Activity: Constructing a Phylogeny by Dana Krempels and Julian Lee
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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). -
Phylogenetic Analysis
BIOL 101L: Principles of Biology Lab Classification & Phylogeny Humans classify almost everything, including each other. This habit can be quite useful. For example, when talking about a car someone might describe it as a 4-door sedan with a fuel injected V-8 engine. A knowledgeable listener who has not seen the car will still have a good idea of what it is like because of certain characteristics it shares with other familiar cars. Humans have been classifying plants and animals for a lot longer than they have been classifying cars, but the principle is much the same. In fact, one of the central problems in biology is the classification of organisms on the basis of shared characteristics. As an example, biologists classify all organisms with a backbone as "vertebrates." In this case the backbone is a characteristic that defines the group. If, in addition to a backbone, an organism has gills and fins it is a fish, a subcategory of the vertebrates. This fish can be further assigned to smaller and smaller categories down to the level of the species. The classification of organisms in this way aids the biologist by bringing order to what would otherwise be a bewildering diversity of species. (There are probably several million species - of which about one million have been named and classified.) The field devoted to the classification of organisms is called taxonomy [Gk. taxis, arrange, put in order + nomos, law]. The modern taxonomic system was devised by Carolus Linnaeus (1707-1778). It is a hierarchical system since organisms are grouped into ever more inclusive categories from species up to kingdom. -
Constructing a Phylogenetic Tree (Cladogram) K.L
Constructing a Phylogenetic Tree (Cladogram) K.L. Wennstrom, Shoreline Community College Biologists use phylogenetic trees to express the evolutionary relationships among groups of organisms. Such trees are constructed by comparing the anatomical structures, embryology, and genetic sequences of different species. Species that are more similar to one another are interpreted as being more closely related to one another. Before you continue, you should carefully read BioSkills 2, “Reading a Phylogenetic Tree” in your textbook. The BioSkills units can be found at the back of the book. BioSkills 2 begins on page B-3. Steps in creating a phylogenetic tree 1. Obtain a list of characters for the species you are interested in comparing. 2. Construct a character table or Venn diagram that illustrates which characters the groups have in common. a. In a character table, the columns represent characters, beginning with the most common and ending with the least common. The rows represent organisms, beginning with the organism with the fewest derived characters and ending with the organism with the most derived characters. Place an X in the boxes in the table to represent which characters are present in each organism. b. In a Venn diagram, the circles represent the characters, and the contents of each circle represent the organisms that have those characters. Organism Characters Rose Leaves, flowers, thorns Grass Leaves Daisy Leaves, flowers Character Table Venn Diagram leaves thorns flowers Grass X Daisy X X Rose X X X 3. Using the information in your character table or Venn diagram, construct a cladogram that represents the relationship of the organisms through evolutionary time. -
Reading Phylogenetic Trees: a Quick Review (Adapted from Evolution.Berkeley.Edu)
Biological Trees Gloria Rendon SC11 Education June, 2011 Biological trees • Biological trees are used for the purpose of classification, i.e. grouping and categorization of organisms by biological type such as genus or species. Types of Biological trees • Taxonomy trees, like the one hosted at NCBI, are hierarchies; thus classification is determined by position or rank within the hierarchy. It goes from kingdom to species. • Phylogenetic trees represent evolutionary relationships, or genealogy, among species. Nowadays, these trees are usually constructed by comparing 16s/18s ribosomal RNA. • Gene trees represent evolutionary relationships of a particular biological molecule (gene or protein product) among species. They may or may not match the species genealogy. Examples: hemoglobin tree, kinase tree, etc. TAXONOMY TREES Exercise 1: Exploring the Species Tree at NCBI •There exist many taxonomies. •In this exercise, we will examine the taxonomy at NCBI. •NCBI has a taxonomy database where each category in the tree (from the root to the species level) has a unique identifier called taxid. •The lineage of a species is the full path you take in that tree from the root to the point where that species is located. •The (NCBI) taxonomy common tree is therefore the tree that results from adding together the full lineages of each species in a particular list of your choice. Exercise 1: Exploring the Species Tree at NCBI • Open a web browser on NCBI’s Taxonomy page http://www.ncbi.nlm.n ih.gov/Taxonomy/ • Click on each one of the names here to look up the taxonomy id (taxid) of each one of the five categories of the taxonomy browser: Archaea, bacteria, Eukaryotes, Viroids and Viruses. -
