Multispecies Network Coalescent Research Articles

Complex Patterns of Diversification in the Gray Zone of Speciation: Model-Based Approaches Applied to Patagonian Liolaemid Lizards (Squamata: Liolaemus kingii clade).

In this study we detangled the evolutionary history of the Patagonian lizard clade Liolaemus kingii, coupling dense geographic sampling and novel computational analytical approaches. We analyzed nuclear and mitochondrial data (restriction site-associated DNA sequencing and cytochrome b) to hypothesize and evaluate species limits, phylogenetic relationships, and demographic histories. We complemented these analyses with posterior predictive simulations to assess the fit of the genomic data to the multispecies coalescent model. We also employed a novel approach to time-calibrate a phylogenetic network. Our results show several instances of mito-nuclear discordance and consistent support for a reticulated history, supporting the view that the complex evolutionary history of the kingii clade is characterized by extensive gene flow and rapid diversification events. We discuss our findings in the contexts of the "gray zone" of speciation, phylogeographic patterns in the Patagonian region, and taxonomic outcomes. [Model adequacy; multispecies coalescent; multispecies network coalescent; phylogenomics; species delimitation.].

Hybridization and Transgressive Evolution Generate Diversity in an Adaptive Radiation of Anolis Lizards.

Interspecific hybridization may act as a major force contributing to the evolution of biodiversity. Although generally thought to reduce or constrain divergence between 2 species, hybridization can, paradoxically, promote divergence by increasing genetic variation or providing novel combinations of alleles that selection can act upon to move lineages toward new adaptive peaks. Hybridization may, then, play a key role in adaptive radiation by allowing lineages to diversify into new ecological space. Here, we test for signatures of historical hybridization in the Anolis lizards of Puerto Rico and evaluate 2 hypotheses for the role of hybridization in facilitating adaptive radiation-the hybrid swarm origins hypothesis and the syngameon hypothesis. Using whole genome sequences from all 10 species of Puerto Rican anoles, we calculated D and f-statistics (from ABBA-BABA tests) to test for introgression across the radiation and employed multispecies network coalescent methods to reconstruct phylogenetic networks that allow for hybridization. We then analyzed morphological data for these species to test for patterns consistent with transgressive evolution, a phenomenon in which the trait of a hybrid lineage is found outside of the range of its 2 parents. Our analyses uncovered strong evidence for introgression at multiple stages of the radiation, including support for an ancient hybrid origin of a clade comprising half of the extant Puerto Rican anole species. Moreover, we detected significant signals of transgressive evolution for 2 ecologically important traits, head length and toepad width, the latter of which has been described as a key innovation in Anolis. [Adaptive radiation; introgression; multispecies network coalescent; phenotypic evolution; phylogenetic network; reticulation; syngameon; transgressive segregation.].

Interspecific Gene Flow and Mitochondrial Genome Capture during the Radiation of Jamaican Anolis Lizards (Squamata; Iguanidae).

Gene flow and reticulation are increasingly recognized as important processes in the diversification of many taxonomic groups. With the increasing ease of collecting genomic data and the development of multispecies coalescent network approaches, such reticulations can be accounted for when inferring phylogeny and diversification. Caribbean Anolis lizards are a classic example of an adaptive radiation in which species have independently radiated on the islands of the Greater Antilles into the same ecomorph classes. Within the Jamaican radiation at least one species, Anolis opalinus, has been documented to be polyphyletic in its mitochondrial DNA, which could be the result of an ancient reticulation event or incomplete lineage sorting (ILS). Here, we generate mtDNA and genotyping-by-sequencing (GBS) data and implement gene tree, species tree, and multispecies coalescent network methods to infer the diversification of this group. Our mtDNA gene tree recovers the same relationships previously inferred for this group, which is strikingly different from the species tree inferred from our GBS data. Posterior predictive simulations suggest that our genomic data violate commonly adopted assumptions of the multispecies coalescent model (MSCM), so we use network approaches to infer phylogenetic relationships. The inferred network topology contains a reticulation event but does not explain the mtDNA polyphyly observed in this group; however, coalescent simulations suggest that the observed mtDNA topology is likely the result of past introgression. How common a signature of gene flow and reticulation is across the radiation of Anolis is unknown; however, the reticulation events that we demonstrate here may have allowed for adaptive evolution, as has been suggested in other, more recent, adaptive radiations. [Adaptive radiation; hybridization; introgression; multispecies network coalescent; posterior predictive simulation.].

Maximum Parsimony Inference of Phylogenetic Networks in the Presence of Polyploid Complexes.

Phylogenetic networks provide a powerful framework for modeling and analyzing reticulate evolutionary histories. While polyploidy has been shown to be prevalent not only in plants but also in other groups of eukaryotic species, most work done thus far on phylogenetic network inference assumes diploid hybridization. These inference methods have been applied, with varying degrees of success, to data sets with polyploid species, even though polyploidy violates the mathematical assumptions underlying these methods. Statistical methods were developed recently for handling specific types of polyploids and so were parsimony methods that could handle polyploidy more generally yet while excluding processes such as incomplete lineage sorting. In this article, we introduce a new method for inferring most parsimonious phylogenetic networks on data that include polyploid species. Taking gene tree topologies as input, the method seeks a phylogenetic network that minimizes deep coalescences while accounting for polyploidy. We demonstrate the performance of the method on both simulated and biological data. The inference method as well as a method for evaluating evolutionary hypotheses in the form of phylogenetic networks are implemented and publicly available in the PhyloNet software package. [Incomplete lineage sorting; minimizing deep coalescences; multilabeled trees; multispecies network coalescent; phylogenetic networks; polyploidy.]

