1
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Westbury MV, Cabrera AA, Rey-Iglesia A, De Cahsan B, Duchêne DA, Hartmann S, Lorenzen ED. A genomic assessment of the marine-speciation paradox within the toothed whale superfamily Delphinoidea. Mol Ecol 2023; 32:4829-4843. [PMID: 37448145 DOI: 10.1111/mec.17069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 06/21/2023] [Accepted: 07/03/2023] [Indexed: 07/15/2023]
Abstract
The impact of post-divergence gene flow in speciation has been documented across a range of taxa in recent years, and may have been especially widespread in highly mobile, wide-ranging marine species, such as cetaceans. Here, we studied individual genomes from nine species across the three families of the toothed whale superfamily Delphinoidea (Delphinidae, Phocoenidae and Monodontidae). To investigate the role of post-divergence gene flow in the speciation process, we used a multifaceted approach, including (i) phylogenomics, (ii) the distribution of shared derived alleles and (iii) demographic inference. We found the divergence of lineages within Delphinoidea did not follow a process of pure bifurcation, but was much more complex. Sliding-window phylogenomics reveal a high prevalence of discordant topologies within the superfamily, with further analyses indicating these discordances arose due to both incomplete lineage sorting and gene flow. D-statistics and f-branch analyses supported gene flow between members of Delphinoidea, with the vast majority of gene flow occurring as ancient interfamilial events. Demographic analyses provided evidence that introgressive gene flow has likely ceased between all species pairs tested, despite reports of contemporary interspecific hybrids. Our study provides the first steps towards resolving the large complexity of speciation within Delphinoidea; we reveal the prevalence of ancient interfamilial gene flow events prior to the diversification of each family, and suggest that contemporary hybridisation events may be disadvantageous, as hybrid individuals do not appear to contribute to the parental species' gene pools.
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Affiliation(s)
| | | | | | - Binia De Cahsan
- Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - David A Duchêne
- Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Stefanie Hartmann
- Institute of Biochemistry and Biology, University of Potsdam, Potsdam, Germany
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2
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Kong S, Pons JC, Kubatko L, Wicke K. Classes of explicit phylogenetic networks and their biological and mathematical significance. J Math Biol 2022; 84:47. [PMID: 35503141 DOI: 10.1007/s00285-022-01746-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Revised: 01/18/2022] [Accepted: 03/31/2022] [Indexed: 11/24/2022]
Abstract
The evolutionary relationships among organisms have traditionally been represented using rooted phylogenetic trees. However, due to reticulate processes such as hybridization or lateral gene transfer, evolution cannot always be adequately represented by a phylogenetic tree, and rooted phylogenetic networks that describe such complex processes have been introduced as a generalization of rooted phylogenetic trees. In fact, estimating rooted phylogenetic networks from genomic sequence data and analyzing their structural properties is one of the most important tasks in contemporary phylogenetics. Over the last two decades, several subclasses of rooted phylogenetic networks (characterized by certain structural constraints) have been introduced in the literature, either to model specific biological phenomena or to enable tractable mathematical and computational analyses. In the present manuscript, we provide a thorough review of these network classes, as well as provide a biological interpretation of the structural constraints underlying these networks where possible. In addition, we discuss how imposing structural constraints on the network topology can be used to address the scalability and identifiability challenges faced in the estimation of phylogenetic networks from empirical data.
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Affiliation(s)
- Sungsik Kong
- Department of Evolution, Ecology, and Organismal Biology, The Ohio State University, Columbus, OH, USA
| | - Joan Carles Pons
- Department of Mathematics and Computer Science, University of the Balearic Islands, Palma, 07122, Spain
| | - Laura Kubatko
- Department of Evolution, Ecology, and Organismal Biology, The Ohio State University, Columbus, OH, USA.,Department of Statistics, The Ohio State University, Columbus, OH, USA
| | - Kristina Wicke
- Department of Mathematics, The Ohio State University, Columbus, OH, USA.