Molecular Evolution and Phylogenetic Tree Reconstruction
1 4 Molecular Evolution and 3 2 5 Phylogenetic Tree Reconstruction 1 4 2 3 5 Orthology, Paralogy, Inparalogs, Outparalogs Phylogenetic Trees • Nodes: species • Edges: time of independent evolution • Edge length represents evolution time § AKA genetic distance § Not necessarily chronological time Inferring Phylogenetic Trees Trees can be inferred by several criteria: § Morphology of the organisms • Can lead to mistakes § Sequence comparison Example: Mouse: ACAGTGACGCCCCAAACGT Rat: ACAGTGACGCTACAAACGT Baboon: CCTGTGACGTAACAAACGA Chimp: CCTGTGACGTAGCAAACGA Human: CCTGTGACGTAGCAAACGA Distance Between Two Sequences Basic principle: • Distance proportional to degree of independent sequence evolution Given sequences xi, xj, dij = distance between the two sequences One possible definition: i j dij = fraction f of sites u where x [u] ≠ x [u] Better scores are derived by modeling evolution as a continuous change process Molecular Evolution Modeling sequence substitution: Consider what happens at a position for time Δt, • P(t) = vector of probabilities of {A,C,G,T} at time t • µAC = rate of transition from A to C per unit time • µA = µAC + µAG + µAT rate of transition out of A • pA(t+Δt) = pA(t) – pA(t) µA Δt + pC(t) µCA Δt + pG(t) µGA Δt + pT(t) µTA Δt Molecular Evolution In matrix/vector notation, we get P(t+Δt) = P(t) + Q P(t) Δt where Q is the substitution rate matrix Molecular Evolution • This is a differential equation: P’(t) = Q P(t) • Q => prob. distribution over {A,C,G,T} at each position, stationary (equilibrium) frequencies πA, πC, πG, -
Introduction to Phylogenetic Comparative Methods in R Pável Matos October 17, 2019
Introduction to phylogenetic comparative methods in R Pável Matos October 17, 2019 This is a tutorial that captures the essence of comparative methods using phylogenies. We will use both simulated and real-world data, along with basic statistics implemented in R packages. The lecture is divided in three sections: 1) Handling and visualizing phylogenies and species traits data in the R environment; 2) Understanding the principles of Brownian motion and its use in evolutionary correlations among species traits; 3) Working with phylogenetically independent contrasts (PIC) and phylogenetic generalized least squares regression (PGLS) using R. Package installations This tutorial was created using R v.3.6.1. You can download the latest R version from the CRAN site. We require two of the most popular phylogenetic R packages: ape and phytools: • ape is an essential R package for handling phylogenetic trees and running analyses of comparative data, including ancestral state reconstruction, diversification rate analyses, and DNA distance computation. • phytools is also handy for manipulating phylogenetic trees and includes other comparative methods and functions not available in ape. We begin this tutorial by installing them: if(!require(ape))install.packages("ape") if(!require(phytools))install.packages("phytools") # the nlme package will allow us to fit Gaussian linear mixed-effects model if(!require(phytools))install.packages("nlme") # the dplyr package will help us to handle data tables if(!require(phytools))install.packages("dplyr") And loading the phylogenetic R packages into our R working space: library(ape) library(phytools) library(nlme) Other important phylogenetic packages include phylobase (manipulating trees and comparative data), geiger (methods for fitting evolutionary models to phylogneies), and caper (phylogenetic comparative analyses). -
Assessing Phylogenetic Accuracy
Assessing Phylogenetic Accuracy A simulation study Theodoor Heijerman CENTRALE LANDBOUW CATALO GU S 0000067 0060 9 Promotor: Dr R. J. Post, hoogleraar in de diertaxonomie fiuoft-iof, \*iQy Assessing Phylogenetic Accuracy A simulation study Theodoor Heijerman Proefschrift ter verkrijging van de graad van doctor in de landbouw- en milieuwetenschappen op gezag van de rector magnificus, dr C. M. Karssen, in het openbaar te verdedigen op woensdag 27 september 1995 des namiddags te vier uur in de Aula van de Landbouwuniversiteit te Wageningen 0 SVI a1 (H>^ LA2\!ï>(JüL",VLK'V;:F.>i^lïiT YY*/.