Phylogenetic Analysis 2 Introducing Some of the Most Commonly Used Methods for Phylogenetic Analysis
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Lecture Notes: the Mathematics of Phylogenetics
Lecture Notes: The Mathematics of Phylogenetics Elizabeth S. Allman, John A. Rhodes IAS/Park City Mathematics Institute June-July, 2005 University of Alaska Fairbanks Spring 2009, 2012, 2016 c 2005, Elizabeth S. Allman and John A. Rhodes ii Contents 1 Sequences and Molecular Evolution 3 1.1 DNA structure . .4 1.2 Mutations . .5 1.3 Aligned Orthologous Sequences . .7 2 Combinatorics of Trees I 9 2.1 Graphs and Trees . .9 2.2 Counting Binary Trees . 14 2.3 Metric Trees . 15 2.4 Ultrametric Trees and Molecular Clocks . 17 2.5 Rooting Trees with Outgroups . 18 2.6 Newick Notation . 19 2.7 Exercises . 20 3 Parsimony 25 3.1 The Parsimony Criterion . 25 3.2 The Fitch-Hartigan Algorithm . 28 3.3 Informative Characters . 33 3.4 Complexity . 35 3.5 Weighted Parsimony . 36 3.6 Recovering Minimal Extensions . 38 3.7 Further Issues . 39 3.8 Exercises . 40 4 Combinatorics of Trees II 45 4.1 Splits and Clades . 45 4.2 Refinements and Consensus Trees . 49 4.3 Quartets . 52 4.4 Supertrees . 53 4.5 Final Comments . 54 4.6 Exercises . 55 iii iv CONTENTS 5 Distance Methods 57 5.1 Dissimilarity Measures . 57 5.2 An Algorithmic Construction: UPGMA . 60 5.3 Unequal Branch Lengths . 62 5.4 The Four-point Condition . 66 5.5 The Neighbor Joining Algorithm . 70 5.6 Additional Comments . 72 5.7 Exercises . 73 6 Probabilistic Models of DNA Mutation 81 6.1 A first example . 81 6.2 Markov Models on Trees . 87 6.3 Jukes-Cantor and Kimura Models . -
Investgating Determinants of Phylogeneic Accuracy
IMPACT OF MOLECULAR EVOLUTIONARY FOOTPRINTS ON PHYLOGENETIC ACCURACY – A SIMULATION STUDY Dissertation Submitted to The College of Arts and Sciences of the UNIVERSITY OF DAYTON In Partial Fulfillment of the Requirements for The Degree Doctor of Philosophy in Biology by Bhakti Dwivedi UNIVERSITY OF DAYTON August, 2009 i APPROVED BY: _________________________ Gadagkar, R. Sudhindra Ph.D. Major Advisor _________________________ Robinson, Jayne Ph.D. Committee Member Chair Department of Biology _________________________ Nielsen, R. Mark Ph.D. Committee Member _________________________ Rowe, J. John Ph.D. Committee Member _________________________ Goldman, Dan Ph.D. Committee Member ii ABSTRACT IMPACT OF MOLECULAR EVOLUTIONARY FOOTPRINTS ON PHYLOGENETIC ACCURACY – A SIMULATION STUDY Dwivedi Bhakti University of Dayton Advisor: Dr. Sudhindra R. Gadagkar An accurately inferred phylogeny is important to the study of molecular evolution. Factors impacting the accuracy of a phylogenetic tree can be traced to several consecutive steps leading to the inference of the phylogeny. In this simulation-based study our focus is on the impact of the certain evolutionary features of the nucleotide sequences themselves in the alignment rather than any source of error during the process of sequence alignment or due to the choice of the method of phylogenetic inference. Nucleotide sequences can be characterized by summary statistics such as sequence length and base composition. When two or more such sequences need to be compared to each other (as in an alignment prior to phylogenetic analysis) additional evolutionary features come into play, such as the overall rate of nucleotide substitution, the ratio of two specific instantaneous, rates of substitution (rate at which transitions and transversions occur), and the shape parameter, of the gamma distribution (that quantifies the extent of iii heterogeneity in substitution rate among sites in an alignment). -
Random Mutation and Natural Selection in Competitive and Non-Competitive Environments
