Species Tree Inference Research Articles

Species trees from consensus single nucleotide polymorphism (SNP) data: Testing phylogenetic approaches with simulated and empirical data

Datasets of hundreds or thousands of SNPs (Single Nucleotide Polymorphisms) from multiple individuals per species are increasingly used to study population structure, species delimitation and shallow phylogenetics. The principal software tool to infer species or population trees from SNP data is currently the BEAST template SNAPP which uses a Bayesian coalescent analysis. However, it is computationally extremely demanding and tolerates only small amounts of missing data. We used simulated and empirical SNPs from plants (Australian Craspedia, Asteraceae, and Pelargonium, Geraniaceae) to compare species trees produced (1) by SNAPP, (2) using SVD quartets, and (3) using Bayesian and parsimony analysis with several different approaches to summarising data from multiple samples into one set of traits per species. Our aims were to explore the impact of tree topology and missing data on the results, and to test which data summarising and analyses approaches would best approximate the results obtained from SNAPP for empirical data. SVD quartets retrieved the correct topology from simulated data, as did SNAPP except in the case of a very unbalanced phylogeny. Both methods failed to retrieve the correct topology when large amounts of data were missing. Bayesian analysis of species level summary data scoring the two alleles of each SNP as independent characters and parsimony analysis of data scoring each SNP as one character produced trees with branch length distributions closest to the true trees on which SNPs were simulated. For empirical data, Bayesian inference and Dollo parsimony analysis of data scored allele-wise produced phylogenies most congruent with the results of SNAPP. In the case of study groups divergent enough for missing data to be phylogenetically informative (because of additional mutations preventing amplification of genomic fragments or bioinformatic establishment of homology), scoring of SNP data as a presence/absence matrix irrespective of allele content might be an additional option. As this depends on sampling across species being reasonably even and a random distribution of non-informative instances of missing data, however, further exploration of this approach is needed. Properly chosen data summary approaches to inferring species trees from SNP data may represent a potential alternative to currently available individual-level coalescent analyses especially for quick data exploration and when dealing with computationally demanding or patchy datasets.

Comparative transcriptomic analysis of the evolution and development of flower size in Saltugilia (Polemoniaceae)

BackgroundFlower size varies dramatically across angiosperms, representing innovations over the course of >130 million years of evolution and contributing substantially to relationships with pollinators. However, the genetic underpinning of flower size is not well understood. Saltugilia (Polemoniaceae) provides an excellent non-model system for extending the genetic study of flower size to interspecific differences that coincide with variation in pollinators.ResultsUsing targeted gene capture methods, we infer phylogenetic relationships among all members of Saltugilia to provide a framework for investigating the genetic control of flower size differences via RNA-Seq de novo assembly. Nuclear concatenation and species tree inference methods provide congruent topologies. The inferred evolutionary trajectory of flower size is from small flowers to larger flowers. We identified 4 to 10,368 transcripts that are differentially expressed during flower development, with many unigenes associated with cell wall modification and components of the auxin and gibberellin pathways.ConclusionsSaltugilia is an excellent model for investigating covarying floral and pollinator evolution. Four candidate genes from model systems (BIG BROTHER, BIG PETAL, GASA, and LONGIFOLIA) show differential expression during development of flowers in Saltugilia, and four other genes (FLOWERING-PROMOTING FACTOR 1, PECTINESTERASE, POLYGALACTURONASE, and SUCROSE SYNTHASE) fit into hypothesized organ size pathways. Together, these gene sets provide a strong foundation for future functional studies to determine their roles in specifying interspecific differences in flower size.

Integrative taxonomy by molecular species delimitation: multi-locus data corroborate a new species of Balkan Drusinae micro-endemics

