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      Species Tree Inference with BPP Using Genomic Sequences and the Multispecies Coalescent

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          Abstract

          The multispecies coalescent provides a natural framework for accommodating ancestral genetic polymorphism and coalescent processes that can cause different genomic regions to have different genealogical histories. The Bayesian program BPP includes a full-likelihood implementation of the multispecies coalescent, using transmodel Markov chain Monte Carlo to calculate the posterior probabilities of different species trees. BPP is suitable for analyzing multilocus sequence data sets and it accommodates the heterogeneity of gene trees (both the topology and branch lengths) among loci and gene tree uncertainties due to limited phylogenetic information at each locus. Here, we provide a practical guide to the use of BPP in species tree estimation. BPP is a command-line program that runs on linux, macosx, and windows. This protocol shows how to use both BPP 3.4 ( http://abacus.gene.ucl.ac.uk/software/) and BPP 4.0 ( https://github.com/bpp/).

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          Bayesian species delimitation using multilocus sequence data.

          Ziheng Yang, Bruce Rannala (2010)
          In the absence of recent admixture between species, bipartitions of individuals in gene trees that are shared across loci can potentially be used to infer the presence of two or more species. This approach to species delimitation via molecular sequence data has been constrained by the fact that genealogies for individual loci are often poorly resolved and that ancestral lineage sorting, hybridization, and other population genetic processes can lead to discordant gene trees. Here we use a Bayesian modeling approach to generate the posterior probabilities of species assignments taking account of uncertainties due to unknown gene trees and the ancestral coalescent process. For tractability, we rely on a user-specified guide tree to avoid integrating over all possible species delimitations. The statistical performance of the method is examined using simulations, and the method is illustrated by analyzing sequence data from rotifers, fence lizards, and human populations.
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            Is a new and general theory of molecular systematics emerging?

            Scott Edwards (2009)
            The advent and maturation of algorithms for estimating species trees-phylogenetic trees that allow gene tree heterogeneity and whose tips represent lineages, populations and species, as opposed to genes-represent an exciting confluence of phylogenetics, phylogeography, and population genetics, and ushers in a new generation of concepts and challenges for the molecular systematist. In this essay I argue that to better deal with the large multilocus datasets brought on by phylogenomics, and to better align the fields of phylogeography and phylogenetics, we should embrace the primacy of species trees, not only as a new and useful practical tool for systematics, but also as a long-standing conceptual goal of systematics that, largely due to the lack of appropriate computational tools, has been eclipsed in the past few decades. I suggest that phylogenies as gene trees are a "local optimum" for systematics, and review recent advances that will bring us to the broader optimum inherent in species trees. In addition to adopting new methods of phylogenetic analysis (and ideally reserving the term "phylogeny" for species trees rather than gene trees), the new paradigm suggests shifts in a number of practices, such as sampling data to maximize not only the number of accumulated sites but also the number of independently segregating genes; routinely using coalescent or other models in computer simulations to allow gene tree heterogeneity; and understanding better the role of concatenation in influencing topologies and confidence in phylogenies. By building on the foundation laid by concepts of gene trees and coalescent theory, and by taking cues from recent trends in multilocus phylogeography, molecular systematics stands to be enriched. Many of the challenges and lessons learned for estimating gene trees will carry over to the challenge of estimating species trees, although adopting the species tree paradigm will clarify many issues (such as the nature of polytomies and the star tree paradox), raise conceptually new challenges, or provide new answers to old questions.
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              Inconsistency of phylogenetic estimates from concatenated data under coalescence.

              Laura Kubatko, James H. Degnan (2007)
              Although multiple gene sequences are becoming increasingly available for molecular phylogenetic inference, the analysis of such data has largely relied on inference methods designed for single genes. One of the common approaches to analyzing data from multiple genes is concatenation of the individual gene data to form a single supergene to which traditional phylogenetic inference procedures - e.g., maximum parsimony (MP) or maximum likelihood (ML) - are applied. Recent empirical studies have demonstrated that concatenation of sequences from multiple genes prior to phylogenetic analysis often results in inference of a single, well-supported phylogeny. Theoretical work, however, has shown that the coalescent can produce substantial variation in single-gene histories. Using simulation, we combine these ideas to examine the performance of the concatenation approach under conditions in which the coalescent produces a high level of discord among individual gene trees and show that it leads to statistically inconsistent estimation in this setting. Furthermore, use of the bootstrap to measure support for the inferred phylogeny can result in moderate to strong support for an incorrect tree under these conditions. These results highlight the importance of incorporating variation in gene histories into multilocus phylogenetics.
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                Author and article information

                Contributors
                Anne D Yoder: Role: Associate Editor
                Journal
                Journal ID (nlm-ta): Mol Biol Evol
                Journal ID (iso-abbrev): Mol. Biol. Evol
                Journal ID (publisher-id): molbev
                Title: Molecular Biology and Evolution
                Publisher: Oxford University Press
                ISSN (Print): 0737-4038
                ISSN (Electronic): 1537-1719
                Publication date (Print): October 2018
                Publication date (Electronic): 23 July 2018
                Publication date PMC-release: 23 July 2018
                Volume: 35
                Issue: 10
                Pages: 2585-2593
                Affiliations
                [1 ]Department of Genetics, Evolution and Environment, University College London, London, United Kingdom
                [2 ]Department of Ecology and Evolution, University of California, Davis, CA
                Author notes
                Corresponding authors: E-mails: brannala@ 123456ucdavis.edu ; z.yang@ 123456ucl.ac.uk .
                Article
                Publisher ID: msy147
                DOI: 10.1093/molbev/msy147
                PMC ID: 6188564
                PubMed ID: 30053098
                SO-VID: a84bdea6-2e5a-46b3-9949-168e2e39cc56
                Copyright © © The Author(s) 2018. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.
                License:

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Page count
                Pages: 9
                Funding
                Funded by: Biotechnological and Biological Sciences Research Council
                Award ID: BB/P006493/1
                Categories
                Subject: Protocols

                ScienceOpen disciplines: Molecular biology
                Keywords: bpp,mcmc,multispecies coalescent,species tree inference
                Data availability:
                ScienceOpen disciplines: Molecular biology
                Keywords: bpp, mcmc, multispecies coalescent, species tree inference

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