ISSN: 2574-1241 Volume 5- Issue 4: 2018 DOI: 10.26717/BJSTR.2018.09.001751 Alan Kleinman. Biomed J Sci & Tech Res Mini Review Open Access Random Mutation and Natural Selection In Competitive and Non-Competitive Environments Alan Kleinman* Department of Medicine, USA Received: : September 10, 2018; Published: September 18, 2018 *Corresponding author: Alan Kleinman, PO BOX 1240, Coarsegold, CA 93614, USA Abstract Random mutation and natural selection occur in a variety of different environments. Three of the most important factors which govern the rate at which this phenomenon occurs is whether there is competition between the different variants for the resources of the environment or not whether the replicator can do recombination and whether the intensity of selection has an impact on the evolutionary trajectory. Two different experimental models of random mutation and natural selection are analyzed to determine the impact of competition on random mutation and natural selection. One experiment places the different variants in competition for the resources of the environment while the lineages are attempting to evolve to the selection pressure while the other experiment allows the lineages to grow without intense competition for the resources of the environment while the different lineages are attempting to evolve to the selection pressure. The mathematics which governs either experiment is discussed, and the results correlated to the medical problem of the evolution of drug resistance. Introduction important experiments testing the RMNS phenomenon. And how Random mutation and natural selection (RMNS) are a does recombination alter the evolutionary trajectory to a given phenomenon which works to defeat the treatments physicians use selection pressure? for infectious diseases and cancers. -
Phylogeny Inference Based on Parsimony and Other Methods Using Paup*
8 Phylogeny inference based on parsimony and other methods using Paup* THEORY David L. Swofford and Jack Sullivan 8.1 Introduction Methods for inferring evolutionary trees can be divided into two broad categories: thosethatoperateonamatrixofdiscretecharactersthatassignsoneormore attributes or character states to each taxon (i.e. sequence or gene-family member); and those that operate on a matrix of pairwise distances between taxa, with each distance representing an estimate of the amount of divergence between two taxa since they last shared a common ancestor (see Chapter 1). The most commonly employed discrete-character methods used in molecular phylogenetics are parsi- mony and maximum likelihood methods. For molecular data, the character-state matrix is typically an aligned set of DNA or protein sequences, in which the states are the nucleotides A, C, G, and T (i.e. DNA sequences) or symbols representing the 20 common amino acids (i.e. protein sequences); however, other forms of discrete data such as restriction-site presence/absence and gene-order information also may be used. Parsimony, maximum likelihood, and some distance methods are examples of a broader class of phylogenetic methods that rely on the use of optimality criteria. Methods in this class all operate by explicitly defining an objective function that returns a score for any input tree topology. This tree score thus allows any two or more trees to be ranked according to the chosen optimality criterion. Ordinarily, phylogenetic inference under criterion-based methods couples the selection of The Phylogenetic Handbook: a Practical Approach to Phylogenetic Analysis and Hypothesis Testing, Philippe Lemey, Marco Salemi, and Anne-Mieke Vandamme (eds.). -
In Defence of the Three-Domains of Life Paradigm P.T.S
van der Gulik et al. BMC Evolutionary Biology (2017) 17:218 DOI 10.1186/s12862-017-1059-z REVIEW Open Access In defence of the three-domains of life paradigm P.T.S. van der Gulik1*, W.D. Hoff2 and D. Speijer3* Abstract Background: Recently, important discoveries regarding the archaeon that functioned as the “host” in the merger with a bacterium that led to the eukaryotes, its “complex” nature, and its phylogenetic relationship to eukaryotes, have been reported. Based on these new insights proposals have been put forward to get rid of the three-domain Model of life, and replace it with a two-domain model. Results: We present arguments (both regarding timing, complexity, and chemical nature of specific evolutionary processes, as well as regarding genetic structure) to resist such proposals. The three-domain Model represents an accurate description of the differences at the most fundamental level of living organisms, as the eukaryotic lineage that arose from this unique merging event is distinct from both Archaea and Bacteria in a myriad of crucial ways. Conclusions: We maintain that “a natural system of organisms”, as proposed when the three-domain Model of life was introduced, should not be revised when considering the recent discoveries, however exciting they may be. Keywords: Eucarya, LECA, Phylogenetics, Eukaryogenesis, Three-domain model Background (English: domain) as a higher taxonomic level than The discovery that methanogenic microbes differ funda- regnum: introducing the three domains of cellular life, Ar- mentally from Bacteria such as Escherichia coli or Bacillus chaea, Bacteria and Eucarya. This paradigm was proposed subtilis constitutes one of the most important biological by Woese, Kandler and Wheelis in PNAS in 1990 [2]. -
