Multispecies Coalescent Research Articles

Incorporating the speciation process into species delimitation.

The "multispecies" coalescent (MSC) model that underlies many genomic species-delimitation approaches is problematic because it does not distinguish between genetic structure associated with species versus that of populations within species. Consequently, as both the genomic and spatial resolution of data increases, a proliferation of artifactual species results as within-species population lineages, detected due to restrictions in gene flow, are identified as distinct species. The toll of this extends beyond systematic studies, getting magnified across the many disciplines that rely upon an accurate framework of identified species. Here we present the first of a new class of approaches that addresses this issue by incorporating an extended speciation process for species delimitation. We model the formation of population lineages and their subsequent development into independent species as separate processes and provide for a way to incorporate current understanding of the species boundaries in the system through specification of species identities of a subset of population lineages. As a result, species boundaries and within-species lineages boundaries can be discriminated across the entire system, and species identities can be assigned to the remaining lineages of unknown affinities with quantified probabilities. In addition to the identification of species units in nature, the primary goal of species delimitation, the incorporation of a speciation model also allows us insights into the links between population and species-level processes. By explicitly accounting for restrictions in gene flow not only between, but also within, species, we also address the limits of genetic data for delimiting species. Specifically, while genetic data alone is not sufficient for accurate delimitation, when considered in conjunction with other information we are able to not only learn about species boundaries, but also about the tempo of the speciation process itself.

Statistical inconsistency of the unrooted minimize deep coalescence criterion.

Species trees, which describe the evolutionary relationships between species, are often inferred from gene trees, which describe the ancestral relationships between sequences sampled at different loci from the species of interest. A common approach to inferring species trees from gene trees is motivated by supposing that gene tree variation is due to incomplete lineage sorting, also known as deep coalescence. One of the earliest methods motivated by deep coalescence is to find the species tree that minimizes the number of deep coalescent events needed to explain discrepancies between the species tree and input gene trees. This minimize deep coalescence (MDC) criterion can be applied in both rooted and unrooted settings. where either rooted or unrooted gene trees can be used to infer a rooted species tree. Previous work has shown that MDC is statistically inconsistent in the rooted setting, meaning that under a probabilistic model for deep coalescence, the multispecies coalescent, for some species trees, increasing the number of input gene trees does not make the method more likely to return a correct species tree. Here, we obtain analogous results in the unrooted setting, showing conditions leading to inconsistency of the MDC criterion using the multispecies coalescent model with unrooted gene trees for four taxa and five taxa.

Heuristics for unrooted, unranked, and ranked anomaly zones under birth-death models

Species trees that can generate a nonmatching gene tree topology that is more probable than the topology matching the species tree are said to be in an anomaly zone. We introduce some heuristic approaches to infer whether species trees are in anomaly zones when it is difficult or impossible to compute the entire distribution of gene tree topologies. Here, probabilities of unrooted, unranked, and ranked gene tree topologies under the multispecies coalescent are used. A ranked tree can be viewed as an unranked tree with a temporal ordering of its internal nodes. Overall, considering probabilities of unrooted or unranked gene tree topologies within one nearest neighbor interchange from the species tree topology is a reasonable heuristic to infer the existence of anomalous unrooted or unranked gene trees, respectively. We investigated a test proposed by Linkem et al. (2016) which classifies a species tree as being in an unranked anomaly zone if there is a subset of four taxa in an unranked anomaly zone. We find this test to have high true positive rates, but it can also have high false positive rates. For ranked trees, because at least one of the most probable ranked gene tree topologies must have the same unranked topology as the species tree, we propose to use only those ranked gene trees that have topologies that match the unranked species tree topology. We find that the probability that the species tree is in unrooted and unranked anomaly zones tends to increase with the speciation rate, and the probability of all three types of anomaly zones increases rapidly with the number of taxa. We find that probabilities that species trees are in an anomaly zone can be quite high for moderately high speciation rates.