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3
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Jiao X, Flouri T, Yang Z. Multispecies coalescent and its applications to infer species phylogenies and cross-species gene flow. Natl Sci Rev 2022; 8:nwab127. [PMID: 34987842 PMCID: PMC8692950 DOI: 10.1093/nsr/nwab127] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 07/10/2021] [Accepted: 07/11/2021] [Indexed: 02/06/2023] Open
Abstract
Multispecies coalescent (MSC) is the extension of the single-population coalescent model to multiple species. It integrates the phylogenetic process of species divergences and the population genetic process of coalescent, and provides a powerful framework for a number of inference problems using genomic sequence data from multiple species, including estimation of species divergence times and population sizes, estimation of species trees accommodating discordant gene trees, inference of cross-species gene flow and species delimitation. In this review, we introduce the major features of the MSC model, discuss full-likelihood and heuristic methods of species tree estimation and summarize recent methodological advances in inference of cross-species gene flow. We discuss the statistical and computational challenges in the field and research directions where breakthroughs may be likely in the next few years.
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Affiliation(s)
- Xiyun Jiao
- Department of Genetics, Evolution and Environment, University College London, London WC1E 6BT, UK
| | - Tomáš Flouri
- Department of Genetics, Evolution and Environment, University College London, London WC1E 6BT, UK
| | - Ziheng Yang
- Department of Genetics, Evolution and Environment, University College London, London WC1E 6BT, UK
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4
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Rabier CE, Berry V, Stoltz M, Santos JD, Wang W, Glaszmann JC, Pardi F, Scornavacca C. On the inference of complex phylogenetic networks by Markov Chain Monte-Carlo. PLoS Comput Biol 2021; 17:e1008380. [PMID: 34478440 PMCID: PMC8445492 DOI: 10.1371/journal.pcbi.1008380] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2020] [Revised: 09/16/2021] [Accepted: 07/13/2021] [Indexed: 11/19/2022] Open
Abstract
For various species, high quality sequences and complete genomes are nowadays available for many individuals. This makes data analysis challenging, as methods need not only to be accurate, but also time efficient given the tremendous amount of data to process. In this article, we introduce an efficient method to infer the evolutionary history of individuals under the multispecies coalescent model in networks (MSNC). Phylogenetic networks are an extension of phylogenetic trees that can contain reticulate nodes, which allow to model complex biological events such as horizontal gene transfer, hybridization and introgression. We present a novel way to compute the likelihood of biallelic markers sampled along genomes whose evolution involved such events. This likelihood computation is at the heart of a Bayesian network inference method called SnappNet, as it extends the Snapp method inferring evolutionary trees under the multispecies coalescent model, to networks. SnappNet is available as a package of the well-known beast 2 software. Recently, the MCMC_BiMarkers method, implemented in PhyloNet, also extended Snapp to networks. Both methods take biallelic markers as input, rely on the same model of evolution and sample networks in a Bayesian framework, though using different methods for computing priors. However, SnappNet relies on algorithms that are exponentially more time-efficient on non-trivial networks. Using simulations, we compare performances of SnappNet and MCMC_BiMarkers. We show that both methods enjoy similar abilities to recover simple networks, but SnappNet is more accurate than MCMC_BiMarkers on more complex network scenarios. Also, on complex networks, SnappNet is found to be extremely faster than MCMC_BiMarkers in terms of time required for the likelihood computation. We finally illustrate SnappNet performances on a rice data set. SnappNet infers a scenario that is consistent with previous results and provides additional understanding of rice evolution.