Phylogenetic Trees and Cladograms Are Graphical Representations (Models) of Evolutionary History That Can Be Tested
AP Biology Lab/Cladograms and Phylogenetic Trees Name _______________________________ Relationship to the AP Biology Curriculum Framework Big Idea 1: The process of evolution drives the diversity and unity of life. Essential knowledge 1.B.2: Phylogenetic trees and cladograms are graphical representations (models) of evolutionary history that can be tested. Learning Objectives: LO 1.17 The student is able to pose scientific questions about a group of organisms whose relatedness is described by a phylogenetic tree or cladogram in order to (1) identify shared characteristics, (2) make inferences about the evolutionary history of the group, and (3) identify character data that could extend or improve the phylogenetic tree. LO 1.18 The student is able to evaluate evidence provided by a data set in conjunction with a phylogenetic tree or a simple cladogram to determine evolutionary history and speciation. LO 1.19 The student is able create a phylogenetic tree or simple cladogram that correctly represents evolutionary history and speciation from a provided data set. [Introduction] Cladistics is the study of evolutionary classification. Cladograms show evolutionary relationships among organisms. Comparative morphology investigates characteristics for homology and analogy to determine which organisms share a recent common ancestor. A cladogram will begin by grouping organisms based on a characteristics displayed by ALL the members of the group. Subsequently, the larger group will contain increasingly smaller groups that share the traits of the groups before them. However, they also exhibit distinct changes as the new species evolve. Further, molecular evidence from genes which rarely mutate can provide molecular clocks that tell us how long ago organisms diverged, unlocking the secrets of organisms that may have similar convergent morphology but do not share a recent common ancestor. -
Comparison of Similarity Coefficients Used for Cluster Analysis with Dominant Markers in Maize (Zea Mays L)
Genetics and Molecular Biology, 27, 1, 83-91 (2004) Copyright by the Brazilian Society of Genetics. Printed in Brazil www.sbg.org.br Research Article Comparison of similarity coefficients used for cluster analysis with dominant markers in maize (Zea mays L) Andréia da Silva Meyer1, Antonio Augusto Franco Garcia2, Anete Pereira de Souza3 and Cláudio Lopes de Souza Jr.2 1Uscola Superior de Agricultura “Luiz de Queiroz”, Departamento de Ciências Exatas, Piracicaba, SP, Brazil. 2Escola Superior de Agricultura “Luiz de Queiroz”, Departamento de Genética, Piracicaba, SP, Brazil. 3Universidade Estadual de Campinas, Departamento de Genética e Evolução, Campinas, SP, Brazil. Abstract The objective of this study was to evaluate whether different similarity coefficients used with dominant markers can influence the results of cluster analysis, using eighteen inbred lines of maize from two different populations, BR-105 and BR-106. These were analyzed by AFLP and RAPD markers and eight similarity coefficients were calculated: Jaccard, Sorensen-Dice, Anderberg, Ochiai, Simple-matching, Rogers and Tanimoto, Ochiai II and Russel and Rao. The similarity matrices obtained were compared by the Spearman correlation, cluster analysis with dendrograms (UPGMA, WPGMA, Single Linkage, Complete Linkage and Neighbour-Joining methods), the consensus fork index between all pairs of dendrograms, groups obtained through the Tocher optimization procedure and projection efficiency in a two-dimensional space. The results showed that for almost all methodologies and marker systems, the Jaccard, Sorensen-Dice, Anderberg and Ochiai coefficient showed close results, due to the fact that all of them exclude negative co-occurrences. Significant alterations in the results for the Simple Matching, Rogers and Tanimoto, and Ochiai II coefficients were not observed either, probably due to the fact that they all include negative co-occurrences. -