Computing the probability of gene trees concordant with the species tree in the multispecies coalescent

The multispecies coalescent process models the genealogical relationships of genes sampled from several species, enabling useful predictions about phenomena such as the discordance between a gene tree and the species phylogeny due to incomplete lineage sorting. Conversely, knowledge of large collections of gene trees can inform us about several aspects of the species phylogeny, such as its topology and ancestral population sizes. A fundamental open problem in this context is how to efficiently compute the probability of a gene tree topology, given the species phylogeny. Although a number of algorithms for this task have been proposed, they either produce approximate results, or, when they are exact, they do not scale to large data sets. In this paper, we present some progress towards exact and efficient computation of the probability of a gene tree topology. We provide a new algorithm that, given a species tree and the number of genes sampled for each species, calculates the probability that the gene tree topology will be concordant with the species tree. Moreover, we provide an algorithm that computes the probability of any specific gene tree topology concordant with the species tree. Both algorithms run in polynomial time and have been implemented in Python. Experiments show that they are able to analyze data sets where thousands of genes are sampled in a matter of minutes to hours.

Assessing the fit of the multi-species network coalescent to multi-locus data.

With growing genome-wide molecular datasets from next-generation sequencing, phylogenetic networks can be estimated using a variety of approaches. These phylogenetic networks include events like hybridization, gene flow or horizontal gene transfer explicitly. However, the most accurate network inference methods are computationally heavy. Methods that scale to larger datasets do not calculate a full likelihood, such that traditional likelihood-based tools for model selection are not applicable to decide how many past hybridization events best fit the data. We propose here a goodness-of-fit test to quantify the fit between data observed from genome-wide multi-locus data, and patterns expected under the multi-species coalescent model on a candidate phylogenetic network. We identified weaknesses in the previously proposed TICR test, and proposed corrections. The performance of our new test was validated by simulations on real-world phylogenetic networks. Our test provides one of the first rigorous tools for model selection, to select the adequate network complexity for the data at hand. The test can also work for identifying poorly inferred areas on a network. Software for the goodness-of-fit test is available as a Julia package at https://github.com/cecileane/QuartetNetworkGoodnessFit.jl. Supplementary data are available at Bioinformatics online.

The Multilocus Multispecies Coalescent: A Flexible New Model of Gene Family Evolution.

Incomplete lineage sorting (ILS), the interaction between coalescence and speciation, can generate incongruence between gene trees and species trees, as can gene duplication (D), transfer (T), and loss (L). These processes are usually modeled independently, but in reality, ILS can affect gene copy number polymorphism, that is, interfere with DTL. This has been previously recognized, but not treated in a satisfactory way, mainly because DTL events are naturally modeled forward-in-time, while ILS is naturally modeled backward-in-time with the coalescent. Here, we consider the joint action of ILS and DTL on the gene tree/species tree problem in all its complexity. In particular, we show that the interaction between ILS and duplications/transfers (without losses) can result in patterns usually interpreted as resulting from gene loss, and that the realized rate of D, T, and L becomes nonhomogeneous in time when ILS is taken into account. We introduce algorithmic solutions to these problems. Our new model, the multilocus multispecies coalescent, which also accounts for any level of linkage between loci, generalizes the multispecies coalescent (MSC) model and offers a versatile, powerful framework for proper simulation, and inference of gene family evolution. [Gene duplication; gene loss; horizontal gene transfer; incomplete lineage sorting; multispecies coalescent; hemiplasy; recombination.].

MSCquartets 1.0: quartet methods for species trees and networks under the multispecies coalescent model in R.

MSCquartets is an R package for species tree hypothesis testing, inference of species trees and inference of species networks under the Multispecies Coalescent model of incomplete lineage sorting and its network analog. Input for these analyses are collections of metric or topological locus trees which are then summarized by the quartets displayed on them. Results of hypothesis tests at user-supplied levels are displayed in a simplex plot by color-coded points. The package implements the QDC and WQDC algorithms for topological and metric species tree inference, and the NANUQ algorithm for level-1 topological species network inference, all of which give statistically consistent estimators under the model. MSCquartets is available through the Comprehensive R Archive Network: https://CRAN.R-project.org/package=MSCquartets.

