Tree Reconciliation Research Articles

The Evolution of Extreme Genetic Variability in a Parasite-Resistance Complex.

Genomic regions that play a role in parasite defense are often found to be highly variable, with the MHC serving as an iconic example. Single nucleotide polymorphisms may represent only a small portion of this variability, with Indel polymorphisms and copy number variation further contributing. In extreme cases, haplotypes may no longer be recognized as orthologous. Understanding the evolution of such highly divergent regions is challenging because the most extreme variation is not visible using reference-assisted genomic approaches. Here we analyze the case of the Pasteuria Resistance Complex (PRC) in the crustacean Daphnia magna, a defense complex in the host against the common and virulent bacterium Pasteuria ramosa. Two haplotypes of this region have been previously described, with parts of it being non-homologous, and the region has been shown to be under balancing selection. Using pan-genome analysis and tree reconciliation methods to explore the evolution of the PRC and its characteristics within and between species of Daphnia and other Cladoceran species, our analysis revealed a remarkable diversity in this region even among host species, with many non-homologous hyper-divergent-haplotypes. The PRC is characterized by extensive duplication and losses of Fucosyltransferase (FuT) and Galactosyltransferase (GalT) genes that are believed to play a role in parasite defense. The PRC region can be traced back to common ancestors over 250 million years. The unique combination of an ancient resistance complex and a dynamic, hyper-divergent genomic environment presents a fascinating opportunity to investigate the role of such regions in the evolution and long-term maintenance of resistance polymorphisms. Our findings offer valuable insights into the evolutionary forces shaping disease resistance and adaptation, not only in the genus Daphnia, but potentially across the entire Cladocera class.

Gene transfer among viruses substantially contributes to gene gain of giant viruses.

The phylum Nucleocytoviricota comprises a diverse group of double-stranded DNA viruses that display a wide range of gene repertoires. Although these gene repertoires determine the characteristics of individual viruses, the evolutionary processes that have shaped the gene repertoires of extant viruses since their common ancestor are poorly characterized. In this study, we aimed to address this gap in knowledge by using amalgamated likelihood estimation (ALE), a probabilistic tree reconciliation method that infers evolutionary scenarios by distinguishing origination, gene duplications, virus-to-virus horizontal gene transfer (vHGT), and gene losses. We analyzed over 4,700 gene families from 195 genomes spanning all known viral orders. The evolutionary reconstruction suggests a history of extensive gene gains and losses during the evolution of these viruses, notably with vHGT contributing to gene gains at a comparable level to duplications and originations. The vHGT frequently occurred between phylogenetically closely related viruses, as well as between distantly related viruses with an overlapping host range. We observed a pattern of massive gene duplications that followed vHGTs for gene families that was potentially related to host range control and virus-host arms race. These results suggest that vHGT represents a previously overlooked, yet important, evolutionary force that integrates the evolutionary paths of multiple viruses and affects shaping of Nucleocytoviricota virus gene repertoires.

Synesth: Comprehensive Syntenic Reconciliation with Unsampled Lineages

We present Synesth, the most comprehensive and flexible tool for tree reconciliation that allows for events on syntenies (i.e., on sets of multiple genes), including duplications, transfers, fissions, and transient events going through unsampled species. This model allows for building histories that explicate the inconsistencies between a synteny tree and its associated species tree. We examine the combinatorial properties of this extended reconciliation model and study various associated parsimony problems. First, the infinite set of explicatory histories is reduced to a finite but exponential set of Pareto-optimal histories (in terms of counts of each event type), then to a polynomial set of Pareto-optimal event count vectors, and this eventually ends with minimum event cost histories given an event cost function. An inductive characterization of the solution space using different algebras for each granularity leads to efficient dynamic programming algorithms, ultimately ending with an O(mn) time complexity algorithm for computing the cost of a minimum-cost history (m and n: number of nodes in the input synteny and species trees). This time complexity matches that of the fastest known algorithms for classical gene reconciliation with transfers. We show how Synesth can be applied to infer Pareto-optimal evolutionary scenarios for CRISPR-Cas systems in a set of bacterial genomes.