Plant Evolution an Introduction to the History of Life
Plant Evolution An Introduction to the History of Life KARL J. NIKLAS The University of Chicago Press Chicago and London CONTENTS Preface vii Introduction 1 1 Origins and Early Events 29 2 The Invasion of Land and Air 93 3 Population Genetics, Adaptation, and Evolution 153 4 Development and Evolution 217 5 Speciation and Microevolution 271 6 Macroevolution 325 7 The Evolution of Multicellularity 377 8 Biophysics and Evolution 431 9 Ecology and Evolution 483 Glossary 537 Index 547 v Introduction The unpredictable and the predetermined unfold together to make everything the way it is. It’s how nature creates itself, on every scale, the snowflake and the snowstorm. — TOM STOPPARD, Arcadia, Act 1, Scene 4 (1993) Much has been written about evolution from the perspective of the history and biology of animals, but significantly less has been writ- ten about the evolutionary biology of plants. Zoocentricism in the biological literature is understandable to some extent because we are after all animals and not plants and because our self- interest is not entirely egotistical, since no biologist can deny the fact that animals have played significant and important roles as the actors on the stage of evolution come and go. The nearly romantic fascination with di- nosaurs and what caused their extinction is understandable, even though we should be equally fascinated with the monarchs of the Carboniferous, the tree lycopods and calamites, and with what caused their extinction (fig. 0.1). Yet, it must be understood that plants are as fascinating as animals, and that they are just as important to the study of biology in general and to understanding evolutionary theory in particular. -
An Introduction to Phylogenetic Analysis
This article reprinted from: Kosinski, R.J. 2006. An introduction to phylogenetic analysis. Pages 57-106, in Tested Studies for Laboratory Teaching, Volume 27 (M.A. O'Donnell, Editor). Proceedings of the 27th Workshop/Conference of the Association for Biology Laboratory Education (ABLE), 383 pages. Compilation copyright © 2006 by the Association for Biology Laboratory Education (ABLE) ISBN 1-890444-09-X All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the copyright owner. Use solely at one’s own institution with no intent for profit is excluded from the preceding copyright restriction, unless otherwise noted on the copyright notice of the individual chapter in this volume. Proper credit to this publication must be included in your laboratory outline for each use; a sample citation is given above. Upon obtaining permission or with the “sole use at one’s own institution” exclusion, ABLE strongly encourages individuals to use the exercises in this proceedings volume in their teaching program. Although the laboratory exercises in this proceedings volume have been tested and due consideration has been given to safety, individuals performing these exercises must assume all responsibilities for risk. The Association for Biology Laboratory Education (ABLE) disclaims any liability with regards to safety in connection with the use of the exercises in this volume. The focus of ABLE is to improve the undergraduate biology laboratory experience by promoting the development and dissemination of interesting, innovative, and reliable laboratory exercises. -
Phylogenetic Comparative Methods: a User's Guide for Paleontologists
Phylogenetic Comparative Methods: A User’s Guide for Paleontologists Laura C. Soul - Department of Paleobiology, National Museum of Natural History, Smithsonian Institution, Washington, DC, USA David F. Wright - Division of Paleontology, American Museum of Natural History, Central Park West at 79th Street, New York, New York 10024, USA and Department of Paleobiology, National Museum of Natural History, Smithsonian Institution, Washington, DC, USA Abstract. Recent advances in statistical approaches called Phylogenetic Comparative Methods (PCMs) have provided paleontologists with a powerful set of analytical tools for investigating evolutionary tempo and mode in fossil lineages. However, attempts to integrate PCMs with fossil data often present workers with practical challenges or unfamiliar literature. In this paper, we present guides to the theory behind, and application of, PCMs with fossil taxa. Based