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Affiliation(s)
- Charles-Elie Rabier
- Institut des Sciences de l’Evolution (ISEM), Université de Montpellier, CNRS, EPHE, IRD, Montpellier, France
- Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier (LIRMM), Université de Montpellier, CNRS, Montpellier, France
- Institut Montpelliérain Alexander Grothendieck (IMAG), Université de Montpellier, CNRS, Montpellier, France
| | - Vincent Berry
- Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier (LIRMM), Université de Montpellier, CNRS, Montpellier, France
| | - Marnus Stoltz
- Institut des Sciences de l’Evolution (ISEM), Université de Montpellier, CNRS, EPHE, IRD, Montpellier, France
| | - João D. Santos
- CIRAD, UMR AGAP, Montpellier, France
- Amélioration Génétique et Adaptation des Plantes méditerranéennes et tropicales (AGAP), Université de Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, France
| | - Wensheng Wang
- Institute of Crop Sciences (ICS), Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jean-Christophe Glaszmann
- CIRAD, UMR AGAP, Montpellier, France
- Amélioration Génétique et Adaptation des Plantes méditerranéennes et tropicales (AGAP), Université de Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, France
| | - Fabio Pardi
- Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier (LIRMM), Université de Montpellier, CNRS, Montpellier, France
| | - Celine Scornavacca
- Institut des Sciences de l’Evolution (ISEM), Université de Montpellier, CNRS, EPHE, IRD, Montpellier, France
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5
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Adams RH, Blackmon H, DeGiorgio M. Of Traits and Trees: Probabilistic Distances under Continuous Trait Models for Dissecting the Interplay among Phylogeny, Model, and Data. Syst Biol 2021; 70:660-680. [PMID: 33587145 PMCID: PMC8208806 DOI: 10.1093/sysbio/syab009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Accepted: 02/01/2021] [Indexed: 12/03/2022] Open
Abstract
Stochastic models of character trait evolution have become a cornerstone of evolutionary biology in an array of contexts. While probabilistic models have been used extensively for statistical inference, they have largely been ignored for the purpose of measuring distances between phylogeny-aware models. Recent contributions to the problem of phylogenetic distance computation have highlighted the importance of explicitly considering evolutionary model parameters and their impacts on molecular sequence data when quantifying dissimilarity between trees. By comparing two phylogenies in terms of their induced probability distributions that are functions of many model parameters, these distances can be more informative than traditional approaches that rely strictly on differences in topology or branch lengths alone. Currently, however, these approaches are designed for comparing models of nucleotide substitution and gene tree distributions, and thus, are unable to address other classes of traits and associated models that may be of interest to evolutionary biologists. Here, we expand the principles of probabilistic phylogenetic distances to compute tree distances under models of continuous trait evolution along a phylogeny. By explicitly considering both the degree of relatedness among species and the evolutionary processes that collectively give rise to character traits, these distances provide a foundation for comparing models and their predictions, and for quantifying the impacts of assuming one phylogenetic background over another while studying the evolution of a particular trait. We demonstrate the properties of these approaches using theory, simulations, and several empirical data sets that highlight potential uses of probabilistic distances in many scenarios. We also introduce an open-source R package named PRDATR for easy application by the scientific community for computing phylogenetic distances under models of character trait evolution.[Brownian motion; comparative methods; phylogeny; quantitative traits.].
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Affiliation(s)
- Richard H Adams
- Department of Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL 33431, USA
| | - Heath Blackmon
- Department of Biology, Texas A&M University, College Station, TX 77843, USA
| | - Michael DeGiorgio
- Department of Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL 33431, USA
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6
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Huber KT, Linz S, Moulton V. The rigid hybrid number for two phylogenetic trees. J Math Biol 2021; 82:40. [PMID: 33770290 PMCID: PMC7997861 DOI: 10.1007/s00285-021-01594-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Revised: 01/25/2021] [Accepted: 03/13/2021] [Indexed: 11/29/2022]
Abstract
Recently there has been considerable interest in the problem of finding a phylogenetic network with a minimum number of reticulation vertices which displays a given set of phylogenetic trees, that is, a network with minimum hybrid number. Such networks are useful for representing the evolution of species whose genomes have undergone processes such as lateral gene transfer and recombination that cannot be represented appropriately by a phylogenetic tree. Even so, as was recently pointed out in the literature, insisting that a network displays the set of trees can be an overly restrictive assumption when modeling certain evolutionary phenomena such as incomplete lineage sorting. In this paper, we thus consider the less restrictive notion of rigidly displaying which we introduce and study here. More specifically, we characterize when two trees can be rigidly displayed by a certain type of phylogenetic network called a temporal tree-child network in terms of fork-picking sequences. These are sequences of special subconfigurations of the two trees related to the well-studied cherry-picking sequences. We also show that, in case it exists, the rigid hybrid number for two phylogenetic trees is given by a minimum weight fork-picking sequence for the trees. Finally, we consider the relationship between the rigid hybrid number and three closely related numbers; the weak, beaded, and temporal hybrid numbers. In particular, we show that these numbers can all be different even for a fixed pair of trees, and also present an infinite family of pairs of trees which demonstrates that the difference between the rigid hybrid number and the temporal-hybrid number for two phylogenetic trees on the same set of n leaves can grow at least linearly with n.
