DOCSLIB.ORG

Chapter 5 Genome Sequences and Evolution

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Chapter 5 Genome Sequences and Evolution © Jones & Bartlett Learning LLC, an Ascend Learning Company. NOT FOR SALE OR DISTRIBUTION. CHAPTER 5 © Jones & Bartlett Learning, LLC © Jones & Bartlett Learning, LLC NOT FOR SALE OR DISTRIBUTION NOT FOR SALE OR DISTRIBUTION © Jones & Bartlett Learning, LLC © Jones & Bartlett Learning, LLC NOT FOR SALE OR DISTRIBUTION NOT FOR SALE OR DISTRIBUTION © Jones & Bartlett Learning, LLC © Jones & Bartlett Learning, LLC NOT FOR SALE OR DISTRIBUTION NOT FOR SALE OR DISTRIBUTION © Jones & Bartlett Learning, LLC © Jones & Bartlett Learning, LLC NOT FOR SALE OR DISTRIBUTION NOT FOR SALE OR DISTRIBUTION Genome Sequences © Jones & Bartlett Learning, LLC © Jones & Bartlett Learning, LLC and ENOTvolu FOR SALEtion OR DISTRIBUTION NOT FOR SALE OR DISTRIBUTION CHAPTER OUTLINE © Jones & Bartlett Learning, LLC © Jones & Bartlett Learning, LLC 5.1 Introduction 5.13 A Constant Rate of Sequence Divergence Is NOT FOR SALE OR DISTRIBUTION NOT FOR SALE OR DISTRIBUTION 5.2 Prokaryotic Gene Numbers Range Over an a Molecular Clock Order of Magnitude 5.14 The Rate of Neutral Substitution Can Be 5.3 Total Gene Number Is Known for Several Measured from Divergence of Repeated Eukaryotes Sequences © Jones &5.4 Bartlett How Many Learning, Different LLC Types of Genes Are © Jones5.15 &How Bartlett Did Interrupted Learning, Genes LLC Evolve? NOT FOR SALEThere? OR DISTRIBUTION NOT 5.16FOR Why SALE Are OR Some DISTRIBUTION Genomes So Large? 5.5 The Human Genome Has Fewer Genes Than 5.17 Morphological Complexity Evolves by Originally Expected Adding New Gene Functions 5.6 How Are Genes and Other Sequences 5.18 Gene Duplication Contributes to Genome Distributed in ©the Jones Genome? & Bartlett Learning, LLC Evolution © Jones & Bartlett Learning, LLC 5.7 The Y ChromosomeNOT HasFOR Several SALE OR DISTRIBUTION5.19 Globin Clusters AriseNOT by DuplicationFOR SALE and OR DISTRIBUTION Male-Specific Genes Divergence 5.8 How Many Genes Are Essential? 5.20 Pseudogenes Have Lost Their Original 5.9 About 10,000 Genes Are Expressed at Functions ©Widely Jones Differing & Bartlett Levels Learning, in a Eukaryotic LLC Cell 5.21 Genome© Jones Duplication & Bartlett Has PlaLearning,yed a Role LLC in 5.10 NOTExpressed FOR SALEGene Number OR DISTRIBUTION Can Be Measured PlantNOT and FOR Vertebrate SALE Evolution OR DISTRIBUTION En Masse 5.22 What Is The Role of Transposable Elements 5.11 DNA Sequences Evolve by Mutation and a in Genome Evolution? Sorting Mechanism 5.23 There May Be Biases in Mutation, Gene © Jones &5.12 Bartlett Selection Learning, Can Be DetectLLC ed by Measuring © Jones &Conversion, Bartlett Learning, and Codon LLCUsage NOT FOR SALESequence OR DISTRIBUTION Variation NOT FOR SALE OR DISTRIBUTION Top texture: © Laguna Design / Science Source; Chapter Opener: Image courtesy of U.S. Department of Energy. Used with permission of Lisa J. Stubbs, University of Illinois at Urbana-Champaign. 101 9781284104646_CH05_101_142.indd 101 01/02/17 5:03 PM © Jones & Bartlett Learning LLC, an Ascend Learning Company. NOT FOR SALE OR DISTRIBUTION. 5.1 Introduction 500 genes © Jones Since& Bartlett the first completeLearning, organismal LLC genomes were sequenced© Jones & BartlettIntracellular Learning,(parasitic) LLC NOT FORin SALE 1995, both OR the DISTRIBUTION speed and range of sequencing have greatlyNOT FOR SALEbacterium OR DISTRIBUTION improved. The first genomes to be sequenced were small bacterial genomes of less than 2 megabase (Mb) in size. By 2002, the human genome of about 3,200 Mb had been sequenced. Genomes have now been sequenced from a wide 1,500 genes range of organisms, including© Jones bacteria, & archaeans,Bartlett yeasts,Learning, and LLC Free-living bacterium © Jones & Bartlett Learning, LLC other unicellular eukaryotes,NOT plants,FOR andSALE animals, OR including DISTRIBUTION NOT FOR SALE OR DISTRIBUTION worms, flies, and mammals. Perhaps the single most important piece of information provided by a genome sequence is the number of genes. (See 5,000 genes the chapter titled The Content of the Genome for a discussion Unicellular eukaryote about© the Jones difficulties & Bartlett of defining Learning, a gene; for ourLLC purposes, © Jones & Bartlett Learning, LLC the termNOT gene FOR refers SALE to a DNA OR sequenceDISTRIBUTION transcribed to a NOT FOR SALE OR DISTRIBUTION functional RNA molecule.) Mycoplasma genitalium, a free- living parasitic bacterium, has the smallest known genome 13,000 genes of any organism, with about only 470 genes. The genomes of Multicellular eukaryote free-living bacteria have from 1,700 to 7,500 genes. Archaean © Jones &genomes Bartlett have Learning, a smaller range LLC of 1,500 to 2,700 genes.