Species delimitation in the cyanolichen genus Rostania

BackgroundIn this study, we investigate species limits in the cyanobacterial lichen genus Rostania (Collemataceae, Peltigerales, Lecanoromycetes). Four molecular markers (mtSSU rDNA, β-tubulin, MCM7, RPB2) were sequenced and analysed with two coalescent-based species delimitation methods: the Generalized Mixed Yule Coalescent model (GMYC) and a Bayesian species delimitation method (BPP) using a multispecies coalescence model (MSC), the latter with or without an a priori defined guide tree.ResultsSpecies delimitation analyses indicate the presence of eight strongly supported candidate species. Conclusive correlation between morphological/ecological characters and genetic delimitation could be found for six of these. Of the two additional candidate species, one is represented by a single sterile specimen and the other currently lacks morphological or ecological supporting evidence.ConclusionsWe conclude that Rostania includes a minimum of six species: R. ceranisca, R. multipunctata, R. occultata 1, R. occultata 2, R. occultata 3, and R. occultata 4,5,6. Three distinct Nostoc morphotypes occur in Rostania, and there is substantial correlation between these morphotypes and Rostania thallus morphology.

Defining relictual biodiversity: Conservation units in speckled dace (Leuciscidae: Rhinichthys osculus) of the Greater Death Valley ecosystem.

The tips in the tree of life serve as foci for conservation and management, yet clear delimitations are masked by inherent variance at the species–population interface. Analyses using thousands of nuclear loci can potentially sort inconsistencies, yet standard categories applied to this parsing are themselves potentially conflicting and/or subjective [e.g., DPS (distinct population segments); DUs (Diagnosable Units‐Canada); MUs (management units); SSP (subspecies); ESUs (Evolutionarily Significant Units); and UIEUs (uniquely identified evolutionary units)]. One potential solution for consistent categorization is to create a comparative framework by accumulating statistical results from independent studies and evaluating congruence among data sets. Our study illustrates this approach in speckled dace (Leuciscidae: Rhinichthys osculus) endemic to two basins (Owens and Amargosa) in the Death Valley ecosystem. These fish persist in the Mojave Desert as isolated Plio‐Pleistocene relicts and are of conservation concern, but lack formal taxonomic descriptions/designations. Double digest RAD (ddRAD) methods identified 14,355 SNP loci across 10 populations (N = 140). Species delimitation analyses [multispecies coalescent (MSC) and unsupervised machine learning (UML)] delineated four putative ESUs. F ST outlier loci (N = 106) were juxtaposed to uncover the potential for localized adaptations. We detected one hybrid population that resulted from upstream reconnection of habitat following contemporary pluvial periods, whereas remaining populations represent relics of ancient tectonism within geographically isolated springs and groundwater‐fed streams. Our study offers three salient conclusions: a blueprint for a multifaceted delimitation of conservation units; a proposed mechanism by which criteria for intraspecific biodiversity can be potentially standardized; and a strong argument for the proactive management of critically endangered Death Valley ecosystem fishes.

The genomic view of diversification.

