Gene Tree Parsimony Research Articles

Phylogenomic Analyses of 2,786 Genes in 158 Lineages Support a Root of the Eukaryotic Tree of Life between Opisthokonts and All Other Lineages.

Advances in phylogenomics and high-throughput sequencing have allowed the reconstruction of deep phylogenetic relationships in the evolution of eukaryotes. Yet, the root of the eukaryotic tree of life remains elusive. The most popular hypothesis in textbooks and reviews is a root between Unikonta (Opisthokonta + Amoebozoa) and Bikonta (all other eukaryotes), which emerged from analyses of a single-gene fusion. Subsequent, highly cited studies based on concatenation of genes supported this hypothesis with some variations or proposed a root within Excavata. However, concatenation of genes does not consider phylogenetically-informative events like gene duplications and losses. A recent study using gene tree parsimony (GTP) suggested the root lies between Opisthokonta and all other eukaryotes, but only including 59 taxa and 20 genes. Here we use GTP with a duplication-loss model in a gene-rich and taxon-rich dataset (i.e., 2,786 gene families from two sets of 155 and 158 diverse eukaryotic lineages) to assess the root, and we iterate each analysis 100 times to quantify tree space uncertainty. We also contrasted our results and discarded alternative hypotheses from the literature using GTP and the likelihood-based method SpeciesRax. Our estimates suggest a root between Fungi or Opisthokonta and all other eukaryotes; but based on further analysis of genome size, we propose that the root between Opisthokonta and all other eukaryotes is the most likely.

Gene tree parsimony for incomplete gene trees: addressing true biological loss

Motivation Species tree estimation from gene trees can be complicated by gene duplication and loss, and “gene tree parsimony” (GTP) is one approach for estimating species trees from multiple gene trees. In its standard formulation, the objective is to find a species tree that minimizes the total number of gene duplications and losses with respect to the input set of gene trees. Although much is known about GTP, little is known about how to treat inputs containing some incomplete gene trees (i.e., gene trees lacking one or more of the species).ResultsWe present new theory for GTP considering whether the incompleteness is due to gene birth and death (i.e., true biological loss) or taxon sampling, and present dynamic programming algorithms that can be used for an exact but exponential time solution for small numbers of taxa, or as a heuristic for larger numbers of taxa. We also prove that the “standard” calculations for duplications and losses exactly solve GTP when incompleteness results from taxon sampling, although they can be incorrect when incompleteness results from true biological loss. The software for the DP algorithm is freely available as open source code at https://github.com/smirarab/DynaDup.

Bijective Diameters of Gene Tree Parsimony Costs.

Synthesizing median trees from a collection of gene trees under the biologically motivated gene tree parsimony (GTP) costs has provided credible species tree estimates. GTP costs are defined for each of the classic evolutionary processes. These costs count the minimum number of events necessary to reconcile the gene tree with the species tree where the leaf-genes are mapped to the leaf-species through a function called labeling. To better understand the synthesis of median trees under these costs, there is an increased interest in analyzing their diameters. The diameters of a GTP cost between a gene tree and a species tree are the maximum values of this cost of one or both topologies of the trees involved. We are concerned about the diameters of the GTP costs under bijective labelings. While these diameters are linear time computable for the gene duplication and deep coalescence costs, this has been unknown for the classic gene duplication and loss, and for the loss cost. For the first time, we show how to compute these diameters and proof that this can be achieved in linear time, and thus, completing the computational time analysis for all of the bijective diameters under the GTP costs.

Venom Evolution: Gene Loss Shapes Phenotypic Adaptation

Snake venoms are variable protein mixtures with a multitude of bioactivities. New work shows, surprisingly, that it is the loss of toxin-encoding genes that strongly influences venom function in rattlesnakes, highlighting how gene loss can underpin adaptive phenotypic change.