© Jones & Bartlett Learning, LLC NOT FORThe SALE smallest OR unicellular DISTRIBUTION eukaryotic genomes have aboutNOT FOR SALE OR DISTRIBUTION 5,300 genes. Nematode worms and fruit flies have roughly 21,700 and 17,000 genes, respectively. Surprisingly, the num- 25,000 genes ber rises only to 20,000 to 25,000 for mammalian genomes. Higher plants FIGURE 5.1 summarizes the minimum number of genes found in six groups of organisms.© Jones A cell& Bartlett requires a minimumLearning, LLC © Jones & Bartlett Learning, LLC of about 500 genes, a free-livingNOT FOR cell SALE requires OR about DISTRIBUTION 1,500 NOT FOR SALE OR DISTRIBUTION genes, a eukaryotic cell requires more than 5,000 genes, a 25,000 genes multicellular organism requires more than 10,000 genes, Mammals and an organism with a nervous system requires more than 13,000 genes. Many species have more than the minimum number© Jonesof genes required,& Bartlett so the Learning, number of genes LLC can vary FIGURE 5.1 ©The Jones minimum & gene Bartlett number Learning,required for any LLC type of organism increases with its complexity. widely,NOT even FORamong SALE closely related OR DISTRIBUTION species. NOT FOR SALE OR DISTRIBUTION (a) Photo of intracellular bacterium courtesy of Gregory P. Henderson and Grant J. Jensen, California Institute of Within prokaryotes and unicellular eukaryotes, most Technology. genes are unique. Within multicellular eukaryotic genomes, (b) Courtesy of Rocky Mountain Laboratories, NIAID, NIH. (c) Courtesy of Eishi Noguchi, Drexel University College of Medicine. however, some genes are arranged into families of related (d) Courtesy of Carolyn B. Marks and David H. Hall, Albert Einstein College of Medicine, Bronx, NY. members. Of course, some genes are unique (meaning the (e) Courtesy of Keith Weller/USDA. © Jones &family Bartlett has only Learning, one member), LLC but many belong to families© Jones(f) © Photodisc. & Bartlett Learning, LLC NOT FORwith SALE 10 or ORmore DISTRIBUTION members. The number of different familiesNOT FOR SALE OR DISTRIBUTION may be a better indication of the overall complexity of the The availability of the genome sequences of genetic organism than the number of genes. “model organisms” (e.g., Escherichia coli, yeast, Drosophila, Some of the most insightful information comes from Arabidopsis, and humans) in the late 1990s and early 2000s comparing genome sequences. The growing number of com- allowed comparisons between major taxonomic groups such plete genome sequences© has Jones provided & Bartlettvaluable opportuni Learning,- LLCas prokaryote versus eukaryote,© animalJones versus & Bartlett plant, or verLearning,- LLC ties to study genome structureNOT FORand organization. SALE OR As DISTRIBUTIONgenome tebrate versus invertebrate. MoreNOT recently, FOR data SALE from multiple OR DISTRIBUTION sequences of related species become available, there are oppor- genomes within lower-level taxonomic groups (classes down tunities to compare not only individual gene differences but to genera) have allowed closer examination of genome evo- also large-scale genomic differences in aspects such as gene lution. Such comparisons have the advantage of highlighting distribution, the proportions of nonrepetitive and repetitive changes that have occurred much more recently and are less DNA© and Jones their functional & Bartlett potentials, Learning, and the number LLC of cop- obscured by© additional Jones &changes, Bartlett such Learning,as multiple mutations LLC ies ofNOT repetitive FOR sequences. SALE By OR making DISTRIBUTION these comparisons, we at the sameNOT site. In FOR addition, SALE evolutionary OR DISTRIBUTION events specific to can gain insight into the historical genetic events that have a taxonomic group can be explored. For example, human– shaped the genomes of individual species and of the adaptive chimpanzee comparisons can provide information about and nonadaptive forces at work following these events. For primate-specific genome evolution, particularly when com- example, with the sequences now available for both the human pared with an outgroup (a species that is less closely related, © Jones &and Bartlett chimpanzee Learning, genomes, it