BackgroundTaxonomy offers precise species identification and delimitation and thus provides basic information for biological research, e.g. through assessment of species richness. The importance of molecular taxonomy, i.e., the identification and delimitation of taxa based on molecular markers, has increased in the past decade. Recently developed exploratory tools now allow estimating species-level diversity in multi-locus molecular datasets.ResultsHere we use molecular species delimitation tools that either quantify differences in intra- and interspecific variability of loci, or divergence times within and between species, or perform coalescent species tree inference to estimate species-level entities in molecular genetic datasets. We benchmark results from these methods against 14 morphologically readily differentiable species of a well-defined subgroup of the diverse Drusinae subfamily (Trichoptera, Limnephilidae). Using a 3798 bp (6 loci) molecular data set we aim to corroborate a geographically isolated new species by integrating comparative morphological studies and molecular taxonomy.ConclusionsOur results indicate that only multi-locus species delimitation provides taxonomically relevant information. The data further corroborate the new species Drusus zivici sp. nov. We provide differential diagnostic characters and describe the male, female and larva of this new species and discuss diversity patterns of Drusinae in the Balkans. We further discuss potential and significance of molecular species delimitation. Finally we argue that enhancing collaborative integrative taxonomy will accelerate assessment of global diversity and completion of reference libraries for applied fields, e.g., conservation and biomonitoring.

STELLS2: fast and accurate coalescent-based maximum likelihood inference of species trees from gene tree topologies

It is well known that gene trees and species trees may have different topologies. One explanation is incomplete lineage sorting, which is commonly modeled by the coalescent process. In multispecies coalescent, a gene tree topology is observed with some probability (called the gene tree probability) for a given species tree. Gene tree probability is the main tool for the program STELLS, which finds the maximum likelihood estimate of the species tree from the given gene tree topologies. However, STELLS becomes slow when data size increases. Recently, several fast species tree inference methods have been developed, which can handle large data. However, these methods often do not fully utilize the information in the gene trees. In this paper, we present an algorithm (called STELLS2) for computing the gene tree probability more efficiently than the original STELLS. The key idea of STELLS2 is taking some 'shortcuts' during the computation and computing the gene tree probability approximately. We apply the STELLS2 algorithm in the species tree inference approach in the original STELLS, which leads to a new maximum likelihood species tree inference method (also called STELLS2). Through simulation we demonstrate that the gene tree probabilities computed by STELLS2 and STELLS have strong correlation. We show that STELLS2 is almost as accurate in species tree inference as STELLS. Also STELLS2 is usually more accurate than several existing methods when there is one allele per species, although STELLS2 is slower than these methods. STELLS2 outperforms these methods significantly when there are multiple alleles per species. The program STELLS2 is available for download at: https://github.com/yufengwudcs/STELLS2. yufeng.wu@uconn.edu. Supplementary data are available at Bioinformatics online.

Using Genomic Location and Coalescent Simulation to Investigate Gene Tree Discordance in Medicago L.

Several well-documented evolutionary processes are known to cause conflict between species-level phylogenies and gene-level phylogenies. Three of the most challenging processes for species tree inference are incomplete lineage sorting, hybridization and gene duplication, which may result in unwarranted comparisons of paralogous genes. Several existing methods have dealt with these processes but none has yet been able to untangle all three at once. Here, we propose a stepwise method by which these processes can be discerned using information on genomic location coupled with coalescent simulations. In the first step, highly discordant genes within genomic blocks (putative paralogs) are identified and excluded from the data set and, in the second step, blocks of linked genes are grouped according to their hybrid history. Existing multispecies coalescent software can then be applied to recover the principal tree(s) that make up the species tree/network without violating the underlying model. The potential of the approach is evaluated on simulated data derived from a species network composed of nine species, of which one is of hybrid origin, and displaying a single-gene duplication that leads to paralogous comparisons. We apply our method to an empirical set of 12 genes from 7 species sampled in the plant genus Medicago that display phylogenetic discordance. We identify the causes of the discordance and demonstrate that the Medicago orbicularis lineage experienced an episode of ancient hybridization. Our results show promise as a new way to explore phylogenetic sequence data that can significantly improve species tree inference in presence of hybridization and undetected paralogy or other causes leading to extremely discordant gene trees. [Coalescent simulation; gene tree; genomic location; hybridization; incomplete lineage sorting; paralogy; phylogenetic incongruence; principal tree; species tree.].

