Reading Phylogenetic Trees: a Quick Review (Adapted from Evolution.Berkeley.Edu)
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Title Genomic Analysis of the Marine Hyperthermophilic Archaeon
Genomic analysis of the marine hyperthermophilic archaeon Title Aeropyrum( Digest_要約 ) Author(s) Daifuku, Takashi Citation 京都大学 Issue Date 2015-03-23 URL https://doi.org/10.14989/doctor.k19034 学位規則第9条第2項により要約公開; 許諾条件により本文 Right は2019-08-01に公開 Type Thesis or Dissertation Textversion ETD Kyoto University Summary The increasing number of genome sequences of archaea and bacteria leads to show their adaptation to different environmental conditions at the genomic level. Aeropyrum spp. are aerobic and hyperthermophilic archaea. A. camini was isolated from a deep-sea hydrothermal vent, and A. pernix was isolated from a coastal solfataric vent. In chapter 2, I compared the genomes of the two species to investigate the adaptation strategy in each habitat. Their shared genome features were a small genome size, a high GC content, and a large portion of orthologous genes (86 to 88%). The genomes also showed high synteny. These shared features may have been derived from the small number of mobile genetic elements and the lack of a RecBCD system, a recombinational enzyme complex. In addition, the specialized physiology (aerobic and hyperthermophilic) of Aeropyrum spp. may also contribute to the entire-genome similarity. Despite having stable genomes, interference of synteny occurred with two proviruses, A. pernix spindle-shaped virus 1 (APSV1) and A. pernix ovoid virus 1 (APOV1), and clustered regularly interspaced short palindromic repeat (CRISPR) elements. CRISPR spacer sequences observed in the A. camini showed significant matches with protospacers of the two proviruses found in the genome of A. pernix, indicating that A. camini interacted with viruses closely related to APSV1 and APOV1. Furthermore, a significant fraction of the nonorthologous genes (41 to 45%) were proviral genes or ORFans probably originating from viruses. -
Species Concepts Should Not Conflict with Evolutionary History, but Often Do
ARTICLE IN PRESS Stud. Hist. Phil. Biol. & Biomed. Sci. xxx (2008) xxx–xxx Contents lists available at ScienceDirect Stud. Hist. Phil. Biol. & Biomed. Sci. journal homepage: www.elsevier.com/locate/shpsc Species concepts should not conflict with evolutionary history, but often do Joel D. Velasco Department of Philosophy, University of Wisconsin-Madison, 5185 White Hall, 600 North Park St., Madison, WI 53719, USA Department of Philosophy, Building 90, Stanford University, Stanford, CA 94305, USA article info abstract Keywords: Many phylogenetic systematists have criticized the Biological Species Concept (BSC) because it distorts Biological Species Concept evolutionary history. While defences against this particular criticism have been attempted, I argue that Phylogenetic Species Concept these responses are unsuccessful. In addition, I argue that the source of this problem leads to previously Phylogenetic Trees unappreciated, and deeper, fatal objections. These objections to the BSC also straightforwardly apply to Taxonomy other species concepts that are not defined by genealogical history. What is missing from many previous discussions is the fact that the Tree of Life, which represents phylogenetic history, is independent of our choice of species concept. Some species concepts are consistent with species having unique positions on the Tree while others, including the BSC, are not. Since representing history is of primary importance in evolutionary biology, these problems lead to the conclusion that the BSC, along with many other species concepts, are unacceptable. If species are to be taxa used in phylogenetic inferences, we need a history- based species concept. Ó 2008 Elsevier Ltd. All rights reserved. When citing this paper, please use the full journal title Studies in History and Philosophy of Biological and Biomedical Sciences 1. -
Biological Diversity in the Patent System
Biological Diversity in the Patent System Paul Oldham1,2*, Stephen Hall1,3, Oscar Forero1,4 1 ESRC Centre for Economic and Social Aspects of Genomics (Cesagen), Lancaster University, Lancaster, United Kingdom, 2 Institute of Advanced Studies, United Nations University, Yokohama, Japan, 3 One World Analytics, Lancaster, United Kingdom, 4 Centre for Development, Environment and Policy, SOAS, University of London, London, United Kingdom Abstract Biological diversity in the patent system is an enduring focus of controversy but empirical analysis of the presence of biodiversity in the patent system has been limited. To address this problem we text mined 11 million patent documents for 6 million Latin species names from the Global Names Index (GNI) established by the Global Biodiversity Information Facility (GBIF) and Encyclopedia of Life (EOL). We identified 76,274 full Latin species names from 23,882 genera in 767,955 patent documents. 