Impact of gene family evolutionary histories on phylogenetic species tree inference by gene tree parsimony

Complicated history of gene duplication and loss brings challenge to molecular phylogenetic inference, especially in deep phylogenies. However, phylogenomic approaches, such as gene tree parsimony (GTP), show advantage over some other approaches in its ability to use gene families with duplications. GTP searches the ‘optimal’ species tree by minimizing the total cost of biological events such as duplications, but accuracy of GTP and phylogenetic signal in the context of different gene families with distinct histories of duplication and loss are unclear. To evaluate how different evolutionary properties of different gene families can impact on species tree inference, 3900 gene families from seven angiosperms encompassing a wide range of gene content, lineage-specific expansions and contractions were analyzed. It was found that the gene content and total duplication number in a gene family strongly influence species tree inference accuracy, with the highest accuracy achieved at either very low or very high gene content (or duplication number) and lowest accuracy centered in intermediate gene content (or duplication number), as the relationship can fit a binomial regression. Besides, for gene families of similar level of average gene content, those with relatively higher lineage-specific expansion or duplication rates tend to show lower accuracy. Additional correlation tests support that high accuracy for those gene families with large gene content may rely on abundant ancestral copies to provide many subtrees to resolve conflicts, whereas high accuracy for single or low copy gene families are just subject to sequence substitution per se. Very low accuracy reached by gene families of intermediate gene content or duplication number can be due to insufficient subtrees to resolve the conflicts from loss of alternative copies. As these evolutionary properties can significantly influence species tree accuracy, I discussed the potential weighting of the duplication cost by evolutionary properties of gene families in future GTP analyses.

Evidence of duplicated Hox genes in the most recent common ancestor of extant scorpions.

Scorpions (order Scorpiones) are unusual among arthropods, both for the extreme heteronomy of their bauplan and for the high gene family turnover exhibited in their genomes. These phenomena appear to be correlated, as two scorpion species have been shown to possess nearly twice the number of Hox genes present in most arthropods. Segmentally offset anterior expression boundaries of a subset of Hox paralogs have been shown to correspond to transitions in segmental identities in the scorpion posterior tagmata, suggesting that posterior heteronomy in scorpions may have been achieved by neofunctionalization of Hox paralogs. However, both the first scorpion genome sequenced and the developmental genetic data are based on exemplars of Buthidae, one of 19 families of scorpions. It is therefore not known whether Hox paralogy is limited to Buthidae or widespread among scorpions. We surveyed 24 high throughput transcriptomes and the single whole genome available for scorpions, in order to test the prediction that Hox gene duplications are common to the order. We used gene tree parsimony to infer whether the paralogy was consistent with a duplication event in the scorpion common ancestor. Here we show that duplicated Hox genes in non-buthid scorpions occur in six of the ten Hox classes. Gene tree topologies and parsimony-based reconciliation of the gene trees are consistent with a duplication event in the most recent common ancestor of scorpions. These results suggest that a Hox paralogy, and by extension the model of posterior patterning established in a buthid, can be extended to non-Buthidae scorpions.

Species Tree Inference Using a Mixture Model.

Species tree reconstruction has been a subject of substantial research due to its central role across biology and medicine. A species tree is often reconstructed using a set of gene trees or by directly using sequence data. In either of these cases, one of the main confounding phenomena is the discordance between a species tree and a gene tree due to evolutionary events such as duplications and losses. Probabilistic methods can resolve the discordance by coestimating gene trees and the species tree but this approach poses a scalability problem for larger data sets. We present MixTreEM-DLRS: A two-phase approach for reconstructing a species tree in the presence of gene duplications and losses. In the first phase, MixTreEM, a novel structural expectation maximization algorithm based on a mixture model is used to reconstruct a set of candidate species trees, given sequence data for monocopy gene families from the genomes under study. In the second phase, PrIME-DLRS, a method based on the DLRS model (Åkerborg O, Sennblad B, Arvestad L, Lagergren J. 2009. Simultaneous Bayesian gene tree reconstruction and reconciliation analysis. Proc Natl Acad Sci U S A. 106(14):5714-5719), is used for selecting the best species tree. PrIME-DLRS can handle multicopy gene families since DLRS, apart from modeling sequence evolution, models gene duplication and loss using a gene evolution model (Arvestad L, Lagergren J, Sennblad B. 2009. The gene evolution model and computing its associated probabilities. J ACM. 56(2):1-44). We evaluate MixTreEM-DLRS using synthetic and biological data, and compare its performance with a recent genome-scale species tree reconstruction method PHYLDOG (Boussau B, Szöllősi GJ, Duret L, Gouy M, Tannier E, Daubin V. 2013. Genome-scale coestimation of species and gene trees. Genome Res. 23(2):323-330) as well as with a fast parsimony-based algorithm Duptree (Wehe A, Bansal MS, Burleigh JG, Eulenstein O. 2008. Duptree: a program for large-scale phylogenetic analyses using gene tree parsimony. Bioinformatics 24(13):1540-1541). Our method is competitive with PHYLDOG in terms of accuracy and runs significantly faster and our method outperforms Duptree in accuracy. The analysis constituted by MixTreEM without DLRS may also be used for selecting the target species tree, yielding a fast and yet accurate algorithm for larger data sets. MixTreEM is freely available at http://prime.scilifelab.se/mixtreem/.