The process of species diversification is traditionally summarized by a single tree, the species tree, whose reconstruction from molecular data is hindered by frequent conflicts between gene genealogies. Here, we argue that instead of seeing these conflicts as nuisances, we can exploit them to inform the diversification process itself. We adopt a gene-based view of diversification to model the ubiquitous presence of gene flow between diverging lineages, one of the most important processes explaining disagreements among gene trees. We propose a new framework for modelling the joint evolution of gene and species lineages relaxing the hierarchy between the species tree and gene trees inherent to the standard view, as embodied in a popular model known as the multispecies coalescent (MSC). We implement this framework in two alternative models called the gene-based diversification models (GBD): (a) GBD-forward following all evolving genomes through time and (b) GBD-backward based on coalescent theory. They feature four parameters tuning colonization, gene flow, genetic drift and genetic differentiation. We propose an inference method based on differences between gene trees. Applied to two empirical data sets prone to gene flow, we find better support for the GBD-backward model than for the MSC model. Along with the increasing awareness of the extent of gene flow, this work shows the importance of considering the richer signal contained in genomic histories, rather than in the mere species tree, to better apprehend the complex evolutionary history of species.

UglyTrees: a browser-based multispecies coalescent tree visualizer.

SummaryVisualization is a vital task in phylogenetics and yet there is a deficit in programs which visualize the multispecies coalescent (MSC) model. UglyTrees (UT) is an easy-to-use program for visualizing multiple gene trees embedded within a single species trees. The mapping between gene and species nodes is automatically detected allowing for ready access to the program. UT can scrape the contents of a website for MSC analyses, enabling the sharing of interactive MSC figures through optional parameters in the URL. If a posterior distribution is uploaded, the transitions between MSC states are animated allowing the visual tracking of trees throughout the sequence.Availability and implementationUT runs in all major web browsers including mobile devices, and is hosted at www.uglytrees.nz. The MIT-licensed code is available at https://github.com/UglyTrees/uglytrees.github.io.

Cryptic Patterns of Speciation in Cryptic Primates: Microendemic Mouse Lemurs and the Multispecies Coalescent.

Mouse lemurs (Microcebus) are a radiation of morphologically cryptic primates distributed throughout Madagascar for which the number of recognized species has exploded in the past two decades. This taxonomic revision has prompted understandable concern that there has been substantial oversplitting in the mouse lemur clade. Here, we investigate mouse lemur diversity in a region in northeastern Madagascar with high levels of microendemism and predicted habitat loss. We analyzed RADseq data with multispecies coalescent (MSC) species delimitation methods for two pairs of sister lineages that include three named species and an undescribed lineage previously identified to have divergent mtDNA. Marked differences in effective population sizes, levels of gene flow, patterns of isolation-by-distance, and species delimitation results were found among the two pairs of lineages. Whereas all tests support the recognition of the presently undescribed lineage as a separate species, the species-level distinction of two previously described species, M. mittermeieri and M. lehilahytsara is not supported-a result that is particularly striking when using the genealogical discordance index (gdi). Nonsister lineages occur sympatrically in two of the localities sampled for this study, despite an estimated divergence time of less than 1 Ma. This suggests rapid evolution of reproductive isolation in the focal lineages and in the mouse lemur clade generally. The divergence time estimates reported here are based on the MSC calibrated with pedigree-based mutation rates and are considerably more recent than previously published fossil-calibrated relaxed-clock estimates. We discuss the possible explanations for this discrepancy, noting that there are theoretical justifications for preferring the MSC estimates in this case. [Cryptic species; effective population size; microendemism; multispecies coalescent; speciation; species delimitation.].

Bayesian Inference of Species Trees using Diffusion Models.

We describe a new and computationally efficient Bayesian methodology for inferring species trees and demographics from unlinked binary markers. Likelihood calculations are carried out using diffusion models of allele frequency dynamics combined with novel numerical algorithms. The diffusion approach allows for analysis of data sets containing hundreds or thousands of individuals. The method, which we call Snapper, has been implemented as part of the BEAST2 package. We conducted simulation experiments to assess numerical error, computational requirements, and accuracy recovering known model parameters. A reanalysis of soybean SNP data demonstrates that the models implemented in Snapp and Snapper can be difficult to distinguish in practice, a characteristic which we tested with further simulations. We demonstrate the scale of analysis possible using a SNP data set sampled from 399 fresh water turtles in 41 populations. [Bayesian inference; diffusion models; multi-species coalescent; SNP data; species trees; spectral methods.].