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Affiliation(s)
| | - Simone Linz
- School of Computer Science, University of Auckland, Auckland, New Zealand
| | - Vincent Moulton
- School of Computing Sciences, University of East Anglia, Norwich, UK
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7
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Kim A, Rosenberg NA, Degnan JH. Probabilities of Unranked and Ranked Anomaly Zones under Birth-Death Models. Mol Biol Evol 2021; 37:1480-1494. [PMID: 31860090 DOI: 10.1093/molbev/msz305] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Abstract
A labeled gene tree topology that is more probable than the labeled gene tree topology matching a species tree is called "anomalous." Species trees that can generate such anomalous gene trees are said to be in the "anomaly zone." Here, probabilities of "unranked" and "ranked" gene tree topologies under the multispecies coalescent are considered. A ranked tree depicts not only the topological relationship among gene lineages, as an unranked tree does, but also the sequence in which the lineages coalesce. In this article, we study how the parameters of a species tree simulated under a constant-rate birth-death process can affect the probability that the species tree lies in the anomaly zone. We find that with more than five taxa, it is possible for species trees to have both anomalous unranked and ranked gene trees. The probability of being in either type of anomaly zone increases with more taxa. The probability of anomalous gene trees also increases with higher speciation rates. We observe that the probabilities of unranked anomaly zones are higher and grow much faster than those of ranked anomaly zones as the speciation rate increases. Our simulation shows that the most probable ranked gene tree is likely to have the same unranked topology as the species tree. We design the software PRANC, which computes probabilities of ranked gene tree topologies given a species tree under the coalescent model.
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Affiliation(s)
- Anastasiia Kim
- Department of Mathematics and Statistics, University of New Mexico, Albuquerque, NM
| | | | - James H Degnan
- Department of Mathematics and Statistics, University of New Mexico, Albuquerque, NM
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8
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Flouri T, Jiao X, Rannala B, Yang Z. A Bayesian Implementation of the Multispecies Coalescent Model with Introgression for Phylogenomic Analysis. Mol Biol Evol 2021; 37:1211-1223. [PMID: 31825513 PMCID: PMC7086182 DOI: 10.1093/molbev/msz296] [Citation(s) in RCA: 58] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Recent analyses suggest that cross-species gene flow or introgression is common in nature, especially during species divergences. Genomic sequence data can be used to infer introgression events and to estimate the timing and intensity of introgression, providing an important means to advance our understanding of the role of gene flow in speciation. Here, we implement the multispecies-coalescent-with-introgression model, an extension of the multispecies-coalescent model to incorporate introgression, in our Bayesian Markov chain Monte Carlo program Bpp. The multispecies-coalescent-with-introgression model accommodates deep coalescence (or incomplete lineage sorting) and introgression and provides a natural framework for inference using genomic sequence data. Computer simulation confirms the good statistical properties of the method, although hundreds or thousands of loci are typically needed to estimate introgression probabilities reliably. Reanalysis of data sets from the purple cone spruce confirms the hypothesis of homoploid hybrid speciation. We estimated the introgression probability using the genomic sequence data from six mosquito species in the Anopheles gambiae species complex, which varies considerably across the genome, likely driven by differential selection against introgressed alleles.
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Affiliation(s)
- Tomáš Flouri
- Department of Genetics, Evolution and Environment, University College London, London, United Kingdom
| | - Xiyun Jiao
- Department of Genetics, Evolution and Environment, University College London, London, United Kingdom
| | - Bruce Rannala
- Department of Evolution and Ecology, University of California, Davis, Davis, CA
| | - Ziheng Yang
- Department of Genetics, Evolution and Environment, University College London, London, United Kingdom
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9
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Glémin S, Scornavacca C, Dainat J, Burgarella C, Viader V, Ardisson M, Sarah G, Santoni S, David J, Ranwez V. Pervasive hybridizations in the history of wheat relatives. SCIENCE ADVANCES 2019; 5:eaav9188. [PMID: 31049399 PMCID: PMC6494498 DOI: 10.1126/sciadv.aav9188] [Citation(s) in RCA: 56] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2018] [Accepted: 03/20/2019] [Indexed: 05/18/2023]
Abstract
Cultivated wheats are derived from an intricate history of three genomes, A, B, and D, present in both diploid and polyploid species. It was recently proposed that the D genome originated from an ancient hybridization between the A and B lineages. However, this result has been questioned, and a robust phylogeny of wheat relatives is still lacking. Using transcriptome data from all diploid species and a new methodological approach, our comprehensive phylogenomic analysis revealed that more than half of the species descend from an ancient hybridization event but with a more complex scenario involving a different parent than previously thought-Aegilops mutica, an overlooked wild species-instead of the B genome. We also detected other extensive gene flow events that could explain long-standing controversies in the classification of wheat relatives.