Assessing Approaches for Inferring Species Trees from Multi-Copy Genes

With the availability of genomic sequence data, there is increasing interest in using genes with a possible history of duplication and loss for species tree inference. Here we assess the performance of both nonprobabilistic and probabilistic species tree inference approaches using gene duplication and loss and coalescence simulations. We evaluated the performance of gene tree parsimony (GTP) based on duplication (Only-dup), duplication and loss (Dup-loss), and deep coalescence (Deep-c) costs, the NJst distance method, the MulRF supertree method, and PHYLDOG, which jointly estimates gene trees and species tree using a hierarchical probabilistic model. We examined the effects of gene tree and species sampling, gene tree error, and duplication and loss rates on the accuracy of phylogenetic estimates. In the 10-taxon duplication and loss simulation experiments, MulRF is more accurate than the other methods when the duplication and loss rates are low, and Dup-loss is generally the most accurate when the duplication and loss rates are high. PHYLDOG performs well in 10-taxon duplication and loss simulations, but its run time is prohibitively long on larger data sets. In the larger duplication and loss simulation experiments, MulRF outperforms all other methods in experiments with at most 100 taxa; however, in the larger simulation, Dup-loss generally performs best. In all duplication and loss simulation experiments with more than 10 taxa, all methods perform better with more gene trees and fewer missing sequences, and they are all affected by gene tree error. Our results also highlight high levels of error in estimates of duplications and losses from GTP methods and demonstrate the usefulness of methods based on generic tree distances for large analyses.

A Bayesian Supertree Model for Genome-Wide Species Tree Reconstruction.

Current phylogenomic data sets highlight the need for species tree methods able to deal with several sources of gene tree/species tree incongruence. At the same time, we need to make most use of all available data. Most species tree methods deal with single processes of phylogenetic discordance, namely, gene duplication and loss, incomplete lineage sorting (ILS) or horizontal gene transfer. In this manuscript, we address the problem of species tree inference from multilocus, genome-wide data sets regardless of the presence of gene duplication and loss and ILS therefore without the need to identify orthologs or to use a single individual per species. We do this by extending the idea of Maximum Likelihood (ML) supertrees to a hierarchical Bayesian model where several sources of gene tree/species tree disagreement can be accounted for in a modular manner. We implemented this model in a computer program called guenomu whose inputs are posterior distributions of unrooted gene tree topologies for multiple gene families, and whose output is the posterior distribution of rooted species tree topologies. We conducted extensive simulations to evaluate the performance of our approach in comparison with other species tree approaches able to deal with more than one leaf from the same species. Our method ranked best under simulated data sets, in spite of ignoring branch lengths, and performed well on empirical data, as well as being fast enough to analyze relatively large data sets. Our Bayesian supertree method was also very successful in obtaining better estimates of gene trees, by reducing the uncertainty in their distributions. In addition, our results show that under complex simulation scenarios, gene tree parsimony is also a competitive approach once we consider its speed, in contrast to more sophisticated models.

Inferring species trees from incongruent multi-copy gene trees using the Robinson-Foulds distance

BackgroundConstructing species trees from multi-copy gene trees remains a challenging problem in phylogenetics. One difficulty is that the underlying genes can be incongruent due to evolutionary processes such as gene duplication and loss, deep coalescence, or lateral gene transfer. Gene tree estimation errors may further exacerbate the difficulties of species tree estimation.ResultsWe present a new approach for inferring species trees from incongruent multi-copy gene trees that is based on a generalization of the Robinson-Foulds (RF) distance measure to multi-labeled trees (mul-trees). We prove that it is NP-hard to compute the RF distance between two mul-trees; however, it is easy to calculate this distance between a mul-tree and a singly-labeled species tree. Motivated by this, we formulate the RF problem for mul-trees (MulRF) as follows: Given a collection of multi-copy gene trees, find a singly-labeled species tree that minimizes the total RF distance from the input mul-trees. We develop and implement a fast SPR-based heuristic algorithm for the NP-hard MulRF problem.We compare the performance of the MulRF method (available at http://genome.cs.iastate.edu/CBL/MulRF/) with several gene tree parsimony approaches using gene tree simulations that incorporate gene tree error, gene duplications and losses, and/or lateral transfer. The MulRF method produces more accurate species trees than gene tree parsimony approaches. We also demonstrate that the MulRF method infers in minutes a credible plant species tree from a collection of nearly 2,000 gene trees.ConclusionsOur new phylogenetic inference method, based on a generalized RF distance, makes it possible to quickly estimate species trees from large genomic data sets. Since the MulRF method, unlike gene tree parsimony, is based on a generic tree distance measure, it is appealing for analyses of genomic data sets, in which many processes such as deep coalescence, recombination, gene duplication and losses as well as phylogenetic error may contribute to gene tree discord. In experiments, the MulRF method estimated species trees accurately and quickly, demonstrating MulRF as an efficient alternative approach for phylogenetic inference from large-scale genomic data sets.