LLC is possible to begin to address© Jonesbut close & Bartlett enough to Learning,show substantial LLC similarity) such as the NOT FORsome SALE of the OR questions DISTRIBUTION about what makes humans unique. NOT mouse.FOR SALEOne recent OR milestone DISTRIBUTION in this field of comparative 102 Chapter 5 Genome Sequences and Evolution 9781284104646_CH05_101_142.indd 102 01/02/17 5:03 PM © Jones & Bartlett Learning LLC, an Ascend Learning Company. NOT FOR SALE OR DISTRIBUTION. genomics is the completion of genome sequences of nearly with metabolic functions (which are largely provided by the 30 species of the genus Drosophila. These types of fine-scale host cell) and with regulation of gene expression.
Load more

Recommended publications
  • Specificity of Genome Evolution in Experimental Populations Of
    Specificity of genome evolution in experimental PNAS PLUS populations of Escherichia coli evolved at different temperatures Daniel E. Deatheragea,b,c,d, Jamie L. Kepnera,b,c,d, Albert F. Bennette, Richard E. Lenskif,g,1, and Jeffrey E. Barricka,b,c,d,f,1 aCenter for Systems and Synthetic Biology, The University of Texas at Austin, Austin, TX 78712; bCenter for Computational Biology and Bioinformatics, The University of Texas at Austin, Austin, TX 78712; cInstitute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, TX 78712; dDepartment of Molecular Biosciences, The University of Texas at Austin, Austin, TX 78712; eDepartment of Ecology and Evolutionary Biology, University of California, Irvine, CA 92697; fBEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, MI 48824; and gDepartment of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI 48824 Edited by Neil H. Shubin, The University of Chicago, Chicago, IL, and approved January 25, 2017 (received for review September 27, 2016) Isolated populations derived from a common ancestor are expected to produce only in environments within a restricted thermal range. diverge genetically and phenotypically as they adapt to different local Adaptation for improved thermotolerance has important impli- environments. To examine this process, 30 populations of Escherichia cations for plant growth (5) and crop productivity (6), especially coli were evolved for 2,000 generations, with six in each of five dif- in light of climate change (7). Directed evolution of microor- ferent thermal regimes: constant 20 °C, 32 °C, 37 °C, 42 °C, and daily ganisms, such as yeast, to function effectively at higher or lower alternations between 32 °C and 42 °C.
    [Show full text]
  • Comparative Genome Evolution Working Group
    Comparative Genome Evolution Working Group COMPARATIVE GENOME EVOLUTION MODIFIED PROPOSAL Introduction Analysis of comparative genomic sequence information from a well-chosen set of organisms is, at present, one of the most effective approaches available to advance biomedical research. The following document describes rationales and plans for selecting targets for genome sequencing that will provide insight into a number of major biological questions that broadly underlie major areas of research funded by the National Institutes of Health, including studies of gene regulation, understanding animal development, and understanding gene and protein function. Genomic sequence data is a fundamental information resource that is required to address important questions about biology: What is the genomic basis for the advent of major morphogenetic or physiological innovations during evolution? How have genomes changed with the addition of new features observed in the eukaryotic lineage, for example the development of an adaptive immune system, an organized nervous system, bilateral symmetry, or multicellularity? What are the genomic correlates or bases for major evolutionary phenomena such as evolutionary rates; speciation; genome reorganization, and origins of variation? Another vital use to which genomic sequence data are applied is the development of more robust information about important non-human model systems used in biomedical research, i.e. how can we identify conserved functional regions in the existing genome sequences of important non- mammalian model systems, so that we can better understand fundamental aspects of, for example, gene regulation, replication, or interactions between genes? NHGRI established a working group to provide the Institute with well-considered scientific thought about the genomic sequences that would most effectively address these questions.
