Characters and Parsimony Analysis Genetic Relationships
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Handout Lec. 25
Introduction to Biosystematics - Zool 575 Introduction to Biosystematics Confidence - Assessment of the Strength of Lecture 25 - Confidence - Assessment 2 the Phylogenetic Signal - part 2 1. Consistency Index 2. g1 statistic, PTP - test “Quantifying the uncertainty of a phylogenetic 3. Consensus trees estimate is at least as important a goal as obtaining the phylogenetic estimate itself.” 4. Decay index (Bremer Support) - Huelsenbeck & Rannala (2004) 5. Bootstrapping / Jackknifing 6. Statistical hypothesis testing (frequentist) 7. Posterior probability (see lecture on Bayesian) Derek S. Sikes University of Calgary Zool 575 Multiple optimal trees Multiple optimal trees • Many methods can yield multiple equally • If multiple optimal trees are found we know optimal trees that all of them are wrong except, possibly, (hopefully) one • We can further select among these trees with additional criteria, but • Some have argued against consensus tree methods for this reason • Typically, relationships common to all the optimal trees are summarized with • Debate over quest for true tree (point consensus trees estimate) versus quantification of uncertainty Consensus methods Strict consensus methods • A consensus tree is a summary of the agreement • Strict consensus methods require agreement among a set of fundamental trees across all the fundamental trees • There are many consensus methods that differ in: • They show only those relationships that are 1. the kind of agreement unambiguously supported by the data 2. the level of agreement • The commonest -
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 . -
Molecular Data and the Evolutionary History of Dinoflagellates by Juan Fernando Saldarriaga Echavarria Diplom, Ruprecht-Karls-Un
Molecular data and the evolutionary history of dinoflagellates by Juan Fernando Saldarriaga Echavarria Diplom, Ruprecht-Karls-Universitat Heidelberg, 1993 A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE STUDIES Department of Botany We accept this thesis as conforming to the required standard THE UNIVERSITY OF BRITISH COLUMBIA November 2003 © Juan Fernando Saldarriaga Echavarria, 2003 ABSTRACT New sequences of ribosomal and protein genes were combined with available morphological and paleontological data to produce a phylogenetic framework for dinoflagellates. The evolutionary history of some of the major morphological features of the group was then investigated in the light of that framework. Phylogenetic trees of dinoflagellates based on the small subunit ribosomal RNA gene (SSU) are generally poorly resolved but include many well- supported clades, and while combined analyses of SSU and LSU (large subunit ribosomal RNA) improve the support for several nodes, they are still generally unsatisfactory. Protein-gene based trees lack the degree of species representation necessary for meaningful in-group phylogenetic analyses, but do provide important insights to the phylogenetic position of dinoflagellates as a whole and on the identity of their close relatives. Molecular data agree with paleontology in suggesting an early evolutionary radiation of the group, but whereas paleontological data include only taxa with fossilizable cysts, the new data examined here establish that this radiation event included all dinokaryotic lineages, including athecate forms. Plastids were lost and replaced many times in dinoflagellates, a situation entirely unique for this group. Histones could well have been lost earlier in the lineage than previously assumed. -
Geotaxis in the Ciliated Protozoon Loxodes
J. exp. Biol. 110, 17-33 (1984) 17 d in Great Britain © The Company of Biologists Limited 1984 GEOTAXIS IN THE CILIATED PROTOZOON LOXODES BY T. FENCHEL Department of Ecology and Genetics, University ofAarhus, DK-8000 Aarhus, Denmark AND B. J. FINLAY Freshwater Biological Association, The Ferry House, Ambleside, Cumbria LA22 OLP, U.K. Accepted 14 November 1983 SUMMARY Geotaxis is demonstrated in the ciliated protozoon Loxodes. This behaviour is mediated by a mechanoreceptor which is probably the Muller body, an organelle characteristic of loxodid ciliates. The geotactic response is sensitive to dissolved oxygen tension: in anoxia or at very low O2 tensions the ciliates tend to swim up and at higher O2 tensions they tend to swim down. This behaviour, in conjunction with a kinetic response allows the ciliates to orientate themselves in vertical O2 gradients and to congregate in their optimum environment. In two appendices, models of the behaviour predicting vertical distribution patterns and considerations of the minimum size of a functional statocyst are