Diversification in arid mountains: biogeography and cryptic diversity of Pristurus rupestris rupestris in Arabia

AbstractAimTo understand the patterns of genetic, geographical and morphological diversification in the Arabian gecko subspecies Pristurus rupestris rupestris, and to discuss the various processes that generate and shape diversity in arid mountain ranges.LocationHajar Mountains, south‐eastern Arabian Peninsula.MethodsWe sampled 466 individuals across the entire range of P. r. rupestris in the Hajar Mountains and sequenced one mitochondrial gene for all the samples, and one extra mitochondrial and four nuclear genes for a subset of 75 specimens. A total of 155 individuals were characterized morphologically. Multilocus coalescent‐based methods were used for species delimitation, for phylogenetic inference of species trees and to investigate the diversification dynamics. Multivariate statistics were used to analyse morphological data.ResultsOur molecular methods revealed 14 candidate species hidden within the subspecies P. r. rupestris. Diversification started c. 15 Ma, but most of the lineages have evolved in the last 7 Ma of the mountains’ orogeny, producing a mosaic of allopatric taxa. Secondary interchange has occurred between high and low elevation lineages, and along the mountain chain between unrelated lineages formerly separated by mountain blocks. Morphological variation between the 14 candidate species is slight, but a high elevation robust morphotype is identified.Main conclusionsOur results support the notion that mountain ranges constitute important centres of diversification in arid regions, and also act as ‘species pumps’ into surrounding areas. We also demonstrate that arid mountains may constitute important reservoirs of cryptic diversity, even in common and widespread species. This, and previous evidence, suggest that the Hajar Mountains are a biological hotspot and an important reservoir of diversity. We therefore suggest that these mountains should be a priority focal point for conservation in Arabia.

Homology-Aware Phylogenomics at Gigabase Scales.

Obstacles to inferring species trees from whole genome data sets range from algorithmic and data management challenges to the wholesale discordance in evolutionary history found in different parts of a genome. Recent work that builds trees directly from genomes by parsing them into sets of small n}{}k-mer strings holds promise to streamline and simplify these efforts, but existing approaches do not account well for gene tree discordance. We describe a “seed and extend” protocol that finds nearly exact matching sets of orthologous n}{}k-mers and extends them to construct data sets that can properly account for genomic heterogeneity. Exploiting an efficient suffix array data structure, sets of whole genomes can be parsed and converted into phylogenetic data matrices rapidly, with contiguous blocks of n}{}k-mers from the same chromosome, gene, or scaffold concatenated as needed. Phylogenetic trees constructed from highly curated rice genome data and a diverse set of six other eukaryotic whole genome, transcriptome, and organellar genome data sets recovered trees nearly identical to published phylogenomic analyses, in a small fraction of the time, and requiring many fewer parameter choices. Our method’s ability to retain local homology information was demonstrated by using it to characterize gene tree discordance across the rice genome, and by its robustness to the high rate of interchromosomal gene transfer found in several rice species.

Efficient Quartet Representations of Trees and Applications to Supertree and Summary Methods.

Quartet trees displayed by larger phylogenetic trees have long been used as inputs for species tree and supertree reconstruction. Computational constraints prevent the use of all displayed quartets in many practical problems with large numbers of taxa. We introduce the notion of an Efficient Quartet System (EQS) to represent a phylogenetic tree with a subset of the quartets displayed by the tree. We show mathematically that the set of quartets obtained from a tree via an EQS contains all of the combinatorial information of the tree itself. Using performance tests on simulated datasets, we also demonstrate that using an EQS to reduce the number of quartets in both summary method pipelines for species tree inference as well as methods for supertree inference results in only small reductions in accuracy.

Challenges in Species Tree Estimation Under the Multispecies Coalescent Model.

The multispecies coalescent (MSC) model has emerged as a powerful framework for inferring species phylogenies while accounting for ancestral polymorphism and gene tree-species tree conflict. A number of methods have been developed in the past few years to estimate the species tree under the MSC. The full likelihood methods (including maximum likelihood and Bayesian inference) average over the unknown gene trees and accommodate their uncertainties properly but involve intensive computation. The approximate or summary coalescent methods are computationally fast and are applicable to genomic datasets with thousands of loci, but do not make an efficient use of information in the multilocus data. Most of them take the two-step approach of reconstructing the gene trees for multiple loci by phylogenetic methods and then treating the estimated gene trees as observed data, without accounting for their uncertainties appropriately. In this article we review the statistical nature of the species tree estimation problem under the MSC, and explore the conceptual issues and challenges of species tree estimation by focusing mainly on simple cases of three or four closely related species. We use mathematical analysis and computer simulation to demonstrate that large differences in statistical performance may exist between the two classes of methods. We illustrate that several counterintuitive behaviors may occur with the summary methods but they are due to inefficient use of information in the data by summary methods and vanish when the data are analyzed using full-likelihood methods. These include (i) unidentifiability of parameters in the model, (ii) inconsistency in the so-called anomaly zone, (iii) singularity on the likelihood surface, and (iv) deterioration of performance upon addition of more data. We discuss the challenges and strategies of species tree inference for distantly related species when the molecular clock is violated, and highlight the need for improving the computational efficiency and model realism of the likelihood methods as well as the statistical efficiency of the summary methods.