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Affiliation(s)
- Sylvain Glémin
- CNRS, Univ Rennes, ECOBIO (Ecosystèmes, biodiversité, évolution)–UMR 6553, F-35042 Rennes, France
- Department of Ecology and Genetics, Evolutionary Biology Center, Uppsala University, Norbyvägen 18D, 752 36 Uppsala, Sweden
| | - Celine Scornavacca
- Institut des Sciences de l’Evolution Université de Montpellier, CNRS, IRD, EPHE CC 064, Place Eugène Bataillon, 34095 Montpellier, cedex 05, France
| | - Jacques Dainat
- National Bioinformatics Infrastructure Sweden (NBIS), SciLifeLab, Uppsala Biomedicinska Centrum (BMC), Husargatan 3, S-751 23 Uppsala, Sweden
- IMBIM–Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala Biomedicinska Centrum (BMC), Husargatan 3, Box 582, S-751 23 Uppsala, Sweden
| | - Concetta Burgarella
- AGAP, Univ Montpellier, CIRAD, INRA, Montpellier SupAgro, Montpellier, France
- CIRAD, UMR AGAP, F-34398 Montpellier, France
| | - Véronique Viader
- AGAP, Univ Montpellier, CIRAD, INRA, Montpellier SupAgro, Montpellier, France
| | - Morgane Ardisson
- AGAP, Univ Montpellier, CIRAD, INRA, Montpellier SupAgro, Montpellier, France
| | - Gautier Sarah
- AGAP, Univ Montpellier, CIRAD, INRA, Montpellier SupAgro, Montpellier, France
- South Green Bioinformatics Platform, BIOVERSITY, CIRAD, INRA, IRD, Montpellier SupAgro, Montpellier, France
| | - Sylvain Santoni
- AGAP, Univ Montpellier, CIRAD, INRA, Montpellier SupAgro, Montpellier, France
| | - Jacques David
- AGAP, Univ Montpellier, CIRAD, INRA, Montpellier SupAgro, Montpellier, France
| | - Vincent Ranwez
- AGAP, Univ Montpellier, CIRAD, INRA, Montpellier SupAgro, Montpellier, France
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10
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Zhang C, Ogilvie HA, Drummond AJ, Stadler T. Bayesian Inference of Species Networks from Multilocus Sequence Data. Mol Biol Evol 2019; 35:504-517. [PMID: 29220490 PMCID: PMC5850812 DOI: 10.1093/molbev/msx307] [Citation(s) in RCA: 103] [Impact Index Per Article: 20.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
Reticulate species evolution, such as hybridization or introgression, is relatively common in nature. In the presence of reticulation, species relationships can be captured by a rooted phylogenetic network, and orthologous gene evolution can be modeled as bifurcating gene trees embedded in the species network. We present a Bayesian approach to jointly infer species networks and gene trees from multilocus sequence data. A novel birth-hybridization process is used as the prior for the species network, and we assume a multispecies network coalescent prior for the embedded gene trees. We verify the ability of our method to correctly sample from the posterior distribution, and thus to infer a species network, through simulations. To quantify the power of our method, we reanalyze two large data sets of genes from spruces and yeasts. For the three closely related spruces, we verify the previously suggested homoploid hybridization event in this clade; for the yeast data, we find extensive hybridization events. Our method is available within the BEAST 2 add-on SpeciesNetwork, and thus provides an extensible framework for Bayesian inference of reticulate evolution.