25,595 species appeared in the claims section of 136,880 patent documents. This reveals that human innovative activity involving biodiversity in the patent system focuses on approximately 4% of taxonomically described species and between 0.8–1% of predicted global species. In this article we identify the major features of the patent landscape for biological diversity by focusing on key areas including pharmaceuticals, neglected diseases, traditional medicines, genetic engineering, foods, biocides, marine genetic resources and Antarctica. We conclude that the narrow focus of human innovative activity and ownership of genetic resources is unlikely to be in the long term interest of humanity. We argue that a broader spectrum of biodiversity needs to be opened up to research and development based on the principles of equitable benefit-sharing, respect for the objectives of the Convention on Biological Diversity, human rights and ethics. -
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. -
Microbial Evolution and Diversity
PART V Microbial Evolution and Diversity This material cannot be copied, disseminated, or used in any way without the express written permission of the publisher. Copyright 2007 Sinauer Associates Inc. The objectives of this chapter are to: N Provide information on how bacteria are named and what is meant by a validly named species. N Discuss the classification of Bacteria and Archaea and the recent move toward an evolutionarily based, phylogenetic classification. N Describe the ways in which the Bacteria and Archaea are identified in the laboratory. This material cannot be copied, disseminated, or used in any way without the express written permission of the publisher. Copyright 2007 Sinauer Associates Inc. 17 Taxonomy of Bacteria and Archaea It’s just astounding to see how constant, how conserved, certain sequence motifs—proteins, genes—have been over enormous expanses of time. You can see sequence patterns that have per- sisted probably for over three billion years. That’s far longer than mountain ranges last, than continents retain their shape. —Carl Woese, 1997 (in Perry and Staley, Microbiology) his part of the book discusses the variety of microorganisms that exist on Earth and what is known about their characteris- Ttics and evolution. Most of the material pertains to the Bacteria and Archaea because there is a special chapter dedicated to eukaryotic microorganisms. Therefore, this first chapter discusses how the Bacte- ria and Archaea are named and classified and is followed by several chapters (Chapters 18–22) that discuss the properties and diversity of the Bacteria and Archaea. When scientists encounter a large number of related items—such as the chemical elements, plants, or animals—they characterize, name, and organize them into groups. -
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). -
Lineages, Splits and Divergence Challenge Whether the Terms Anagenesis and Cladogenesis Are Necessary
Biological Journal of the Linnean Society, 2015, , – . With 2 figures. Lineages, splits and divergence challenge whether the terms anagenesis and cladogenesis are necessary FELIX VAUX*, STEVEN A. TREWICK and MARY MORGAN-RICHARDS Ecology Group, Institute of Agriculture and Environment, Massey University, Palmerston North, New Zealand Received 3 June 2015; revised 22 July 2015; accepted for publication 22 July 2015 Using the framework of evolutionary lineages to separate the process of evolution and classification of species, we observe that ‘anagenesis’ and ‘cladogenesis’ are unnecessary terms. The terms have changed significantly in meaning over time, and current usage is inconsistent and vague across many different disciplines. The most popular definition of cladogenesis is the splitting of evolutionary lineages (cessation of gene flow), whereas anagenesis is evolutionary change between splits. Cladogenesis (and lineage-splitting) is also regularly made synonymous with speciation. This definition is misleading as lineage-splitting is prolific during evolution and because palaeontological studies provide no direct estimate of gene flow. The terms also fail to incorporate speciation without being arbitrary or relative, and the focus upon lineage-splitting ignores the importance of divergence, hybridization, extinction and informative value (i.e. what is helpful to describe as a taxon) for species classification. We conclude and demonstrate that evolution and species diversity can be considered with greater clarity using simpler, more transparent terms than anagenesis and cladogenesis. Describing evolution and taxonomic classification can be straightforward, and there is no need to ‘make words mean so many different things’. © 2015 The Linnean Society of London, Biological Journal of the Linnean Society, 2015, 00, 000–000. -
Statistical Inference for the Linguistic and Non-Linguistic Past