A performance study of the impact of recombination on species tree analysis.

BackgroundThe most widely used state-of-the-art methods for reconstructing species phylogenies from genomic sequence data assume that sampled loci are identically and independently distributed. In principle, free recombination between loci and a lack of intra-locus recombination are necessary to satisfy this assumption. Few studies have quantified the practical impact of recombination on species tree inference methods, and even fewer have used genomic sequence data for this purpose. One prominent exception is the 2012 study of Lanier and Knowles. A main finding from the study was that species tree inference methods are relatively robust to intra-locus recombination, assuming free recombination between loci. The latter assumption means that the open question regarding the impact of recombination on species tree analysis is not fully resolved.ResultsThe goal of this study is to further investigate this open question. Using simulations based upon the multi-species coalescent-with-recombination model as well as empirical datasets, we compared common pipeline-based techniques for inferring species phylogenies. The simulation conditions included a range of dataset sizes and several choices for recombination rate which was either uniform across loci or incorporated recombination hotspots. We found that pipelines which explicitly utilize inferred recombination breakpoints to delineate recombination-free intervals result in greater accuracy compared to widely used alternatives that preprocess sequences based upon linkage disequilibrium decay. Furthermore, the use of a relatively simple approach for recombination breakpoint inference does not degrade the accuracy of downstream species tree inference compared to more accurate alternatives.ConclusionsOur findings clarify the impact of recombination upon current phylogenomic pipelines for species tree inference. Pipeline-based approaches which utilize inferred recombination breakpoints to densely sample loci across genomic sequences can tolerate intra-locus recombination and violations of the assumption of free recombination between loci.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3104-5) contains supplementary material, which is available to authorized users.

An analytical upper bound on the number of loci required for all splits of a species tree to appear in a set of gene trees.

BackgroundMany methods for species tree inference require data from a sufficiently large sample of genomic loci in order to produce accurate estimates. However, few studies have attempted to use analytical theory to quantify “sufficiently large”.ResultsUsing the multispecies coalescent model, we report a general analytical upper bound on the number of gene trees n required such that with probability q, each bipartition of a species tree is represented at least once in a set of n random gene trees. This bound employs a formula that is straightforward to compute, depends only on the minimum internal branch length of the species tree and the number of taxa, and applies irrespective of the species tree topology. Using simulations, we investigate numerical properties of the bound as well as its accuracy under the multispecies coalescent.ConclusionsOur results are helpful for conservatively bounding the number of gene trees required by the ASTRAL inference method, and the approach has potential to be extended to bound other properties of gene tree sets under the model.

Anchoring quartet-based phylogenetic distances and applications to species tree reconstruction.

BackgroundInferring species trees from gene trees using the coalescent-based summary methods has been the subject of much attention, yet new scalable and accurate methods are needed.ResultsWe introduce DISTIQUE, a new statistically consistent summary method for inferring species trees from gene trees under the coalescent model. We generalize our results to arbitrary phylogenetic inference problems; we show that two arbitrarily chosen leaves, called anchors, can be used to estimate relative distances between all other pairs of leaves by inferring relevant quartet trees. This results in a family of distance-based tree inference methods, with running times ranging between quadratic to quartic in the number of leaves.ConclusionsWe show in simulated studies that DISTIQUE has comparable accuracy to leading coalescent-based summary methods and reduced running times.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3098-z) contains supplementary material, which is available to authorized users.

Accounting for Uncertainty in Gene Tree Estimation: Summary-Coalescent Species Tree Inference in a Challenging Radiation of Australian Lizards.