    [Show full text]
  • Section 4. Guidance Document on Horizontal Gene Transfer Between Bacteria
    306 - PART 2. DOCUMENTS ON MICRO-ORGANISMS Section 4. Guidance document on horizontal gene transfer between bacteria 1. Introduction Horizontal gene transfer (HGT) 1 refers to the stable transfer of genetic material from one organism to another without reproduction. The significance of horizontal gene transfer was first recognised when evidence was found for ‘infectious heredity’ of multiple antibiotic resistance to pathogens (Watanabe, 1963). The assumed importance of HGT has changed several times (Doolittle et al., 2003) but there is general agreement now that HGT is a major, if not the dominant, force in bacterial evolution. Massive gene exchanges in completely sequenced genomes were discovered by deviant composition, anomalous phylogenetic distribution, great similarity of genes from distantly related species, and incongruent phylogenetic trees (Ochman et al., 2000; Koonin et al., 2001; Jain et al., 2002; Doolittle et al., 2003; Kurland et al., 2003; Philippe and Douady, 2003). There is also much evidence now for HGT by mobile genetic elements (MGEs) being an ongoing process that plays a primary role in the ecological adaptation of prokaryotes. Well documented is the example of the dissemination of antibiotic resistance genes by HGT that allowed bacterial populations to rapidly adapt to a strong selective pressure by agronomically and medically used antibiotics (Tschäpe, 1994; Witte, 1998; Mazel and Davies, 1999). MGEs shape bacterial genomes, promote intra-species variability and distribute genes between distantly related bacterial genera. Horizontal gene transfer (HGT) between bacteria is driven by three major processes: transformation (the uptake of free DNA), transduction (gene transfer mediated by bacteriophages) and conjugation (gene transfer by means of plasmids or conjugative and integrated elements).
    [Show full text]
  • Genome Evolution: Mutation Is the Main Driver of Genome Size in Prokaryotes Gabriel A.B
    Genome Evolution: Mutation Is the Main Driver of Genome Size in Prokaryotes Gabriel A.B. Marais, Bérénice Batut, Vincent Daubin To cite this version: Gabriel A.B. Marais, Bérénice Batut, Vincent Daubin. Genome Evolution: Mutation Is the Main Driver of Genome Size in Prokaryotes. Current Biology - CB, Elsevier, 2020, 30 (19), pp.R1083- R1085. 10.1016/j.cub.2020.07.093. hal-03066151 HAL Id: hal-03066151 https://hal.archives-ouvertes.fr/hal-03066151 Submitted on 15 Dec 2020 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. DISPATCH Genome Evolution: Mutation is the Main Driver of Genome Size in Prokaryotes Gabriel A.B. Marais1, Bérénice Batut2, and Vincent Daubin1 1Université Lyon 1, CNRS, Laboratoire de Biométrie et Biologie Évolutive UMR 5558, F- 69622 Villeurbanne, France 2Albert-Ludwigs-University Freiburg, Department of Computer Science, 79110 Freiburg, Germany Summary Despite intense research on genome architecture since the 2000’s, genome-size evolution in prokaryotes has remained puzzling. Using a phylogenetic approach, a new study found that increased mutation rate is associated with gene loss and reduced genome size in prokaryotes. In 2003 [1] and later in 2007 in his book “The Origins of Genome Architecture” [2], Lynch developed his influential theory that a genome’s complexity, represented by its size, is primarily the result of genetic drift.
    [Show full text]
  • Genomes and Their Evolution
    CAMPBELL BIOLOGY IN FOCUS URRY • CAIN • WASSERMAN • MINORSKY • REECE 18 Genomes and Their Evolution Lecture Presentations by Kathleen Fitzpatrick and Nicole Tunbridge, Simon Fraser University © 2016 Pearson Education, Inc. SECOND EDITION Overview: Reading Leaves from the Tree of Life . Complete genome sequences exist for a human, chimpanzee, E. coli, and numerous other prokaryotes, as well as corn, fruit fly, house mouse, orangutan, and others . Comparisons of genomes among organisms provide information about the evolutionary history of genes and taxonomic groups © 2016 Pearson Education, Inc. Genomics is the study of whole sets of genes and their interactions . Bioinformatics is the application of computational methods to the storage and analysis of biological data © 2016 Pearson Education, Inc. Figure 18.1 © 2016 Pearson Education, Inc. Concept 18.1: The Human Genome Project fostered development of faster, less expensive sequencing techniques . The Human Genome Project officially began in 1990, and the sequencing was largely completed by 2003 . Even with automation, the sequencing of all 3 billion base pairs in a haploid set presented a formidable challenge . A major thrust of the Human Genome Project was the development of technology for faster sequencing © 2016 Pearson Education, Inc. The whole-genome shotgun approach was developed by J. Craig Venter and colleagues . This approach starts with cloning and sequencing random DNA fragments . Powerful computer programs are used to assemble the resulting short overlapping sequences into a single continuous sequence © 2016 Pearson Education, Inc. Figure 18.2-s1 Cut the DNA into overlapping fragments short enough for sequencing. Clone the fragments in plasmid or other vectors. © 2016 Pearson Education, Inc.