on an empirical dataset of Paleozoic crinoids, we present example analyses to illustrate common applications of PCMs to fossil data, including investigating patterns of correlated trait evolution, and macroevolutionary models of morphological change. We emphasize the importance of accounting for sources of uncertainty, and discuss how to evaluate model fit and adequacy. Finally, we discuss several promising methods for modelling heterogenous evolutionary dynamics with fossil phylogenies. Integrating phylogeny-based approaches with the fossil record provides a rigorous, quantitative perspective to understanding key patterns in the history of life. 1. Introduction A fundamental prediction of biological evolution is that a species will most commonly share many characteristics with lineages from which it has recently diverged, and fewer characteristics with lineages from which it diverged further in the past. This principle, which results from descent with modification, is one of the most basic in biology (Darwin 1859). -
Phylogeny Codon Models • Last Lecture: Poor Man’S Way of Calculating Dn/Ds (Ka/Ks) • Tabulate Synonymous/Non-Synonymous Substitutions • Normalize by the Possibilities
Phylogeny Codon models • Last lecture: poor man’s way of calculating dN/dS (Ka/Ks) • Tabulate synonymous/non-synonymous substitutions • Normalize by the possibilities • Transform to genetic distance KJC or Kk2p • In reality we use codon model • Amino acid substitution rates meet nucleotide models • Codon(nucleotide triplet) Codon model parameterization Stop codons are not allowed, reducing the matrix from 64x64 to 61x61 The entire codon matrix can be parameterized using: κ kappa, the transition/transversionratio ω omega, the dN/dS ratio – optimizing this parameter gives the an estimate of selection force πj the equilibrium codon frequency of codon j (Goldman and Yang. MBE 1994) Empirical codon substitution matrix Observations: Instantaneous rates of double nucleotide changes seem to be non-zero There should be a mechanism for mutating 2 adjacent nucleotides at once! (Kosiol and Goldman) • • Phylogeny • • Last lecture: Inferring distance from Phylogenetic trees given an alignment How to infer trees and distance distance How do we infer trees given an alignment • • Branch length Topology d 6-p E 6'B o F P Edo 3 vvi"oH!.- !fi*+nYolF r66HiH- .) Od-:oXP m a^--'*A ]9; E F: i ts X o Q I E itl Fl xo_-+,<Po r! UoaQrj*l.AP-^PA NJ o - +p-5 H .lXei:i'tH 'i,x+<ox;+x"'o 4 + = '" I = 9o FF^' ^X i! .poxHo dF*x€;. lqEgrE x< f <QrDGYa u5l =.ID * c 3 < 6+6_ y+ltl+5<->-^Hry ni F.O+O* E 3E E-f e= FaFO;o E rH y hl o < H ! E Y P /-)^\-B 91 X-6p-a' 6J. -
Family Classification
1.0 GENERAL INTRODUCTION 1.1 Henckelia sect. Loxocarpus Loxocarpus R.Br., a taxon characterised by flowers with two stamens and plagiocarpic (held at an angle of 90–135° with pedicel) capsular fruit that splits dorsally has been treated as a section within Henckelia Spreng. (Weber & Burtt, 1998 [1997]). Loxocarpus as a genus was established based on L. incanus (Brown, 1839). It is principally recognised by its conical, short capsule with a broader base often with a hump-like swelling at the upper side (Banka & Kiew, 2009). It was reduced to sectional level within the genus Didymocarpus (Bentham, 1876; Clarke, 1883; Ridley, 1896) but again raised to generic level several times by different authors (Ridley, 1905; Burtt, 1958). In 1998, Weber & Burtt (1998 ['1997']) re-modelled Didymocarpus. Didymocarpus s.s. was redefined to a natural group, while most of the rest Malesian Didymocarpus s.l. and a few others morphologically close genera including Loxocarpus were transferred to Henckelia within which it was recognised as a section within. See Section 4.1 for its full taxonomic history. Molecular data now suggests that Henckelia sect. Loxocarpus is nested within ‗Twisted-fruited Asian and Malesian genera‘ group and distinct from other didymocarpoid genera (Möller et al. 2009; 2011). 1.2 State of knowledge and problem statements Henckelia sect. Loxocarpus includes 10 species in Peninsular Malaysia (with one species extending into Peninsular Thailand), 12 in Borneo, two in Sumatra and one in Lingga (Banka & Kiew, 2009). The genus Loxocarpus has never been monographed. Peninsular Malaysian taxa are well studied (Ridley, 1923; Banka, 1996; Banka & Kiew, 2009) but the Bornean and Sumatran taxa are poorly known.