-::^- i-'.N CIP-GEGEVENS KONINKLIJKE BIBLIOTHEEK, DEN HAAG Heijerman, Theodoor Assessing phylogenetic accuracy : a simulation study / Theodoor Heijerman. - [S.I. : s.n.] (Wageningen : Ponsen & Looijen) Thesis Landbouw Universiteit Wageningen. - With réf. - With summary in Dutch. ISBN 90-5485-422-7 Subject headings: phylogenesis / animal taxonomy. Cover: 'n kroezen boom Stellingen Het getuigt van te veel optimisme ten aanzien van het prestatievermogen van numeriek taxonomische methoden, wanneer deze worden aangeduid als fylogenie-reconstructie-methoden. (dit proefschrift; F. J. Rohlf & M. C. Wooten, 1988. Evaluation of the restricted maximum-likelihood method for estimating phylogenetic trees using simulated allele-frequency data. — Evolution 42: 581-595). Het beschikbaar komen van steeds gebruikersvriendelijker programma's voor cladistische analyses, zal de gemiddelde kwaliteit van de resultaten van deze programma's doen afnemen. Het is sterk aan te bevelen om bij de presentatie van de resultaten van een cladistische analyse, niet alleen de meest parsimone, maar ook sub-optimale oplossingen te geven. De toepassing van fenetische technieken om verwantschapsrelaties te bepalen, is ten onrechte in onbruik geraakt. -
Computational Methods for Phylogenetic Analysis
Computational Methods for Phylogenetic Analysis Student: Mohd Abdul Hai Zahid Supervisors: Dr. R. C. Joshi and Dr. Ankush Mittal Phylogenetics is the study of relationship among species or genes with the combination of molecular biology and mathematics. Most of the present phy- logenetic analysis softwares and algorithms have limitations of low accuracy, restricting assumptions on size of the dataset, high time complexity, complex results which are difficult to interpret and several others which inhibits their widespread use by the researchers. In this work, we address several problems of phylogenetic analysis and propose better methods addressing prominent issues. It is well known that the network representation of the evolutionary rela- tionship provides a better understanding of the evolutionary process and the non-tree like events such as horizontal gene transfer, hybridization, recom- bination and homoplasy. A pattern recognition based sequence alignment algorithm is proposed which not only employs the similarity of SNP sites, as is generally done, but also the dissimilarity for the classification of the nodes into mutation and recombination nodes. Unlike the existing algo- rithms [1, 2, 3, 4, 5, 6], the proposed algorithm [7] conducts a row-based search to detect the recombination nodes. The existing algorithms search the columns for the detection of recombination. The number of columns 1 in a sequence may be far greater than the rows, which results in increased complexity of the previous algorithms. Most of the individual researchers and research teams are concentrating on the evolutionary pathways of specific phylogenetic groups. Many effi- cient phylogenetic reconstruction methods, such as Maximum Parsimony [8] and Maximum Likelihood [9], are available. -
A Phylogenetic Analysis of the Caminalcules. I
Society of Systematic Biologists A Phylogenetic Analysis of the Caminalcules. I. The Data Base Author(s): Robert R. Sokal Source: Systematic Zoology, Vol. 32, No. 2 (Jun., 1983), pp. 159-184 Published by: Taylor & Francis, Ltd. for the Society of Systematic Biologists Stable URL: http://www.jstor.org/stable/2413279 . Accessed: 26/01/2015 14:41 Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at . http://www.jstor.org/page/info/about/policies/terms.jsp . JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact [email protected]. Taylor & Francis, Ltd. and Society of Systematic Biologists are collaborating with JSTOR to digitize, preserve and extend access to Systematic Zoology. http://www.jstor.org This content downloaded from 129.101.61.40 on Mon, 26 Jan 2015 14:41:44 PM All use subject to JSTOR Terms and Conditions Syst.Zool., 32(2):159-184, 1983 A PHYLOGENETIC ANALYSIS OF THE CAMINALCULES. L. THE DATA BASE ROBERT R. SOKAL Departmentof Ecologyand Evolution,State Universityof New Yorkat StonyBrook, StonyBrook, New York 11794 Abstract.-The Caminalcules are a group of "organisms" generated artificiallyaccording to principles believed to resemble those operating in real organisms. A reanalysis of an earlier data matrixof the Caminalcules revealed some inconsistencies and errorswhich necessitated recoding of some characters.The resultingdifferences with earlier resultsare minor.The images of all 77 Caminalcules are featured,those of the 48 fossilspecies forthe firsttime. -
Phylogenetic Comparative Methods