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Affiliation(s)
- Chi Zhang
- Department of Biosystems Science and Engineering, Eidgenössische Technische Hochschule Zürich, Basel, Switzerland.,Swiss Institute of Bioinformatics (SIB), Switzerland.,Key Laboratory of Vertebrate Evolution and Human Origins of Chinese Academy of Sciences, Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences, Beijing, China
| | - Huw A Ogilvie
- Division of Ecology and Evolution, Research School of Biology, Australian National University, Canberra, Australia.,Centre for Computational Evolution, University of Auckland, Auckland, New Zealand
| | - Alexei J Drummond
- Centre for Computational Evolution, University of Auckland, Auckland, New Zealand.,Department of Computer Science, University of Auckland, Auckland, New Zealand
| | - Tanja Stadler
- Department of Biosystems Science and Engineering, Eidgenössische Technische Hochschule Zürich, Basel, Switzerland.,Swiss Institute of Bioinformatics (SIB), Switzerland
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11
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Baños H. Identifying Species Network Features from Gene Tree Quartets Under the Coalescent Model. Bull Math Biol 2019; 81:494-534. [PMID: 30094772 PMCID: PMC6344282 DOI: 10.1007/s11538-018-0485-4] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2017] [Accepted: 07/30/2018] [Indexed: 10/28/2022]
Abstract
We show that many topological features of level-1 species networks are identifiable from the distribution of the gene tree quartets under the network multi-species coalescent model. In particular, every cycle of size at least 4 and every hybrid node in a cycle of size at least 5 are identifiable. This is a step toward justifying the inference of such networks which was recently implemented by Solís-Lemus and Ané. We show additionally how to compute quartet concordance factors for a network in terms of simpler networks, and explore some circumstances in which cycles of size 3 and hybrid nodes in 4-cycles can be detected.
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Affiliation(s)
- Hector Baños
- University of Alaska Fairbanks, P.O. Box 756660, Fairbanks, AK, 99775-6660, USA.
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12
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The Timing and Direction of Introgression Under the Multispecies Network Coalescent. Genetics 2019; 211:1059-1073. [PMID: 30670542 DOI: 10.1534/genetics.118.301831] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2018] [Accepted: 01/21/2019] [Indexed: 12/26/2022] Open
Abstract
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, D 1 and D 2, which can be used in conjunction with other information to test hypotheses relating to the timing and direction of introgression, respectively. D 1 may find use in evaluating cases of homoploid hybrid speciation (HHS), while D 2 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 D 1 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.
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13
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Degnan JH. Modeling Hybridization Under the Network Multispecies Coalescent. Syst Biol 2018; 67:786-799. [PMID: 29846734 PMCID: PMC6101600 DOI: 10.1093/sysbio/syy040] [Citation(s) in RCA: 59] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2017] [Revised: 05/13/2018] [Accepted: 05/16/2018] [Indexed: 11/13/2022] Open
Abstract
Simultaneously modeling hybridization and the multispecies coalescent is becoming increasingly common, and inference of species networks in this context is now implemented in several software packages. This article addresses some of the conceptual issues and decisions to be made in this modeling, including whether or not to use branch lengths and issues with model identifiability. This article is based on a talk given at a Spotlight Session at Evolution 2017 meeting in Portland, Oregon. This session included several talks about modeling hybridization and gene flow in the presence of incomplete lineage sorting. Other talks given at this meeting are also included in this special issue of Systematic Biology.
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Affiliation(s)
- James H Degnan
- Department of Mathematics and Statistics, University of New Mexico, Albuquerque, NM 87131, USA
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14
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Shekhar S, Roch S, Mirarab S. Species Tree Estimation Using ASTRAL: How Many Genes Are Enough? IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2018; 15:1738-1747. [PMID: 28976320 DOI: 10.1109/tcbb.2017.2757930] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Species tree reconstruction from genomic data is increasingly performed using methods that account for sources of gene tree discordance such as incomplete lineage sorting. One popular method for reconstructing species trees from unrooted gene tree topologies is ASTRAL. In this paper, we derive theoretical sample complexity results for the number of genes required by ASTRAL to guarantee reconstruction of the correct species tree with high probability. We also validate those theoretical bounds in a simulation study. Our results indicate that ASTRAL requires gene trees to reconstruct the species tree correctly with high probability where is the number of species and is the length of the shortest branch in the species tree. Our simulations, some under the anomaly zone, show trends consistent with the theoretical bounds and also provide some practical insights on the conditions where ASTRAL works well.