AleRax: a tool for gene and species tree co-estimation and reconciliation under a probabilistic model of gene duplication, transfer, and loss.

Genomes are a rich source of information on the pattern and process of evolution across biological scales. How best to make use of that information is an active area of research in phylogenetics. Ideally, phylogenetic methods should not only model substitutions along gene trees, which explain differences between homologous gene sequences, but also the processes that generate the gene trees themselves along a shared species tree. To conduct accurate inferences, one needs to account for uncertainty at both levels, that is, in gene trees estimated from inherently short sequences and in their diverse evolutionary histories along a shared species tree. We present AleRax, a software that can infer reconciled gene trees together with a shared species tree using a simple, yet powerful, probabilistic model of gene duplication, transfer, and loss. A key feature of AleRax is its ability to account for uncertainty in the gene tree and its reconciliation by using an efficient approximation to calculate the joint phylogenetic-reconciliation likelihood and sample reconciled gene trees accordingly. Simulations and analyses of empirical data show that AleRax is one order of magnitude faster than competing gene tree inference tools while attaining the same accuracy. It is consistently more robust than species tree inference methods such as SpeciesRax and ASTRAL-Pro 2 under gene tree uncertainty. Finally, AleRax can process multiple gene families in parallel thereby allowing users to compare competing phylogenetic hypotheses and estimate model parameters, such as duplication, transfer, and loss probabilities for genome-scale datasets with hundreds of taxa. GNU GPL at https://github.com/BenoitMorel/AleRax and data are made available at https://cme.h-its.org/exelixis/material/alerax_data.tar.gz.

The evolution of the gliotoxin biosynthetic gene cluster in Penicillium fungi.

Fungi biosynthesize diverse secondary metabolites, small organic bioactive molecules with key roles in fungal ecology. Fungal secondary metabolites are often encoded by physically clustered genes known as biosynthetic gene clusters (BGCs). Fungi in the genus Penicillium produce a cadre of secondary metabolites, some of which are useful (e.g. the antibiotic penicillin and the cholesterol-lowering drug mevastatin) and others harmful (e.g. the mycotoxin patulin and the immunosuppressant gliotoxin) to human affairs. Fungal genomes often also encode resistance genes that confer protection against toxic secondary metabolites. Some Penicillium species, such as Penicillium decumbens, are known to produce gliotoxin, a secondary metabolite with known immunosuppressant activity. To investigate the evolutionary conservation of homologs of the gliotoxin BGC and of genes involved in gliotoxin resistance in Penicillium, we analyzed 35 Penicillium genomes from 23 species. Homologous, lesser fragmented gliotoxin BGCs were found in 12 genomes, mostly fragmented remnants of the gliotoxin BGC were found in 21 genomes, whereas the remaining 2 Penicillium genomes lacked the gliotoxin BGC altogether. In contrast, broad conservation of homologs of resistance genes that reside outside the BGC across Penicillium genomes was observed. Evolutionary rate analysis revealed that BGCs with higher numbers of genes evolve slower than BGCs with few genes, suggestive of constraint and potential functional significance or more recent decay. Gene tree-species tree reconciliation analyses suggested that the history of homologs in the gliotoxin BGC across the genus Penicillium likely involved multiple duplications, losses, and horizontal gene transfers. Our analyses suggest that genes encoded in BGCs can have complex evolutionary histories and be retained in genomes long after the loss of secondary metabolite biosynthesis.