offered. INTRODUCTION Many protozoa display a pronounced positive or negative geotaxis. The mechan- isms responsible for this have been the subject of a prolonged dispute (for references see Roberts, 1970). In the species studied so far, however, there is no evidence of mechanoreceptors. Rather, the geotactic behaviour can be explained as the result of the interactions between sinking velocity, swimming velocity, rate of random reorientation and the net result of gravitational and hydrodynamical forces. These tend passively to orientate the anterior end of the cells upwards. Through modulations of the swimming velocity and the rate of random reorientation, the cells can change their probability of moving upwards and hence their vertical distribution in the water column. -
Phylogenetics Topic 2: Phylogenetic and Genealogical Homology
Phylogenetics Topic 2: Phylogenetic and genealogical homology Phylogenies distinguish homology from similarity Previously, we examined how rooted phylogenies provide a framework for distinguishing similarity due to common ancestry (HOMOLOGY) from non-phylogenetic similarity (ANALOGY). Here we extend the concept of phylogenetic homology by making a further distinction between a HOMOLOGOUS CHARACTER and a HOMOLOGOUS CHARACTER STATE. This distinction is important to molecular evolution, as we often deal with data comprised of homologous characters with non-homologous character states. The figure below shows three hypothetical protein-coding nucleotide sequences (for simplicity, only three codons long) that are related to each other according to a phylogenetic tree. In the figure the nucleotide sequences are aligned to each other; in so doing we are making the implicit assumption that the characters aligned vertically are homologous characters. In the specific case of nucleotide and amino acid alignments this assumption is called POSITIONAL HOMOLOGY. Under positional homology it is implicit that a given position, say the first position in the gene sequence, was the same in the gene sequence of the common ancestor. In the figure below it is clear that some positions do not have identical character states (see red characters in figure below). In such a case the involved position is considered to be a homologous character, while the state of that character will be non-homologous where there are differences. Phylogenetic perspective on homologous characters and homologous character states ACG TAC TAA SYNAPOMORPHY: a shared derived character state in C two or more lineages. ACG TAT TAA These must be homologous in state. -
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. -
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. -
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. -
Interpreting Cladograms Notes
Interpreting Cladograms Notes INTERPRETING CLADOGRAMS BIG IDEA: PHYLOGENIES DEPICT ANCESTOR AND DESCENDENT RELATIONSHIPS AMONG ORGANISMS BASED ON HOMOLOGY THESE EVOLUTIONARY RELATIONSHIPS ARE REPRESENTED BY DIAGRAMS CALLED CLADOGRAMS (BRANCHING DIAGRAMS THAT ORGANIZE RELATIONSHIPS) What is a Cladogram ● A diagram which shows ● Is not an evolutionary ___________ among tree, ___________show organisms. how ancestors are related ● Lines branching off other to descendants or how lines. The lines can be much they have changed traced back to where they branch off. These branching off points represent a hypothetical ancestor. Parts of a Cladogram Reading Cladograms ● Read like a family tree: show ________of shared ancestry between lineages. • When an ancestral lineage______: speciation is indicated due to the “arrival” of some new trait. Each lineage has unique ____to itself alone and traits that are shared with other lineages. each lineage has _______that are unique to that lineage and ancestors that are shared with other lineages — common ancestors. Quick Question #1 ●What is a_________? ● A group that includes a common ancestor and all the descendants (living and extinct) of that ancestor. Reading Cladogram: Identifying Clades ● Using a cladogram, it is easy to tell if a group of lineages forms a clade. ● Imagine clipping a single branch off the phylogeny ● all of the organisms on that pruned branch make up a clade Quick Question #2 ● Looking at the image to the right: ● Is the green box a clade? ● The blue? ● The pink? ● The orange? Reading Cladograms: Clades ● Clades are nested within one another ● they form a nested hierarchy. ● A clade may include many thousands of species or just a few. -
Conceptual Issues in Phylogeny, Taxonomy, and Nomenclature