Accurate gene tree inference is an important aspect of species tree estimation in a summary-coalescent framework. Yet, in empirical studies, inferred gene trees differ in accuracy due to stochastic variation in phylogenetic signal between targeted loci. Empiricists should, therefore, examine the consistency of species tree inference, while accounting for the observed heterogeneity in gene tree resolution of phylogenomic data sets. Here, we assess the impact of gene tree estimation error on summary-coalescent species tree inference by screening ${\sim}2000$ exonic loci based on gene tree resolution prior to phylogenetic inference. We focus on a phylogenetically challenging radiation of Australian lizards (genus Cryptoblepharus, Scincidae) and explore effects on topology and support. We identify a well-supported topology based on all loci and find that a relatively small number of high-resolution gene trees can be sufficient to converge on the same topology. Adding gene trees with decreasing resolution produced a generally consistent topology, and increased confidence for specific bipartitions that were poorly supported when using a small number of informative loci. This corroborates coalescent-based simulation studies that have highlighted the need for a large number of loci to confidently resolve challenging relationships and refutes the notion that low-resolution gene trees introduce phylogenetic noise. Further, our study also highlights the value of quantifying changes in nodal support across locus subsets of increasing size (but decreasing gene tree resolution). Such detailed analyses can reveal anomalous fluctuations in support at some nodes, suggesting the possibility of model violation. By characterizing the heterogeneity in phylogenetic signal among loci, we can account for uncertainty in gene tree estimation and assess its effect on the consistency of the species tree estimate. We suggest that the evaluation of gene tree resolution should be incorporated in the analysis of empirical phylogenomic data sets. This will ultimately increase our confidence in species tree estimation using summary-coalescent methods and enable us to exploit genomic data for phylogenetic inference. [Coalescence; concatenation; Cryptoblepharus; exon capture; gene tree; phylogenomics; species tree.].

Gene Tree Discordance Can Generate Patterns of Diminishing Convergence over Time.

Phenotypic convergence is an exciting outcome of adaptive evolution, occurring when different species find similar solutions to the same problem. Unraveling the molecular basis of convergence provides a way to link genotype to adaptive phenotypes, but can also shed light on the extent to which molecular evolution is repeatable and predictable. Many recent genome-wide studies have uncovered a striking pattern of diminishing convergence over time, ascribing this pattern to the presence of intramolecular epistatic interactions. Here, we consider gene tree discordance as an alternative cause of changes in convergence levels over time in a primate dataset. We demonstrate that gene tree discordance can produce patterns of diminishing convergence by itself, and that controlling for discordance as a cause of apparent convergence makes the pattern disappear. We also show that synonymous substitutions, where neither selection nor epistasis should be prevalent, have the same diminishing pattern of molecular convergence in primates. Finally, we demonstrate that even in situations where biological discordance is not possible, discordance due to errors in species tree inference can drive similar patterns. Though intramolecular epistasis could in principle create a pattern of declining convergence over time, our results suggest a possible alternative explanation for this widespread pattern. These results contribute to a growing appreciation not just of the presence of gene tree discordance, but of the unpredictable effects this discordance can have on analyses of molecular evolution.

Picking holes in traditional species delimitations: an integrative taxonomic reassessment of theParmotrema perforatumgroup (Parmeliaceae, Ascomycota)

Accurate species delimitation is important as species are a fundamental unit in ecological, evolutionary and conservation biology research. In lichenized fungi, species delimitation has been difficult due to a lack of taxonomically important characteristics and due to the limits of traditional, morphology-based species concepts. In this study we reassess the current taxonomy of the Parmotrema perforatum group, which recognizes six closely related species divided into three species pairs, each pair comprising one apotheciate (sexual) and one sorediate (asexual) species. Each pair is further characterized by a distinct combination of secondary metabolites. It was hypothesized that the three apotheciate species are reproductively isolated sibling species and that each sorediate species evolved once from the chemically identical apotheciate species. In this study, species boundaries were re-examined using an integrative approach incorporating morphological, chemical and molecular sequence data to delimit species boundaries. Phylogenetic trees were inferred from a seven-locus DNA sequence dataset using concatenated gene tree and coalescent-based species-tree inference methods. Furthermore, we employed a multi-species coalescent method to validate candidate species. Micromorphological measurements of conidia were found to be congruent with phylogenetic clusters. Each approach that we applied to the P. perforatum group consistently recovered four of the currently circumscribed species (P. perforatum, P. hypotropum, P. subrigidum and P. louisianae), whereas P. preperforatum and P. hypoleucinum were consistently combined and are thus interpreted as conspecific.