Orthogonal Procrustes and Machine Learning: Predicting Bill of Materials errors on time

In an industrial product development process, the Bill of Materials (BOM) is a hierarchical, multi-level representation of all components, parts and quantities of a product. With increasing complexity of industrial products, also BOMs become more complex and thus prone to errors, for example when the individual parts of a product are changed during the product development process. Frequently, these Bill of Materials errors have to be identified manually or by using simple, rule-based schemes. In this paper, we provide a technical background of BOMs, showing the intricacy of temporal BOMs errors in an industrial product development process. The work of other authors, which focused on association mining and tree reconciliation to detect Bill of Materials errors, is analysed. We found that there is currently no system being able to prescribe where in a Bill of Materials and when in the product development process, errors are probable to occur. Also, Machine Learning (ML) methods have not been applied yet. Based on these findings, we formalize the notions Bill of Materials and Bill of Materials errors. Furthermore, we present a deterministic distance measure for BOMS. We provide an answer to the main question of how to represent a Bill of Materials for Machine Learning tasks by solving the orthogonal Procrustes problem for dynamic, hierarchical datasets. Then, we describe an isolation forest based approach to temporal anomaly detection, which points at potential errors in a Bill of Materials at a specific timestamp. Furthermore, we apply Machine Learning and present a multi-output Multi Layer Perceptron for the prediction of temporal Bill of Materials errors. The model predicts where and at which point of time Bill of Materials errors are probable to occur, which renders it a prescriptive system. Eventually, we optimize the performance of our model using contextualization via k-means clustering. Finally, we apply our prescriptive pipeline to a real world dataset and show its superiority to existing methods using a qualitative comparison.

Cophylogeny Reconstruction Allowing for Multiple Associations Through Approximate Bayesian Computation.

Phylogenetic tree reconciliation is extensively employed for the examination of coevolution between host and symbiont species. An important concern is the requirement for dependable cost values when selecting event-based parsimonious reconciliation. Although certain approaches deduce event probabilities unique to each pair of host and symbiont trees, which can subsequently be converted into cost values, a significant limitation lies in their inability to model the invasion of diverse host species by the same symbiont species (termed as a spread event), which is believed to occur in symbiotic relationships. Invasions lead to the observation of multiple associations between symbionts and their hosts (indicating that a symbiont is no longer exclusive to a single host), which are incompatible with the existing methods of coevolution. Here, we present a method called AmoCoala (an enhanced version of the tool Coala) that provides a more realistic estimation of cophylogeny event probabilities for a given pair of host and symbiont trees, even in the presence of spread events. We expand the classical 4-event coevolutionary model to include 2 additional outcomes, vertical and horizontal spreads, that lead to multiple associations. In the initial step, we estimate the probabilities of spread events using heuristic frequencies. Subsequently, in the second step, we employ an approximate Bayesian computation approach to infer the probabilities of the remaining 4 classical events (cospeciation, duplication, host switch, and loss) based on these values. By incorporating spread events, our reconciliation model enables a more accurate consideration of multiple associations. This improvement enhances the precision of estimated cost sets, paving the way to a more reliable reconciliation of host and symbiont trees. To validate our method, we conducted experiments on synthetic datasets and demonstrated its efficacy using real-world examples. Our results showcase that AmoCoala produces biologically plausible reconciliation scenarios, further emphasizing its effectiveness.

On the complexity of non-binary tree reconciliation with endosymbiotic gene transfer

Reconciling a non-binary gene tree with a binary species tree can be done efficiently in the absence of horizontal gene transfers, but becomes NP-hard in the presence of gene transfers. Here, we focus on the special case of endosymbiotic gene transfers (EGT), i.e. transfers between the mitochondrial and nuclear genome of the same species. More precisely, given a multifurcated (non-binary) gene tree with leaves labeled 0 or 1 depending on whether the corresponding genes belong to the mitochondrial or nuclear genome of the corresponding species, we investigate the problem of inferring a most parsimonious Duplication, Loss and EGT (DLE) Reconciliation of any binary refinement of the tree. We present a general two-steps method: ignoring the 0–1 labeling of leaves, output a binary resolution minimizing the Duplication and Loss (DL) Reconciliation and then, for such resolution, assign a known number of 0s and 1s to the leaves in a way minimizing EGT events. While the first step corresponds to the well studied non-binary DL-Reconciliation problem, the complexity of the label assignment problem corresponding to the second step is unknown. We show that this problem is NP-complete, even when the tree is restricted to a single polytomy, and even if transfers can occur in only one direction. We present a general algorithm solving each polytomy separately, which is shown optimal for a unitary cost of operation, and a polynomial-time algorithm for solving a polytomy in the special case where genes are specific to a single genome (mitochondrial or nuclear) in all but one species. This work represents the first algorithmic study for reconciliation with endosymbiotic gene transfers in the case of a multifurcated gene tree.