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Gambette P, van Iersel L, Jones M, Lafond M, Pardi F, Scornavacca C. Rearrangement moves on rooted phylogenetic networks. PLoS Comput Biol 2017; 13:e1005611. [PMID: 28763439 PMCID: PMC5557604 DOI: 10.1371/journal.pcbi.1005611] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2017] [Revised: 08/15/2017] [Accepted: 05/27/2017] [Indexed: 12/05/2022] Open
Abstract
Phylogenetic tree reconstruction is usually done by local search heuristics that explore the space of the possible tree topologies via simple rearrangements of their structure. Tree rearrangement heuristics have been used in combination with practically all optimization criteria in use, from maximum likelihood and parsimony to distance-based principles, and in a Bayesian context. Their basic components are rearrangement moves that specify all possible ways of generating alternative phylogenies from a given one, and whose fundamental property is to be able to transform, by repeated application, any phylogeny into any other phylogeny. Despite their long tradition in tree-based phylogenetics, very little research has gone into studying similar rearrangement operations for phylogenetic network—that is, phylogenies explicitly representing scenarios that include reticulate events such as hybridization, horizontal gene transfer, population admixture, and recombination. To fill this gap, we propose “horizontal” moves that ensure that every network of a certain complexity can be reached from any other network of the same complexity, and “vertical” moves that ensure reachability between networks of different complexities. When applied to phylogenetic trees, our horizontal moves—named rNNI and rSPR—reduce to the best-known moves on rooted phylogenetic trees, nearest-neighbor interchange and rooted subtree pruning and regrafting. Besides a number of reachability results—separating the contributions of horizontal and vertical moves—we prove that rNNI moves are local versions of rSPR moves, and provide bounds on the sizes of the rNNI neighborhoods. The paper focuses on the most biologically meaningful versions of phylogenetic networks, where edges are oriented and reticulation events clearly identified. Moreover, our rearrangement moves are robust to the fact that networks with higher complexity usually allow a better fit with the data. Our goal is to provide a solid basis for practical phylogenetic network reconstruction. Phylogenetic networks are used to represent reticulate evolution, that is, cases in which the tree-of-life metaphor for evolution breaks down, because some of its branches have merged at one or several points in the past. This may occur, for example, when some organisms in the phylogeny are hybrids. In this paper, we deal with an elementary question for the reconstruction of phylogenetic networks: how to explore the space of all possible networks. The fundamental component for this is the set of operations that should be employed to generate alternative hypotheses for what happened in the past—which serve as basic blocks for optimization techniques such as hill-climbing. Although these approaches have a long tradition in classic tree-based phylogenetics, their application to networks that explicitly represent reticulate evolution is relatively unexplored. This paper provides the fundamental definitions and theoretical results for subsequent work in practical methods for phylogenetic network reconstruction: we subdivide networks into layers, according to a generally-accepted measure of their complexity, and provide operations that allow both to fully explore each layer, and to move across different layers. These operations constitute natural generalizations of well-known operations for the exploration of the space of phylogenetic trees, the lowest layer in the hierarchy described above.
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Affiliation(s)
- Philippe Gambette
- Laboratoire d’Informatique Gaspard-Monge (LIGM), Université Paris-Est, CNRS, ENPC, ESIEE Paris, UPEM, F-77454, Marne-la-Vallée, France
| | - Leo van Iersel
- Delft Institute of Applied Mathematics, Delft University of Technology, Postbus 5031, 2628 CD Delft, The Netherlands
| | - Mark Jones
- Delft Institute of Applied Mathematics, Delft University of Technology, Postbus 5031, 2628 CD Delft, The Netherlands
| | - Manuel Lafond
- Department of Mathematics and Statistics, University of Ottawa, K1N 6N5 Ottawa, Canada
| | - Fabio Pardi
- Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier (LIRMM), Université de Montpellier, CNRS, 34095 Montpellier Cedex 5, France
- Institut de Biologie Computationnelle (IBC), 34095 Montpellier, France
- * E-mail:
| | - Celine Scornavacca
- Institut de Biologie Computationnelle (IBC), 34095 Montpellier, France
- Institut des Sciences de l’Evolution (ISE-M), Université de Montpellier, CNRS, IRD, EPHE, 34095 Montpellier Cedex 5, France
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