profiles and relate inferred excesses of gene duplication events on individual branches to whole-genome duplication events inferred for the same branches. Our study improves understanding of the phylogenetic history of Pontederiaceae and also demonstrates the utility of GTP for phylogenetic analysis.     

Inferring species phylogenies from multiple genes: concatenated sequence tree versus consensus gene tree

Phylogenetic trees from multiple genes can be obtained in two fundamentally different ways. In one, gene sequences are concatenated into a super-gene alignment, which is then analyzed to generate the species tree. In the other, phylogenies are inferred separately from each gene, and a consensus of these gene phylogenies is used to represent the species tree. Here, we have compared these two approaches by means of computer simulation, using 448 parameter sets, including evolutionary rate, sequence length, base composition, and transition/transversion rate bias. In these simulations, we emphasized a worst-case scenario analysis in which 100 replicate datasets for each evolutionary parameter set (gene) were generated, and the replicate dataset that produced a tree topology showing the largest number of phylogenetic errors was selected to represent that parameter set. Both randomly selected and worst-case replicates were utilized to compare the consensus and concatenation approaches primarily using the neighbor-joining (NJ) method. We find that the concatenation approach yields more accurate trees, even when the sequences concatenated have evolved with very different substitution patterns and no attempts are made to accommodate these differences while inferring phylogenies. These results appear to hold true for parsimony and likelihood methods as well. The concatenation approach shows >95% accuracy with only 10 genes. However, this gain in accuracy is sometimes accompanied by reinforcement of certain systematic biases, resulting in spuriously high bootstrap support for incorrect partitions, whether we employ site, gene, or a combined bootstrap resampling approach. Therefore, it will be prudent to report the number of individual genes supporting an inferred clade in the concatenated sequence tree, in addition to the bootstrap support.     

Rapid and accurate taxonomic classification of insect (class Insecta) cytochrome c oxidase subunit 1 (COI) DNA barcode sequences using a naïve Bayesian classifier

Current methods to identify unknown insect (class Insecta) cytochrome c oxidase (COI barcode) sequences often rely on thresholds of distances that can be difficult to define, sequence similarity cut‐offs, or monophyly. Some of the most commonly used metagenomic classification methods do not provide a measure of confidence for the taxonomic assignments they provide. The aim of this study was to use a naïve Bayesian classifier (Wang et al. Applied and Environmental Microbiology, 2007; 73: 5261) to automate taxonomic assignments for large batches of insect COI sequences such as data obtained from high‐throughput environmental sequencing. This method provides rank‐flexible taxonomic assignments with an associated bootstrap support value, and it is faster than the blast ‐based methods commonly used in environmental sequence surveys. We have developed and rigorously tested the performance of three different training sets using leave‐one‐out cross‐validation, two field data sets, and targeted testing of Lepidoptera, Diptera and Mantodea sequences obtained from the Barcode of Life Data system. We found that type I error rates, incorrect taxonomic assignments with a high bootstrap support, were already relatively low but could be lowered further by ensuring that all query taxa are actually present in the reference database. Choosing bootstrap support cut‐offs according to query length and summarizing taxonomic assignments to more inclusive ranks can also help to reduce error while retaining the maximum number of assignments. Additionally, we highlight gaps in the taxonomic and geographic representation of insects in public sequence databases that will require further work by taxonomists to improve the quality of assignments generated using any method.     

Inferring angiosperm phylogeny from EST data with widespread gene duplication

Background

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.

Results

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.

Conclusion

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.

     

Phylogenetic relationships of Steinernema Travassos, 1927 (Nematoda: Cephalobina: Steinernematidae) based on nuclear, mitochondrial and morphological data

Entomopathogenic nematodes of the genus Steinernema are lethal parasites of insects that are used as biological control agents of several lepidopteran, dipteran and coleopteran pests. Phylogenetic relationships among 25 Steinernema species were estimated using nucleotide sequences from three genes and 22 morphological characters. Parsimony analysis of 28S (LSU) sequences yielded a well-resolved phylogenetic hypothesis with reliable bootstrap support for 13 clades. Parsimony analysis of mitochondrial DNA sequences (12S rDNA and cox 1 genes) yielded phylogenetic trees with a lower consistency index than for LSU sequences, and with fewer reliably supported clades. Combined phylogenetic analysis of the 3-gene dataset by parsimony and Bayesian methods yielded well-resolved and highly similar trees. Bayesian posterior probabilities were high for most clades; bootstrap (parsimony) support was reliable for approximately half of the internal nodes. Parsimony analysis of the morphological dataset yielded a poorly resolved tree, whereas total evidence analysis (molecular plus morphological data) yielded a phylogenetic hypothesis consistent with, but less resolved than trees inferred from combined molecular data. Parsimony mapping of morphological characters on the 3-gene trees showed that most structural features of steinernematids are highly homoplastic. The distribution of nematode foraging strategies on these trees predicts that S. hermaphroditum, S. diaprepesi and S. longicaudum (US isolate) have cruise forager behaviours.     