Parameter Estimation and Species Tree Rooting Using ALE and GeneRax.

ALE and GeneRax are tools for probabilistic gene tree-species tree reconciliation. Based on a common underlying statistical model of how gene trees evolve along species trees, these methods rely on gene vs. species tree discordance to infer gene duplication, transfer, and loss events, map gene family origins, and root species trees. Published analyses have used these methods to root species trees of Archaea, Bacteria, and several eukaryotic groups, as well as to infer ancestral gene repertoires. However, it was recently suggested that reconciliation-based estimates of duplication and transfer events using the ALE/GeneRax model were unreliable, with potential implications for species tree rooting. Here, we assess these criticisms and find that the methods are accurate when applied to simulated data and in generally good agreement with alternative methodological approaches on empirical data. In particular, ALE recovers variation in gene duplication and transfer frequencies across lineages that is consistent with the known biology of studied clades. In plants and opisthokonts, ALE recovers the consensus species tree root; in Bacteria-where there is less certainty about the root position-ALE agrees with alternative approaches on the most likely root region. Overall, ALE and related approaches are promising tools for studying genome evolution.

Inference and reconstruction of the heimdallarchaeial ancestry of eukaryotes

In the ongoing debates about eukaryogenesis—the series of evolutionary events leading to the emergence of the eukaryotic cell from prokaryotic ancestors—members of the Asgard archaea play a key part as the closest archaeal relatives of eukaryotes1. However, the nature and phylogenetic identity of the last common ancestor of Asgard archaea and eukaryotes remain unresolved2–4. Here we analyse distinct phylogenetic marker datasets of an expanded genomic sampling of Asgard archaea and evaluate competing evolutionary scenarios using state-of-the-art phylogenomic approaches. We find that eukaryotes are placed, with high confidence, as a well-nested clade within Asgard archaea and as a sister lineage to Hodarchaeales, a newly proposed order within Heimdallarchaeia. Using sophisticated gene tree and species tree reconciliation approaches, we show that analogous to the evolution of eukaryotic genomes, genome evolution in Asgard archaea involved significantly more gene duplication and fewer gene loss events compared with other archaea. Finally, we infer that the last common ancestor of Asgard archaea was probably a thermophilic chemolithotroph and that the lineage from which eukaryotes evolved adapted to mesophilic conditions and acquired the genetic potential to support a heterotrophic lifestyle. Our work provides key insights into the prokaryote-to-eukaryote transition and a platform for better understanding the emergence of cellular complexity in eukaryotic cells.

A Variant Q-Sorting Methodology for Building Diagnostic Trees

Diagnostic theories are fundamental to information system (IS) practice and are represented as trees. While there are approaches for validating diagnostic trees, these validate the overall performance of the tree rather than identifying ways incorrect diagnoses can occur. It is important to fully validate diagnostic trees because even if the tree gives the correct decision “most of the time,” it is possible for incorrect decisions traveling down little-used branches of the tree to result in catastrophic decisions. In this article, we describe the process of using a variant of q-sorting to validate diagnostic trees. In this methodology, diagnostic trees that independent experts develop are transformed into a quantitative form, and that quantitative form is tested to determine the inter-rater reliability of the individual branches in the tree. The trees are then successively transformed to incrementally test if they branch in the same way. The results help researchers not only identify quality items for use in a diagnostic tree but also facilitate diagnoses of problems with those items and facilitate the reconciliation of discrepant trees by experts. The methodology validates not only the whole tree but also its subparts.

Revisiting ancient polyploidy in leptosporangiate ferns.