Contributions to Zoology, 66 (1) 3-41 (1996) SPB Academic Publishing bv, Amsterdam Conceptual issues in phylogeny, taxonomy, and nomenclature Alexandr P. Rasnitsyn Paleontological Institute, Russian Academy ofSciences, Profsoyuznaya Street 123, J17647 Moscow, Russia Keywords: Phylogeny, taxonomy, phenetics, cladistics, phylistics, principles of nomenclature, type concept, paleoentomology, Xyelidae (Vespida) Abstract On compare les trois approches taxonomiques principales développées jusqu’à présent, à savoir la phénétique, la cladis- tique et la phylistique (= systématique évolutionnaire). Ce Phylogenetic hypotheses are designed and tested (usually in dernier terme s’applique à une approche qui essaie de manière implicit form) on the basis ofa set ofpresumptions, that is, of à les traits fondamentaux de la taxonomic statements explicite représenter describing a certain order of things in nature. These traditionnelle en de leur et particulier son usage preuves ayant statements are to be accepted as such, no matter whatever source en même temps dans la similitude et dans les relations de evidence for them exists, but only in the absence ofreasonably parenté des taxons en question. L’approche phylistique pré- sound evidence pleading against them. A set ofthe most current sente certains avantages dans la recherche de réponses aux phylogenetic presumptions is discussed, and a factual example problèmes fondamentaux de la taxonomie. ofa practical realization of the approach is presented. L’auteur considère la nomenclature A is made of the three -
Biologia Celular – Cell Biology
Biologia Celular – Cell Biology BC001 - Structural Basis of the Interaction of a Trypanosoma cruzi Surface Molecule Implicated in Oral Infection with Host Cells and Gastric Mucin CORTEZ, C.*1; YOSHIDA, N.1; BAHIA, D.1; SOBREIRA, T.2 1.UNIFESP, SÃO PAULO, SP, BRASIL; 2.SINCROTRON, CAMPINAS, SP, BRASIL. e-mail:[email protected] Host cell invasion and dissemination within the host are hallmarks of virulence for many pathogenic microorganisms. As concerns Trypanosoma cruzi that causes Chagas disease, the insect vector-derived metacyclic trypomastigotes (MT) initiate infection by invading host cells, and later blood trypomastigotes disseminate to diverse organs and tissues. Studies with MT generated in vitro and tissue culture-derived trypomastigotes (TCT), as counterparts of insect- borne and bloodstream parasites, have implicated members of the gp85/trans-sialidase superfamily, MT gp82 and TCT Tc85-11, in cell invasion and interaction with host factors. Here we analyzed the gp82 structure/function characteristics and compared them with those previously reported for Tc85-11. One of the gp82 sequences identified as a cell binding site consisted of an alpha-helix, which connects the N-terminal beta-propeller domain to the C- terminal beta-sandwich domain where the second binding site is nested. In the gp82 structure model, both sites were exposed at the surface. Unlike gp82, the Tc85-11 cell adhesion sites are located in the N-terminal beta-propeller region. The gp82 sequence corresponding to the epitope for a monoclonal antibody that inhibits MT entry into target cells was exposed on the surface, upstream and contiguous to the alpha-helix. Located downstream and close to the alpha-helix was the gp82 gastric mucin binding site, which plays a central role in oral T. -
Consensus Methods Strict Consensus Methods
Systematics - Bio 615 Confidence - Assessment of the Strength of the Phylogenetic Signal - part 2 1. Consistency Index 2. g1 statistic, PTP - test 3. Consensus trees 4. Decay index (Bremer Support) 5. Bootstrapping / Jackknifing 6. Statistical hypothesis testing (frequentist) 7. Posterior probability (see lecture on Bayesian) Derek S. Sikes University of Alaska Multiple optimal trees Multiple optimal trees • Many methods can yield multiple equally • If multiple optimal trees are found we know optimal trees that all of them are wrong except, possibly, (hopefully) one (as species tree, not gene trees) • We can further select among these trees with additional criteria, but • Some have argued against consensus tree methods for this reason • Typically, relationships common to all the optimal trees are summarized with • Debate over quest for true tree (point consensus trees estimate) versus quantification of uncertainty Consensus methods Strict consensus methods • A consensus tree is a summary of the agreement • Strict consensus methods require agreement among a set of fundamental trees across all the fundamental trees • There are many consensus methods that differ in: • They show only those relationships that are 1. the kind of agreement unambiguously supported by the data 2. the level of agreement • The commonest method (strict component • Consensus methods can be used with multiple consensus) focuses on clades/components/full trees from a single analysis or from multiple splits analyses 1 Systematics - Bio 615 Strict consensus methods Strict