Statistical inference for the linguistic and non-linguistic past Igor Yanovich DFG Center for Advanced Study “Words, Bones, Genes and Tools” Universität Tübingen July 6, 2017 Igor Yanovich 1 / 46 Overview of the course Overview of the course 1 Today: trees, as a description and as a process 2 Classes 2-3: simple inference of language-family trees 3 Classes 4-5: computational statistical inference of trees and evolutionary parameters 4 Class 6: histories of languages and of genes 5 Class 7: simple spatial statistics 6 Class 8: regression taking into account linguistic relationships; synthesis of the course Igor Yanovich 2 / 46 Overview of the course Learning outcomes By the end of the course, you should be able to: 1 read and engage with the current literature in linguistic phylogenetics and in spatial statistics for linguistics 2 run phylogenetic and basic spatial analyses on linguistic data 3 proceed further in the subject matter on your own, towards further advances in the field Igor Yanovich 3 / 46 Overview of the course Today’s class 1 Overview of the course 2 Language families and their structures 3 Trees as classifications and as process depictions 4 Linguistic phylogenetics 5 Worries about phylogenetics in linguistics vs. biology 6 Quick overview of the homework 7 Summary of Class 1 Igor Yanovich 4 / 46 Language families and their structures Language families and their structures Igor Yanovich 5 / 46 Language families and their structures Dravidian A modification of [Krishnamurti, 2003, Map 1.1], from Wikipedia Igor Yanovich 6 / 46 Language families and their structures Dravidian [Krishnamurti, 2003]’s classification: Dravidian family South Dravidian Central Dravidian North Dravidian SD I SD II Tamil Malay¯al.am Kannad.a Telugu Kolami Brahui (70M) (38M) (40M) (75M) (0.1M) (4M) (Numbers of speakers from Wikipedia) Igor Yanovich 7 / 46 Language families and their structures Dravidian: similarities and differences Proto-Dr. -
Minimising Branch Crossings in Phylogenetic Trees Sung-Hyuk Cha
22 Int. J. Applied Pattern Recognition, Vol. 3, No. 1, 2016 Minimising branch crossings in phylogenetic trees Sung-Hyuk Cha* Department of Computer Science, Pace University, New York, NY, USA Email: [email protected] *Corresponding author Yoo Jung An Engineering Technologies and Computer Sciences, Essex County College, Newark, NJ, USA Email: [email protected] Abstract: While phylogenetic trees are widely used in bioinformatics, one of the major problems is that different dendrograms may be constructed depending on several factors. Albeit numerous quantitative measures to compare two different phylogenetic trees have been proposed, visual comparison is often necessary. Displaying a pair of alternative phylogenetic trees together by finding a proper order of taxa in the leaf level was considered earlier to give better visual insights of how two dendrograms are similar. This approach raised a problem of branch crossing. Here, a couple of efficient methods to count the number of branch crossings in the trees for a given taxa order are presented. Using the number of branch crossings as a fitness function, genetic algorithms are used to find a taxa order such that two alternative phylogenetic trees can be shown with semi-minimal number of branch crossing. A couple of methods to encode/decode a taxa order to/from a chromosome where genetic operators can be applied are also given. Keywords: clustering; dendrogram; hierarchical clustering; phylogenetic tree; visualisation. Reference to this paper should be made as follows: Cha, S-H. and An, Y.J. (2016) ‘Minimising branch crossings in phylogenetic trees’, Int. J. Applied Pattern Recognition, Vol. 3, No. 1, pp.22–37. -
Archaeal Viruses and Bacteriophages: Comparisons and Contrasts
Review Archaeal viruses and bacteriophages: comparisons and contrasts Maija K. Pietila¨ , Tatiana A. Demina, Nina S. Atanasova, Hanna M. Oksanen, and Dennis H. Bamford Institute of Biotechnology and Department of Biosciences, P.O. Box 56, Viikinkaari 5, 00014 University of Helsinki, Helsinki, Finland Isolated archaeal viruses comprise only a few percent of Euryarchaeaota [9,10]. Archaea have also been cultivated all known prokaryotic viruses. Thus, the study of viruses from moderate environments such as seawater and soil. infecting archaea is still in its early stages. Here we Consequently, an additional phylum, Thaumarchaeota, summarize the most recent discoveries of archaeal vi- has been formed to contain mesophilic and thermophilic ruses utilizing a virion-centered view. We describe the ammonia-oxidizing archaea [11]. However, all known ar- known archaeal virion morphotypes and compare them chaeal viruses infect extremophiles – mainly hyperther- to the bacterial counterparts, if such exist. Viruses infect- mophiles belonging to the crenarchaeal genera Sulfolobus ing archaea are morphologically diverse and present and Acidianus or halophiles of the euryarchaeal