Ferns, and particularly homosporous ferns, have long been assumed to have experienced recurrent whole-genome duplication (WGD) events because of their substantially large genome sizes, surprisingly high chromosome numbers, and high degrees of polyploidy among many extant members. As the number of sequenced fern genomes is limited, recent studies have employed transcriptome data to find evidence for WGDs in ferns. However, they have reached conflicting results concerning the occurrence of ancient polyploidy, for instance, in the lineage of leptosporangiate ferns. Because identifying WGDs in a phylogenetic context is the foremost step in studying the contribution of ancient polyploidy to evolution, we here revisited earlier identified WGDs in leptosporangiate ferns, mainly the core leptosporangiate ferns, by building KS -age distributions and applying substitution rate corrections and by conducting statistical gene tree-species tree reconciliation analyses. Our integrative analyses not only identified four ancient WGDs in the sampled core leptosporangiate ferns but also identified false positives and false negatives for WGDs that recent studies have reported earlier. In conclusion, we underscore the significance of substitution rate corrections and uncertainties in gene tree-species tree reconciliations in calling WGD events and advance an exemplar workflow to overcome such often-overlooked issues.

WGDTree: a phylogenetic software tool to examine conditional probabilities of retention following whole genome duplication events

BackgroundMultiple processes impact the probability of retention of individual genes following whole genome duplication (WGD) events. In analyzing two consecutive whole genome duplication events that occurred in the lineage leading to Atlantic salmon, a new phylogenetic statistical analysis was developed to examine the contingency of retention in one event based upon retention in a previous event. This analysis is intended to evaluate mechanisms of duplicate gene retention and to provide software to generate the test statistic for any genome with pairs of WGDs in its history.ResultsHere a software package written in Python, ‘WGDTree’ for the analysis of duplicate gene retention following whole genome duplication events is presented. Using gene tree-species tree reconciliation to label gene duplicate nodes and differentiate between WGD and SSD duplicates, the tool calculates a statistic based upon the conditional probability of a gene duplicate being retained after a second whole genome duplication dependent upon the retention status after the first event. The package also contains methods for the simulation of gene trees with WGD events. After running simulations, the accuracy of the placement of events has been determined to be high. The conditional probability statistic has been calculated for Phalaenopsis equestris on a monocot species tree with a pair of consecutive WGD events on its lineage, showing the applicability of the method.ConclusionsA new software tool has been created for the analysis of duplicate genes in examination of retention mechanisms. The software tool has been made available on the Python package index and the source code can be found on GitHub here: https://github.com/cnickh/wgdtree.

Phylogenomics as an effective approach to untangle cross-species hybridization event: A case study in the family Nymphaeaceae

Hybridization is common and considered as an important evolutionary force to increase intraspecific genetic diversity. Detecting hybridization events is crucial for understanding the evolutionary history of species and further improving molecular breeding. The studies on identifying hybridization events through the phylogenomic approach are still limited. We proposed the conception and method of identifying allopolyploidy events by phylogenomics. The reconciliation and summary of nuclear multi-labeled gene family trees were adopted to untangle hybridization events from next-generation data in our novel phylogenomic approach. Given horticulturalists' relatively clear cultivated crossbreeding history, the water lily family is a suitable case for examining recent allopolyploidy events. Here, we reconstructed and confirmed the well-resolved nuclear phylogeny for the Nymphaeales family in the context of geological time as a framework for identifying hybridization signals. We successfully identified two possible allopolyploidy events with the parental lineages for the hybrids in the family Nymphaeaceae based on summarization from multi-labeled gene family trees of Nymphaeales. The lineages where species Nymphaea colorata and Nymphaea caerulea are located may be the progenitors of horticultural cultivated species Nymphaea 'midnight' and Nymphaea 'Woods blue goddess'. The proposed hybridization hypothesis is also supported by horticultural breeding records. Our methodology can be widely applied to identify hybridization events and theoretically facilitate the genome breeding design of hybrid plants.

Tree2GD: a phylogenomic method to detect large-scale gene duplication events.