Phylotranscriptomics: Saturated Third Codon Positions Radically Influence the Estimation of Trees Based on Next-Gen Data

Recent advancements in molecular sequencing techniques have led to a surge in the number of phylogenetic studies that incorporate large amounts of genetic data. We test the assumption that analyzing large number of genes will lead to improvements in tree resolution and branch support using moths in the superfamily Bombycoidea, a group with some interfamilial relationships that have been difficult to resolve. Specifically, we use a next-gen data set that included 19 taxa and 938 genes (∼1.2M bp) to examine how codon position and saturation might influence resolution and node support among three key families. Maximum likelihood, parsimony, and species tree analysis using gene tree parsimony, on different nucleotide and amino acid data sets, resulted in largely congruent topologies with high bootstrap support compared with prior studies that included fewer loci. However, for a few shallow nodes, nucleotide and amino acid data provided high support for conflicting relationships. The third codon position was saturated and phylogenetic analysis of this position alone supported a completely different, potentially misleading sister group relationship. We used the program RADICAL to assess the number of genes needed to fix some of these difficult nodes. One such node originally needed a total of 850 genes but only required 250 when synonymous signal was removed. Our study shows that, in order to effectively use next-gen data to correctly resolve difficult phylogenetic relationships, it is necessary to assess the effects of synonymous substitutions and third codon positions.

EXACT SOLUTIONS FOR SPECIES TREE INFERENCE FROM DISCORDANT GENE TREES

Phylogenetic analysis has to overcome the grant challenge of inferring accurate species trees from evolutionary histories of gene families (gene trees) that are discordant with the species tree along whose branches they have evolved. Two well studied approaches to cope with this challenge are to solve either biologically informed gene tree parsimony (GTP) problems under gene duplication, gene loss, and deep coalescence, or the classic RF supertree problem that does not rely on any biological model. Despite the potential of these problems to infer credible species trees, they are NP-hard. Therefore, these problems are addressed by heuristics that typically lack any provable accuracy and precision. We describe fast dynamic programming algorithms that solve the GTP problems and the RF supertree problem exactly, and demonstrate that our algorithms can solve instances with data sets consisting of as many as 22 taxa. Extensions of our algorithms can also report the number of all optimal species trees, as well as the trees themselves. To better asses the quality of the resulting species trees that best fit the given gene trees, we also compute the worst case species trees, their numbers, and optimization score for each of the computational problems. Finally, we demonstrate the performance of our exact algorithms using empirical and simulated data sets, and analyze the quality of heuristic solutions for the studied problems by contrasting them with our exact solutions.

Algorithms for Genome-Scale Phylogenetics Using Gene Tree Parsimony

The use of genomic data sets for phylogenetics is complicated by the fact that evolutionary processes such as gene duplication and loss, or incomplete lineage sorting (deep coalescence) cause incongruence among gene trees. One well-known approach that deals with this complication is gene tree parsimony, which, given a collection of gene trees, seeks a species tree that requires the smallest number of evolutionary events to explain the incongruence of the gene trees. However, a lack of efficient algorithms has limited the use of this approach. Here, we present efficient algorithms for SPR and TBR-based local search heuristics for gene tree parsimony under the 1) duplication, 2) loss, 3) duplication-loss, and 4) deep coalescence reconciliation costs. These novel algorithms improve upon the time complexities of previous algorithms for these problems by a factor of n, where n is the number of species in the collection of gene trees. Our algorithms provide a substantial improvement in runtime and scalability compared to previous implementations and enable large-scale gene tree parsimony analyses using any of the four reconciliation costs. Our algorithms have been implemented in the software packages DupTree and iGTP, and have already been used to perform several compelling phylogenetic studies.