Defining Species When There is Gene Flow.

Whatever one's definition of species, it is generally expected that individuals of the same species should be genetically more similar to each other than they are to individuals of another species. Here, we show that in the presence of cross-species gene flow, this expectation may be incorrect. We use the multispecies coalescent model with continuous-time migration or episodic introgression to study the impact of gene flow on genetic differences within and between species and highlight a surprising but plausible scenario in which different population sizes and asymmetrical migration rates cause a genetic sequence to be on average more closely related to a sequence from another species than to a sequence from the same species. Our results highlight the extraordinary impact that even a small amount of gene flow may have on the genetic history of the species. We suggest that contrasting long-term migration rate and short-term hybridization rate, both of which can be estimated using genetic data, may be a powerful approach to detecting the presence of reproductive barriers and to define species boundaries.[Gene flow; introgression; migration; multispecies coalescent; species concept; species delimitation.].

Addressing incomplete lineage sorting and paralogy in the inference of uncertain salmonid phylogenetic relationships.

Recent and continued progress in the scale and sophistication of phylogenetic research has yielded substantial advances in knowledge of the tree of life; however, segments of that tree remain unresolved and continue to produce contradicting or unstable results. These poorly resolved relationships may be the product of methodological shortcomings or of an evolutionary history that did not generate the signal traits needed for its eventual reconstruction. Relationships within the euteleost fish family Salmonidae have proven challenging to resolve in molecular phylogenetics studies in part due to ancestral autopolyploidy contributing to conflicting gene trees. We examine a sequence capture dataset from salmonids and use alternative strategies to accommodate the effects of gene tree conflict based on aspects of salmonid genome history and the multispecies coalescent. We investigate in detail three uncertain relationships: (1) subfamily branching, (2) monophyly of Coregonus and (3) placement of Parahucho. Coregoninae and Thymallinae are resolved as sister taxa, although conflicting topologies are found across analytical strategies. We find inconsistent and generally low support for the monophyly of Coregonus, including in results of analyses with the most extensive dataset and complex model. The most consistent placement of Parahucho is as sister lineage of Salmo.

PRANC: ML species tree estimation from the ranked gene trees under coalescence.

PRANC computes the Probabilities of RANked gene tree topologies under the multispecies coalescent. A ranked gene tree is a gene tree accounting for the temporal ordering of internal nodes. PRANC can also estimate the maximum likelihood (ML) species tree from a sample of ranked or unranked gene tree topologies. It estimates the ML tree with estimated branch lengths in coalescent units. PRANC is written in C++ and freely available at github.com/anastasiiakim/PRANC. Supplementary data are available at Bioinformatics online.

Inference of population admixture network from local gene genealogies: a coalescent-based maximum likelihood approach.

MotivationPopulation admixture is an important subject in population genetics. Inferring population demographic history with admixture under the so-called admixture network model from population genetic data is an established problem in genetics. Existing admixture network inference approaches work with single genetic polymorphisms. While these methods are usually very fast, they do not fully utilize the information [e.g. linkage disequilibrium (LD)] contained in population genetic data.ResultsIn this article, we develop a new admixture network inference method called GTmix. Different from existing methods, GTmix works with local gene genealogies that can be inferred from population haplotypes. Local gene genealogies represent the evolutionary history of sampled haplotypes and contain the LD information. GTmix performs coalescent-based maximum likelihood inference of admixture networks with inferred local genealogies based on the well-known multispecies coalescent (MSC) model. GTmix utilizes various techniques to speed up the likelihood computation on the MSC model and the optimal network search. Our simulations show that GTmix can infer more accurate admixture networks with much smaller data than existing methods, even when these existing methods are given much larger data. GTmix is reasonably efficient and can analyze population genetic datasets of current interests.Availability and implementationThe program GTmix is available for download at: https://github.com/yufengwudcs/GTmix.Supplementary information Supplementary data are available at Bioinformatics online.