genera some unique morphotypes. Although limited in isolate Haloarcula, Halorubrum, and Halobacterium [6,7]. Even number, archaeal viruses reveal new insights into the though bacteria are also found in diverse extreme habitats viral world, such as deep evolutionary relationships such as hypersaline lakes, archaea typically dominate at between viruses that infect hosts from all three domains extreme salinities, based on both cultivation-dependent of life. and -independent studies [6,12–15]. Consequently, archae- al viruses do the same in hypersaline environments. About Discovery of archaeal viruses 50 prokaryotic haloviruses were recently isolated from All cellular organisms are susceptible to viral infections, nine globally distant locations, and only four of them which makes viruses a major evolutionary force shaping infected bacteria [6,16]. -
Differences in Lateral Gene Transfer in Hypersaline Versus Thermal Environments Matthew E Rhodes1*, John R Spear2, Aharon Oren3 and Christopher H House1
Rhodes et al. BMC Evolutionary Biology 2011, 11:199 http://www.biomedcentral.com/1471-2148/11/199 RESEARCH ARTICLE Open Access Differences in lateral gene transfer in hypersaline versus thermal environments Matthew E Rhodes1*, John R Spear2, Aharon Oren3 and Christopher H House1 Abstract Background: The role of lateral gene transfer (LGT) in the evolution of microorganisms is only beginning to be understood. While most LGT events occur between closely related individuals, inter-phylum and inter-domain LGT events are not uncommon. These distant transfer events offer potentially greater fitness advantages and it is for this reason that these “long distance” LGT events may have significantly impacted the evolution of microbes. One mechanism driving distant LGT events is microbial transformation. Theoretically, transformative events can occur between any two species provided that the DNA of one enters the habitat of the other. Two categories of microorganisms that are well-known for LGT are the thermophiles and halophiles. Results: We identified potential inter-class LGT events into both a thermophilic class of Archaea (Thermoprotei) and a halophilic class of Archaea (Halobacteria). We then categorized these LGT genes as originating in thermophiles and halophiles respectively. While more than 68% of transfer events into Thermoprotei taxa originated in other thermophiles, less than 11% of transfer events into Halobacteria taxa originated in other halophiles. Conclusions: Our results suggest that there is a fundamental difference between LGT in thermophiles and halophiles. We theorize that the difference lies in the different natures of the environments. While DNA degrades rapidly in thermal environments due to temperature-driven denaturization, hypersaline environments are adept at preserving DNA. -
Learning the “Game” of Life: Reconstruction of Cell Lineages Through Crispr-Induced Dna Mutations
LEARNING THE “GAME” OF LIFE: RECONSTRUCTION OF CELL LINEAGES THROUGH CRISPR-INDUCED DNA MUTATIONS JIAXIAO CAI, DA KUANG, ARUN KIRUBARAJAN, MUKUND VENKATESWARAN ABSTRACT. Multi-cellular organisms are composed of many billions of individuals cells that exist by the mutation of a single stem cell. The CRISPR-based molecular-tools induce DNA mutations, which allows us to study the mutation lineages of various multi-ceulluar organisms. However, to date no lineage reconstruction algorithms have been examined for their performance/robustness across various molecular tools, datasets and sizes of lineage trees. In addition, it is unclear whether classical machine learning algorithms, deep neural networks or some combination of the two are the best approach for this task. In this paper, we introduce 1) a simulation framework for the zygote development process to achieve a dataset size required by deep learning models, and 2) various supervised and unsupervised approaches for cell mutation tree reconstruction. In particular, we show how deep generative models (Autoencoders and Variational Autoencoders), unsupervised clustering methods (K-means), and classical tree reconstruction algorithms (UPGMA) can all be used to trace cell mutation lineages. 1. INTRODUCTION Multi-cellular organisms are composed of billions or trillions of different interconnected cells that derive from a single cell through repeated rounds of cell division — knowing the cell lineage that produces a fully developed organism from a single cell provides the framework for understanding when, where, and how cell fate decisions are made. The recent advent of new CRISPR-based molecular tools synthetically induced DNA mutations and made it possible to solve lineage of complex model organisms at single-cell resolution.[1] Starting in early embryogenesis, CRISPR-induced mutations occur stochastically at introduced target sites, and these mutations are stably inherited by the offspring of these cells and immune to further change.