Efficient error correction algorithms for gene tree reconciliation based on duplication, duplication and loss, and deep coalescence

BackgroundGene tree - species tree reconciliation problems infer the patterns and processes of gene evolution within a species tree. Gene tree parsimony approaches seek the evolutionary scenario that implies the fewest gene duplications, duplications and losses, or deep coalescence (incomplete lineage sorting) events needed to reconcile a gene tree and a species tree. While a gene tree parsimony approach can be informative about genome evolution and phylogenetics, error in gene trees can profoundly bias the results.ResultsWe introduce efficient algorithms that rapidly search local Subtree Prune and Regraft (SPR) or Tree Bisection and Reconnection (TBR) neighborhoods of a given gene tree to identify a topology that implies the fewest duplications, duplication and losses, or deep coalescence events. These algorithms improve on the current solutions by a factor of n for searching SPR neighborhoods and n2 for searching TBR neighborhoods, where n is the number of taxa in the given gene tree. They provide a fast error correction protocol for ameliorating the effects of gene tree error by allowing small rearrangements in the topology to improve the reconciliation cost. We also demonstrate a simple protocol to use the gene rearrangement algorithm to improve gene tree parsimony phylogenetic analyses.ConclusionsThe new gene tree rearrangement algorithms provide a fast method to address gene tree error. They do not make assumptions about the underlying processes of genome evolution, and they are amenable to analyses of large-scale genomic data sets. These algorithms are also easily incorporated into gene tree parsimony phylogenetic analyses, potentially producing more credible estimates of reconciliation cost.

Exploiting gene families for phylogenomic analysis of myzostomid transcriptome data.

BackgroundIn trying to understand the evolutionary relationships of organisms, the current flood of sequence data offers great opportunities, but also reveals new challenges with regard to data quality, the selection of data for subsequent analysis, and the automation of steps that were once done manually for single-gene analyses. Even though genome or transcriptome data is available for representatives of most bilaterian phyla, some enigmatic taxa still have an uncertain position in the animal tree of life. This is especially true for myzostomids, a group of symbiotic (or parasitic) protostomes that are either placed with annelids or flatworms.MethodologyBased on similarity criteria, Illumina-based transcriptome sequences of one myzostomid were compared to protein sequences of one additional myzostomid and 29 reference metazoa and clustered into gene families. These families were then used to investigate the phylogenetic position of Myzostomida using different approaches: Alignments of 989 sequence families were concatenated, and the resulting superalignment was analyzed under a Maximum Likelihood criterion. We also used all 1,878 gene trees with at least one myzostomid sequence for a supertree approach: the individual gene trees were computed and then reconciled into a species tree using gene tree parsimony.ConclusionsSuperalignments require strictly orthologous genes, and both the gene selection and the widely varying amount of data available for different taxa in our dataset may cause anomalous placements and low bootstrap support. In contrast, gene tree parsimony is designed to accommodate multilocus gene families and therefore allows a much more comprehensive data set to be analyzed. Results of this supertree approach showed a well-resolved phylogeny, in which myzostomids were part of the annelid radiation, and major bilaterian taxa were found to be monophyletic.

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.

Genome-scale phylogenetics: inferring the plant tree of life from 18,896 gene trees.

Phylogenetic analyses using genome-scale data sets must confront incongruence among gene trees, which in plants is exacerbated by frequent gene duplications and losses. Gene tree parsimony (GTP) is a phylogenetic optimization criterion in which a species tree that minimizes the number of gene duplications induced among a set of gene trees is selected. The run time performance of previous implementations has limited its use on large-scale data sets. We used new software that incorporates recent algorithmic advances to examine the performance of GTP on a plant data set consisting of 18,896 gene trees containing 510,922 protein sequences from 136 plant taxa (giving a combined alignment length of >2.9 million characters). The relationships inferred from the GTP analysis were largely consistent with previous large-scale studies of backbone plant phylogeny and resolved some controversial nodes. The placement of taxa that were present in few gene trees generally varied the most among GTP bootstrap replicates. Excluding these taxa either before or after the GTP analysis revealed high levels of phylogenetic support across plants. The analyses supported magnoliids sister to a eudicot + monocot clade and did not support the eurosid I and II clades. This study presents a nuclear genomic perspective on the broad-scale phylogenic relationships among plants, and it demonstrates that nuclear genes with a history of duplication and loss can be phylogenetically informative for resolving the plant tree of life.