Analysis of the Distribution of Bootstrap Tree Lengths Using the Maximum Parsimony Method

The bootstrap is an important tool for estimating the confidence interval of monophyletic groups within phylogenies. Although bootstrap analyses are used in most evolutionary studies, there is no clear consensus as how best to interpret bootstrap probability values. To study further the bootstrap method, nine small subunit ribosomal DNA (SSU rDNA) data sets were submitted to bootstrapped maximum parsimony (MP) analyses using unweighted and weighted sequence positions. Analyses of the lengths (i.e., parsimony steps) of the bootstrap trees show that the shape and mean of the bootstrap tree distribution may provide important insights into the evolutionary signal within the sequence data. With complex phylogenies containing nodes defined by short internal branches (multifurcations), the mean of the bootstrap tree distribution may differ by 2 standard deviations from the length of the best tree found from the original data set. Weighting sequence positions significantly increases the bootstrap values at internal nodes. There may, however, be strong bootstrap support for conflicting species groupings among different data sets. This phenomenon appears to result from a correlation between the topology of the tree used to create the weights and the topology of the bootstrap consensus tree inferred from the MP analysis of these weighted data. The analyses also show that characteristics of the bootstrap tree distribution (e.g., skewness) may be used to choose between alternative weighting schemes for phylogenetic analyses.     

Evolutionary constraints on structural similarity in orthologs and paralogs

Although a quantitative relationship between sequence similarity and structural similarity has long been established, little is known about the impact of orthology on the relationship between protein sequence and structure. Among homologs, orthologs (derived by speciation) more frequently have similar functions than paralogs (derived by duplication). Here, we hypothesize that an orthologous pair will tend to exhibit greater structural similarity than a paralogous pair at the same level of sequence similarity. To test this hypothesis, we used 284,459 pairwise structure‐based alignments of 12,634 unique domains from SCOP as well as orthology and paralogy assignments from OrthoMCL DB. We divided the comparisons by sequence identity and determined whether the sequence‐structure relationship differed between the orthologs and paralogs. We found that at levels of sequence identity between 30 and 70%, orthologous domain pairs indeed tend to be significantly more structurally similar than paralogous pairs at the same level of sequence identity. An even larger difference is found when comparing ligand binding residues instead of whole domains. These differences between orthologs and paralogs are expected to be useful for selecting template structures in comparative modeling and target proteins in structural genomics.     

Trees within trees: genes and species, molecules and morphology

The construction and interpretation of gene trees is fundamental in molecular systematics. If the gene is defined in a historical (coalescent) sense, there can be multiple gene trees within the single contiguous set of nucleotides, and attempts to construct a single tree for such a sequence must deal with homoplasy created by conflict among divergent histories. On a larger scale, incongruence is expected among gene tree topologies at different loci of individuals within sexually reproducing species, and it has been suggested that this discordance can be used to delimit species. A practical concern for such topological methods is that polymorphisms may be maintained through numerous cladogenic events; this polymorphism problem is less of a concern for nontopological approaches to species delimitation using molecular data. Although a central theoretical concern in molecular systematics is discordance between a given gene tree and the true "species tree," the primary empirical problem faced in reconstructing taxic phylogeny is incongruence among the trees inferred from different sequences. Linkage relationships limit character independence and thus have important implications for handling multiple data sets in phylogenetic analysis, particularly at the species level, where incongruence among different historically associated loci is expected. Gene trees can also be reconstructed for loci that influence phenotypic characters, but there is at best a tenuous relationship between phenotypic homoplasy and homoplasy in such gene trees. Nevertheless, expression patterns and orthology relationships of genes involved in the expression of phenotypes can in theory provide criteria for homology assessment of morphological characters.     

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.