Whole-genome duplication events have long been discovered throughout the evolution of eukaryotes, contributing to genome complexity and biodiversity and leaving traces in the descending organisms. Therefore, an accurate and rapid phylogenomic method is needed to identify the retained duplicated genes on various lineages across the target taxonomy. Here, we present Tree2GD, an integrated method to identify large-scale gene duplication events by automatically perform multiple procedures, including sequence alignment, recognition of homolog, gene tree/species tree reconciliation, Ks distribution of gene duplicates and synteny analyses. Application of Tree2GD on 2 datasets, 12 metazoan genomes and 68 angiosperms, successfully identifies all reported whole-genome duplication events exhibited by these species, showing effectiveness and efficiency of Tree2GD on phylogenomic analyses of large-scale gene duplications. Tree2GD is written in Python and C++ and is available at https://github.com/Dee-chen/Tree2gd. Supplementary data are available at Bioinformatics online.

A Polynomial-Time Algorithm for Minimizing the Deep Coalescence Cost for Level-1 Species Networks.

Phylogenetic analyses commonly assume that the species history can be represented as a tree. However, in the presence of hybridization, the species history is more accurately captured as a network. Despite several advances in modeling phylogenetic networks, there is no known polynomial-time algorithm for parsimoniously reconciling gene trees with species networks while accounting for incomplete lineage sorting. To address this issue, we present a polynomial-time algorithm for the case of level-1 networks, in which no hybrid species is the direct ancestor of another hybrid species. This work enables more efficient reconciliation of gene trees with species networks, which in turn, enables more efficient reconstruction of species networks.

Massive Loss of Transcription Factors Promotes the Initial Diversification of Placental Mammals.

As one of the most successful group of organisms, mammals occupy a variety of niches on Earth as a result of macroevolution. Transcription factors (TFs), the fundamental regulators of gene expression, may also have evolved. To examine the relationship between TFs and mammalian macroevolution, we analyzed 140,821 de novo-identified TFs and their birth and death histories from 96 mammalian species. Gene tree vs. species tree reconciliation revealed that placental mammals experienced an upsurge in TF losses around 100 million years ago (Mya) and also near the Cretaceous–Paleogene boundary (K–Pg boundary, 66 Mya). Early Euarchontoglires, Laurasiatheria and marsupials appeared between 100 and 95 Mya and underwent initial diversification. The K-Pg boundary was associated with the massive extinction of dinosaurs, which lead to adaptive radiation of mammals. Surprisingly, TF loss decelerated, rather than accelerated, molecular evolutionary rates of their target genes. As the rate of molecular evolution is affected by the mutation rate, the proportion of neutral mutations and the population size, the decrease in molecular evolution may reflect increased functional constraints to survive target genes.

Idahoa and Subularia: Hidden polyploid origins of two enigmatic genera of crucifers.

The monotypic Idahoa (I. scapigera) and the bispecific Subularia (S. aquatica and S. monticola) belong to Brassicaceae with unclear phylogenetic relationships and no tribal assignment. To fill this knowledge gap, we investigated these species and their closest relatives by combining cytogenomic and phylogenomic methods. We used whole plastome sequences in maximum likelihood and Bayesian inference analyses. We tested the phylogenetic informativeness of shared genomic repeats. We combined nuclear gene tree reconciliation and comparative chromosome painting (CCP) to examine the occurrence of past whole-genome duplications (WGDs). The plastid data set corroborated the sister relationship between Idahoa and Subularia within the crucifer Lineage V but failed to resolve consistent topologies using both inference methods. The shared repetitive sequences provided conflicting pwhylogenetic signals. CCP analysis unexpectedly revealed that Idahoa (2n = 16) has a diploidized mesotetraploid genome, whereas two Subularia species (2n = 28 and 30) have diploidized mesoctoploid genomes. Several ancient allopolyploidy events have also been detected in closely related taxa (Chamira circaeoides, Cremolobeae, Eudemeae, and Notothlaspideae). Our results suggest that the contentious phylogenetic placement of Idahoa and Subularia is best explained by two WGDs involving one or more shared parental genomes. The newly identified mesopolyploid genomes highlight the challenges of studying plant clades with complex polyploidy histories and provide a better framework for understanding genome evolution in the crucifer family.