IGTP: A software package for large-scale gene tree parsimony analysis

BackgroundThe ever-increasing wealth of genomic sequence information provides an unprecedented opportunity for large-scale phylogenetic analysis. However, species phylogeny inference is obfuscated by incongruence among gene trees due to evolutionary events such as gene duplication and loss, incomplete lineage sorting (deep coalescence), and horizontal gene transfer. Gene tree parsimony (GTP) addresses this issue by seeking a species tree that requires the minimum number of evolutionary events to reconcile a given set of incongruent gene trees. Despite its promise, the use of gene tree parsimony has been limited by the fact that existing software is either not fast enough to tackle large data sets or is restricted in the range of evolutionary events it can handle.ResultsWe introduce iGTP, a platform-independent software program that implements state-of-the-art algorithms that greatly speed up species tree inference under the duplication, duplication-loss, and deep coalescence reconciliation costs. iGTP significantly extends and improves the functionality and performance of existing gene tree parsimony software and offers advanced features such as building effective initial trees using stepwise leaf addition and the ability to have unrooted gene trees in the input. Moreover, iGTP provides a user-friendly graphical interface with integrated tree visualization software to facilitate analysis of the results.ConclusionsiGTP enables, for the first time, gene tree parsimony analyses of thousands of genes from hundreds of taxa using the duplication, duplication-loss, and deep coalescence reconciliation costs, all from within a convenient graphical user interface.

Gene Tree Parsimony of Multilocus Snake Venom Protein Families Reveals Species Tree Conflict as a Result of Multiple Parallel Gene Loss

The proliferation of gene data from multiple loci of large multigene families has been greatly facilitated by considerable recent advances in sequence generation. The evolution of such gene families, which often undergo complex histories and different rates of change, combined with increases in sequence data, pose complex problems for traditional phylogenetic analyses, and in particular, those that aim to successfully recover species relationships from gene trees. Here, we implement gene tree parsimony analyses on multicopy gene family data sets of snake venom proteins for two separate groups of taxa, incorporating Bayesian posterior distributions as a rigorous strategy to account for the uncertainty present in gene trees. Gene tree parsimony largely failed to infer species trees congruent with each other or with species phylogenies derived from mitochondrial and single-copy nuclear sequences. Analysis of four toxin gene families from a large expressed sequence tag data set from the viper genus Echis failed to produce a consistent topology, and reanalysis of a previously published gene tree parsimony data set, from the family Elapidae, suggested that species tree topologies were predominantly unsupported. We suggest that gene tree parsimony failure in the family Elapidae is likely the result of unequal and/or incomplete sampling of paralogous genes and demonstrate that multiple parallel gene losses are likely responsible for the significant species tree conflict observed in the genus Echis. These results highlight the potential for gene tree parsimony analyses to be undermined by rapidly evolving multilocus gene families under strong natural selection.

Efficient genome-scale phylogenetic analysis under the duplication-loss and deep coalescence cost models

BackgroundGenomic data provide a wealth of new information for phylogenetic analysis. Yet making use of this data requires phylogenetic methods that can efficiently analyze extremely large data sets and account for processes of gene evolution, such as gene duplication and loss, incomplete lineage sorting (deep coalescence), or horizontal gene transfer, that cause incongruence among gene trees. One such approach is gene tree parsimony, which, given a set of gene trees, seeks a species tree that requires the smallest number of evolutionary events to explain the incongruence of the gene trees. However, the only existing algorithms for gene tree parsimony under the duplication-loss or deep coalescence reconciliation cost are prohibitively slow for large datasets.ResultsWe describe novel algorithms for SPR and TBR based local search heuristics under the duplication-loss cost, and we show how they can be adapted for the deep coalescence cost. These algorithms improve upon the best existing algorithms for these problems by a factor of n, where n is the number of species in the collection of gene trees. We implemented our new SPR based local search algorithm for the duplication-loss cost and demonstrate the tremendous improvement in runtime and scalability it provides compared to existing implementations. We also evaluate the performance of our algorithm on three large-scale genomic data sets.ConclusionOur new algorithms enable, for the first time, gene tree parsimony analyses of thousands of genes from hundreds of taxa using the duplication-loss and deep coalescence reconciliation costs. Thus, this work expands both the size of data sets and the range of evolutionary models that can be incorporated into genome-scale phylogenetic analyses.