Species Tree Inference from Gene Splits by Unrooted STAR Methods.

The method was proposed by Liu and Yu to infer a species tree topology from unrooted topological gene trees. While its statistical consistency under the multispecies coalescent model was established only for a four-taxon tree, simulations demonstrated its good performance on gene trees inferred from sequences for many taxa. Here, we prove the statistical consistency of the method for an arbitrarily large species tree. Our approach connects to a generalization of the STAR method of Liu, Pearl, and Edwards, and a previous theoretical analysis of it. We further show utilizes only the distribution of splits in the gene trees, and not their individual topologies. Finally, we discuss how multiple samples per taxon per gene should be handled for statistical consistency.

Hypothesis tests for phylogenetic quartets, with applications to coalescent-based species tree inference

Numerous statistical methods have been developed to estimate evolutionary relationships among a collection of present-day species, typically represented by a phylogenetic tree, using the information contained in the DNA sequences sampled from representatives of each species. In the current era of high-throughput genome sequencing, the models underlying such methods have become increasingly sophisticated, and the resulting computations are often prohibitive. Here we consider the problem of rigorously testing the phylogenetic relationships among collections of four species under the multispecies coalescent model that accommodates both multi-locus datasets and SNP data. Our test employs a new statistic — the summed absolute differences between certain columns in flattened phylogenetic matrices — as well as a previously used statistic that measures the distance of a flattened matrix from the space of rank-10 matrices. We derive distributional results for both statistics and study the performance of the corresponding hypothesis tests using both simulated and empirical data. We discuss how these tests may be used to improve inference of phylogenetic relationships for larger samples of species under the multispecies coalescent model, a problem that has until recently been computationally intractable.

Consensus properties and their large-scale applications for the gene duplication problem.

Solving the gene duplication problem is a classical approach for species tree inference from gene trees that are confounded by gene duplications. This problem takes a collection of gene trees and seeks a species tree that implies the minimum number of gene duplications. Wilkinson etal. posed the conjecture that the gene duplication problem satisfies the desirable Pareto property for clusters. That is, for every instance of the problem, all clusters that are commonly present in the input gene trees of this instance, called strict consensus, will also be found in every solution to this instance. We prove that this conjecture does not generally hold. Despite this negative result we show that the gene duplication problem satisfies a weaker version of the Pareto property where the strict consensus is found in at least one solution (rather than all solutions). This weaker property contributes to our design of an efficient scalable algorithm for the gene duplication problem. We demonstrate the performance of our algorithm in analyzing large-scale empirical datasets. Finally, we utilize the algorithm to evaluate the accuracy of standard heuristics for the gene duplication problem using simulated datasets.

Bayesian Inference of Reticulate Phylogenies under the Multispecies Network Coalescent.

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

Consistency and inconsistency of consensus methods for inferring species trees from gene trees in the presence of ancestral population structure

In the last few years, several statistically consistent consensus methods for species tree inference have been devised that are robust to the gene tree discordance caused by incomplete lineage sorting in unstructured ancestral populations. One source of gene tree discordance that has only recently been identified as a potential obstacle for phylogenetic inference is ancestral population structure. In this article, we describe a general model of ancestral population structure, and by relying on a single carefully constructed example scenario, we show that the consensus methods Democratic Vote, STEAC, STAR, R∗ Consensus, Rooted Triple Consensus, Minimize Deep Coalescences, and Majority-Rule Consensus are statistically inconsistent under the model. We find that among the consensus methods evaluated, the only method that is statistically consistent in the presence of ancestral population structure is GLASS/Maximum Tree. We use simulations to evaluate the behavior of the various consensus methods in a model with ancestral population structure, showing that as the number of gene trees increases, estimates on the basis of GLASS/Maximum Tree approach the true species tree topology irrespective of the level of population structure, whereas estimates based on the remaining methods only approach the true species tree topology if the level of structure is low. However, through simulations using species trees both with and without ancestral population structure, we show that GLASS/Maximum Tree performs unusually poorly on gene trees inferred from alignments with little information. This practical limitation of GLASS/Maximum Tree together with the inconsistency of other methods prompts the need for both further testing of additional existing methods and development of novel methods under conditions that incorporate ancestral population structure.