Molecular species delimitation in the primitively segmented spider genus Heptathela endemic to Japanese islands

Determining species boundaries forms an important foundation for biological research. However, the results of molecular species delimitation can vary with the data sets and methods that are used. Here we use a two-step approach to delimit species in the genus Heptathela, a group of primitively segmented trapdoor spiders that are endemic to Japanese islands. Morphological evidence suggests the existence of 19 species in the genus. We tested this initial species hypothesis by using six molecular species-delimitation methods to analyse 180 mitochondrial COI sequences of Heptathela sampled from across the known range of the genus. We then conducted a set of more focused analyses by sampling additional genetic markers from the subset of taxa that were inconsistently delimited by the single-locus analyses of mitochondrial DNA. Multilocus species delimitation was performed using two Bayesian approaches based on the multispecies coalescent. Our approach identified 20 putative species among the 180 sampled individuals of Heptathela. We suggest that our two-step approach provides an efficient strategy for delimiting species while minimizing costs and computational time.

Consistency of SVDQuartets and Maximum Likelihood for Coalescent-Based Species Tree Estimation.

Numerous methods for inferring species-level phylogenies under the coalescent model have been proposed within the last 20 years, and debates continue about the relative strengths and weaknesses of these methods. One desirable property of a phylogenetic estimator is that of statistical consistency, which means intuitively that as more data are collected, the probability that the estimated tree has the same topology as the true tree goes to 1. To date, consistency results for species tree inference under the multispecies coalescent (MSC) have been derived only for summary statistics methods, such as ASTRAL and MP-EST. These methods have been found to be consistent given true gene trees but may be inconsistent when gene trees are estimated from data for loci of finite length. Here, we consider the question of statistical consistency for four taxa for SVDQuartets for general data types, as well as for the maximum likelihood (ML) method in the case in which the data are a collection of sites generated under the MSC model such that the sites are conditionally independent given the species tree (we call these data coalescent independent sites [CIS] data). We show that SVDQuartets is statistically consistent for all data types (i.e., for both CIS data and for multilocus data), and we derive its rate of convergence. We additionally show that ML is consistent for CIS data under the JC69 model and discuss why a proof for the more general multilocus case is difficult. Finally, we compare the performance of ML and SDVQuartets using simulation for both data types. [Consistency; gene tree; maximum likelihood; multilocus data; hylogenetic inference; species tree; SVDQuartets.].

Detecting destabilizing species in the phylogenetic backbone of Potentilla (Rosaceae) using low-copy nuclear markers.

The genus Potentilla (Rosaceae) has been subjected to several phylogenetic studies, but resolving its evolutionary history has proven challenging. Previous analyses recovered six, informally named, groups: the Argentea, Ivesioid, Fragarioides, Reptans, Alba and Anserina clades, but the relationships among some of these clades differ between data sets. The Reptans clade, which includes the type species of Potentilla, has been noticed to shift position between plastid and nuclear ribosomal data sets. We studied this incongruence by analysing four low-copy nuclear markers, in addition to chloroplast and nuclear ribosomal data, with a set of Bayesian phylogenetic and Multispecies Coalescent (MSC) analyses. A selective taxon removal strategy demonstrated that the included representatives from the Fragarioides clade, P. dickinsii and P. fragarioides, were the main sources of the instability seen in the trees. The Fragarioides species showed different relationships in each gene tree, and were only supported as a monophyletic group in a single marker when the Reptans clade was excluded from the analysis. The incongruences could not be explained by allopolyploidy, but rather by homoploid hybridization, incomplete lineage sorting or taxon sampling effects. When P. dickinsii and P. fragarioides were removed from the data set, a fully resolved, supported backbone phylogeny of Potentilla was obtained in the MSC analysis. Additionally, indications of autopolyploid origins of the Reptans and Ivesioid clades were discovered in the low-copy gene trees.