Realistic Gene Transfer to Gene Duplication Ratios Identify Different Roots in the Bacterial Phylogeny Using a Tree Reconciliation Method.

The rooting of phylogenetic trees permits important inferences about ancestral states and the polarity of evolutionary events. Recently, methods that reconcile discordance between gene-trees and species-trees—tree reconciliation methods—are becoming increasingly popular for rooting species trees. Rooting via reconciliation requires values for a particular parameter, the gene transfer to gene duplication ratio (T:D), which in current practice is estimated on the fly from discordances observed in the trees. To date, the accuracy of T:D estimates obtained by reconciliation analyses has not been compared to T:D estimates obtained by independent means, hence the effect of T:D upon inferences of species tree roots is altogether unexplored. Here we investigated the issue in detail by performing tree reconciliations of more than 10,000 gene trees under a variety of T:D ratios for two phylogenetic cases: a bacterial (prokaryotic) tree with 265 species and a fungal-metazoan (eukaryotic) tree with 31 species. We show that the T:D ratios automatically estimated by a current tree reconciliation method, ALE, generate virtually identical T:D ratios across bacterial genes and fungal-metazoan genes. The T:D ratios estimated by ALE differ 10- to 100-fold from robust, ALE-independent estimates from real data. More important is our finding that the root inferences using ALE in both datasets are strongly dependent upon T:D. Using more realistic T:D ratios, the number of roots inferred by ALE consistently increases and, in some cases, clearly incorrect roots are inferred. Furthermore, our analyses reveal that gene duplications have a far greater impact on ALE’s preferences for phylogenetic root placement than gene transfers or gene losses do. Overall, we show that obtaining reliable species tree roots with ALE is only possible when gene duplications are abundant in the data and the number of falsely inferred gene duplications is low. Finding a sufficient sample of true gene duplications for rooting species trees critically depends on the T:D ratios used in the analyses. T:D ratios, while being important parameters of genome evolution in their own right, affect the root inferences with tree reconciliations to an unanticipated degree.

A Linear Time Solution to the Labeled Robinson-Foulds Distance Problem.

A large variety of pairwise measures of similarity or dissimilarity have been developed for comparing phylogenetic trees, for example, species trees or gene trees. Due to its intuitive definition in terms of tree clades and bipartitions and its computational efficiency, the Robinson–Foulds (RF) distance is the most widely used for trees with unweighted edges and labels restricted to leaves (representing the genetic elements being compared). However, in the case of gene trees, an important information revealing the nature of the homologous relation between gene pairs (orthologs, paralogs, and xenologs) is the type of event associated to each internal node of the tree, typically speciations or duplications, but other types of events may also be considered, such as horizontal gene transfers. This labeling of internal nodes is usually inferred from a gene tree/species tree reconciliation method. Here, we address the problem of comparing such event-labeled trees. The problem differs from the classical problem of comparing uniformly labeled trees (all labels belonging to the same alphabet) that may be done using the Tree Edit Distance (TED) mainly due to the fact that, in our case, two different alphabets are considered for the leaves and internal nodes of the tree, and leaves are not affected by edit operations. We propose an extension of the RF distance to event-labeled trees, based on edit operations comparable to those considered for TED: node insertion, node deletion, and label substitution. We show that this new Labeled Robinson–Foulds (LRF) distance can be computed in linear time, in addition of maintaining other desirable properties: being a metric, reducing to RF for trees with no labels on internal nodes and maintaining an intuitive interpretation. The algorithm for computing the LRF distance enables novel analyses on event-label trees such as reconciled gene trees. Here, we use it to study the impact of taxon sampling on labeled gene tree inference and conclude that denser taxon sampling yields trees with better topology but worse labeling. [Algorithms; combinatorics; gene trees; phylogenetics; Robinson–Foulds; tree distance.]