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.

Implementing Large Genomic Single Nucleotide Polymorphism Data Sets in Phylogenetic Network Reconstructions: A Case Study of Particularly Rapid Radiations of Cichlid Fish.

The Midas cichlids of the Amphilophus citrinellus spp. species complex from Nicaragua (13 species) are an extraordinary example of adaptive and rapid radiation ($<$24,000 years old). These cichlids are a very challenging group to infer its evolutionary history in phylogenetic analyses, due to the apparent prevalence of incomplete lineage sorting (ILS), as well as past and current gene flow. Assuming solely a vertical transfer of genetic material from an ancestral lineage to new lineages is not appropriate in many cases of genes transferred horizontally in nature. Recently developed methods to infer phylogenetic networks under such circumstances might be able to circumvent these problems. These models accommodate not just ILS, but also gene flow, under the multispecies network coalescent (MSNC) model, processes that are at work in young, hybridizing, and/or rapidly diversifying lineages. There are currently only a few programs available that implement MSNC for estimating phylogenetic networks. Here, we present a novel way to incorporate single nucleotide polymorphism (SNP) data into the currently available PhyloNetworks program. Based on simulations, we demonstrate that SNPs can provide enough power to recover the true phylogenetic network. We also show that it can accurately infer the true network more often than other similar SNP-based programs (PhyloNet and HyDe). Moreover, our approach results in a faster algorithm compared to the original pipeline in PhyloNetworks, without losing power. We also applied our new approach to infer the phylogenetic network of Midas cichlid radiation. We implemented the most comprehensive genomic data set to date (RADseq data set of 679 individuals and $>$37K SNPs from 19 ingroup lineages) and present estimated phylogenetic networks for this extremely young and fast-evolving radiation of cichlid fish. We demonstrate that the MSNC is more appropriate than the multispecies coalescent alone for the analysis of this rapid radiation. [Genomics; multispecies network coalescent; phylogenetic networks; phylogenomics; RADseq; SNPs.].

The Timing and Direction of Introgression Under the Multispecies Network Coalescent.

Introgression is a pervasive biological process, and many statistical methods have been developed to infer its presence from genomic data. However, many of the consequences and genomic signatures of introgression remain unexplored from a methodological standpoint. Here, we develop a model for the timing and direction of introgression based on the multispecies network coalescent, and from it suggest new approaches for testing introgression hypotheses. We suggest two new statistics, D1 and D2, which can be used in conjunction with other information to test hypotheses relating to the timing and direction of introgression, respectively. D1 may find use in evaluating cases of homoploid hybrid speciation (HHS), while D2 provides a four-taxon test for polarizing introgression. Although analytical expectations for our statistics require a number of assumptions to be met, we show how simulations can be used to test hypotheses about introgression when these assumptions are violated. We apply the D1 statistic to genomic data from the wild yeast Saccharomyces paradoxus-a proposed example of HHS-demonstrating its use as a test of this model. These methods provide new and powerful ways to address questions relating to the timing and direction of introgression.

Inferring Phylogenetic Networks Using PhyloNet

PhyloNet was released in 2008 as a software package for representing and analyzing phylogenetic networks. At the time of its release, the main functionalities in PhyloNet consisted of measures for comparing network topologies and a single heuristic for reconciling gene trees with a species tree. Since then, PhyloNet has grown significantly. The software package now includes a wide array of methods for inferring phylogenetic networks from data sets of unlinked loci while accounting for both reticulation (e.g., hybridization) and incomplete lineage sorting. In particular, PhyloNet now allows for maximum parsimony, maximum likelihood, and Bayesian inference of phylogenetic networks from gene tree estimates. Furthermore, Bayesian inference directly from sequence data (sequence alignments or biallelic markers) is implemented. Maximum parsimony is based on an extension of the "minimizing deep coalescences" criterion to phylogenetic networks, whereas maximum likelihood and Bayesian inference are based on the multispecies network coalescent. All methods allow for multiple individuals per species. As computing the likelihood of a phylogenetic network is computationally hard, PhyloNet allows for evaluation and inference of networks using a pseudolikelihood measure. PhyloNet summarizes the results of the various analyzes and generates phylogenetic networks in the extended Newick format that is readily viewable by existing visualization software.

Coestimating Reticulate Phylogenies and Gene Trees from Multilocus Sequence Data.

The multispecies network coalescent (MSNC) is a stochastic process that captures how gene trees grow within the branches of a phylogenetic network. Coupling the MSNC with a stochastic mutational process that operates along the branches of the gene trees gives rise to a generative model of how multiple loci from within and across species evolve in the presence of both incomplete lineage sorting (ILS) and reticulation (e.g., hybridization). We report on a Bayesian method for sampling the parameters of this generative model, including the species phylogeny, gene trees, divergence times, and population sizes, from DNA sequences of multiple independent loci. We demonstrate the utility of our method by analyzing simulated data and reanalyzing an empirical data set. Our results demonstrate the significance of not only coestimating species phylogenies and gene trees, but also accounting for reticulation and ILS simultaneously. In particular, we show that when gene flow occurs, our method accurately estimates the evolutionary histories, coalescence times, and divergence times. Tree inference methods, on the other hand, underestimate divergence times and overestimate coalescence times when the evolutionary history is reticulate. While the MSNC corresponds to an abstract model of "intermixture," we study the performance of the model and method on simulated data generated under a gene flow model. We show that the method accurately infers the most recent time at which gene flow occurs. Finally, we demonstrate the application of the new method to a 106-locus yeast data set.

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.