Phylogenetic Comparative Methods Luke J. Harmon 2019-3-15 1 Copyright This is book version 1.4, released 15 March 2019. This book is released under a CC-BY-4.0 license. Anyone is free to share and adapt this work with attribution. ISBN-13: 978-1719584463 2 Acknowledgements Thanks to my lab for inspiring me, my family for being my people, and to the students for always keeping us on our toes. Helpful comments on this book came from many sources, including Arne Moo- ers, Brian O’Meara, Mike Whitlock, Matt Pennell, Rosana Zenil-Ferguson, Bob Thacker, Chelsea Specht, Bob Week, Dave Tank, and dozens of others. Thanks to all. Later editions benefited from feedback from many readers, including Liam Rev- ell, Ole Seehausen, Dean Adams and lab, and many others. Thanks! Keep it coming. If you like my publishing model try it yourself. The book barons are rich enough, anyway. Except where otherwise noted, this book is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit https: //creativecommons.org/licenses/by/4.0/. 3 Table of contents Chapter 1 - A Macroevolutionary Research Program Chapter 2 - Fitting Statistical Models to Data Chapter 3 - Introduction to Brownian Motion Chapter 4 - Fitting Brownian Motion Chapter 5 - Multivariate Brownian Motion Chapter 6 - Beyond Brownian Motion Chapter 7 - Models of discrete character evolution Chapter 8 - Fitting models of discrete character evolution Chapter 9 - Beyond the Mk model Chapter 10 - Introduction to birth-death models Chapter 11 - Fitting birth-death models Chapter 12 - Beyond birth-death models Chapter 13 - Characters and diversification rates Chapter 14 - Summary 4 Chapter 1: A Macroevolutionary Research Pro- gram Section 1.1: Introduction Evolution is happening all around us. -
Lecture 11: Phylogenetic Tree Inference: Introduction Evolution
Evolution: inheritance and mutation COSC 348: Computing for Bioinformatics • Organisms (animals or plants) produce a number of offspring which are almost, but not entirely, Lecture 11: like themselves: – Variation is due to sexual Phylogenetic tree inference: introduction reproduction (offspring have some characteristics from each parent, alleles from 2 parents Lubica Benuskova combine randomly) Prepared according to the notes of Dr. Richard O’Keefe – In addition, variation is due to mutation (random changes) in the fertilised egg. http://www.cs.otago.ac.nz/cosc348/ 1 2 Evolution: natural selection Mutations drive evolution • If a mutation happens in the DNA of a fertilised • Some of these offspring survive egg, then all the cells of an offspring carry this to produce offspring of their mutation because this mutation is replicated by DNA replication during cell division. own—some won’t: – The offspring with bigger • If that offspring survives, every offspring of his fitness are more likely to own will carry the same mutation. That’s how survive and reproduce mutations are preserved over evolution. – Over time, later generations become better and better • Mutations that result in an improved trait, drive evolution. adapted to a given – E.g., bigger claws, better eyesight, opposing environment because only the thumb, bigger brains, etc. fittest individuals have a higher chance to survive and Charles Darwin • Mutations that accumulate over time lead to reproduce. appearance of new species through intermediate 4 3 forms. What is a phylogeny? Basic terms from dictionary • A phylogeny is a tree showing • Taxonomy: The classification of items in an ordered system ancestor/descendant relationships that indicates natural relationships. -
Phylogeny and the Tree of Life 537 That Pines and firs Are Different Enough to Be Placed in Sepa- History
how do biologists distinguish and categorize the millions of species on Earth? An understanding of evolutionary relationships suggests 26 one way to address these questions: We can decide in which “container” to place a species by comparing its traits with those of potential close relatives. For example, the scaly-foot does not have a fused eyelid, a highly mobile jaw, or a short tail posterior to the anus, three traits shared by all snakes. Phylogeny and These and other characteristics suggest that despite a superfi- cial resemblance, the scaly-foot is not a snake. Furthermore, a the Tree of Life survey of the lizards reveals that the scaly-foot is not alone; the legless condition has evolved independently in several different groups of lizards. Most legless lizards are burrowers or live in grasslands, and like snakes, these species lost their legs over generations as they adapted to their environments. Snakes and lizards are part of the continuum of life ex- tending from the earliest organisms to the great variety of species alive today. In this unit, we will survey this diversity and describe hypotheses regarding how it evolved. As we do so, our emphasis will shift from the process of evolution (the evolutionary mechanisms described in Unit Four) to its pattern (observations of evolution’s products over time). To set the stage for surveying life’s diversity, in this chapter we consider how biologists trace phylogeny, the evolution- ary history of a species or group of species. A phylogeny of lizards and snakes, for example, indicates that both the scaly- foot and snakes evolved from lizards with legs—but that they evolved from different lineages of legged lizards.