    [Show full text]
  • On the Law of Directionality of Genome Evolution
    On the Law of Directionality of Genome Evolution Liaofu Luo Laboratory of Theoretical Biophysics, Faculty of Science and Technology, Inner Mongolia University, Hohhot 010021, China *Email address: [email protected] Abstract The problem of the directionality of genome evolution is studied from the information-theoretic view. We propose that the function-coding information quantity of a genome always grows in the course of evolution through sequence duplication, expansion of code, and gene transfer between genomes. The function-coding information quantity of a genome consists of two parts, p-coding information quantity which encodes functional protein and n-coding information quantity which encodes other functional elements except amino acid sequence. The relation of the proposed law to the thermodynamic laws is indicated. The evolutionary trends of DNA sequences revealed by bioinformatics are investigated which afford further evidences on the evolutionary law. It is argued that the directionality of genome evolution comes from species competition adaptive to environment. An expression on the evolutionary rate of genome is proposed that the rate is a function of Darwin temperature (describing species competition) and fitness slope (describing adaptive landscape). Finally, the problem of directly experimental test on the evolutionary directionality is discussed briefly. 1 A law of genomic information The traditional natural sciences mostly focused on matter and energy. Of course, the two are basic categories in the nature. However, parallel to yet different from matter and energy, information constitutes the third fundamental category in natural sciences. One characteristic of a life system is that it contains a large amount of information. Life consists of matter and energy, but it is not just matter and energy.
    [Show full text]
  • The Neoselectionist Theory of Genome Evolution
    The neoselectionist theory of genome evolution Giorgio Bernardi* Molecular Evolution Laboratory, Stazione Zoologica Anton Dohrn, Villa Comunale, 80121 Naples, Italy Edited by Tomoko Ohta, National Institute of Genetics, Mishima, Japan, and approved April 4, 2007 (received for review February 22, 2007) The vertebrate genome is a mosaic of GC-poor and GC-rich isoch- of chance in evolution. A very significant modification of the ores, megabase-sized DNA regions of fairly homogeneous base neutral theory was the nearly neutral theory of Ohta (11, 12), composition that differ in relative amount, gene density, gene who proposed that a substantial fraction of changes are caused expression, replication timing, and recombination frequency. At by random fixation of nearly neutral changes, a class that the emergence of warm-blooded vertebrates, the gene-rich, mod- ‘‘includes intermediates between neutral and advantageous, as erately GC-rich isochores of the cold-blooded ancestors underwent well as between neutral and deleterious classes’’ (13). The first a GC increase. This increase was similar in mammals and birds and four schemes of Fig. 1 display a qualitative picture of the classical was maintained during the evolution of mammalian and avian theories just mentioned. orders. Neither the GC increase nor its conservation can be ac- All classical theories proposed that natural selection acted on counted for by the random fixation of neutral or nearly neutral the ‘‘phenotype’’ [called the ‘‘classical phenotype’’ by Bernardi single-nucleotide changes (i.e., the vast majority of nucleotide and Bernardi (14), to distinguish it from the ‘‘genome pheno- substitutions) or by a biased gene conversion process occurring at type’’ presented below].
    [Show full text]
  • On the Law of Directionality of Genome Evolution”
    Law of Genome Evolution Direction : Coding Information Quantity Grows Liaofu Luo Laboratory of Theoretical Biophysics, Faculty of Science and Technology, Inner Mongolia University, Hohhot 010021, China; *Email address: [email protected] Abstract The problem of the directionality of genome evolution is studied. Based on the analysis of C-value paradox and the evolution of genome size we propose that the function-coding information quantity of a genome always grows in the course of evolution through sequence duplication, expansion of code, and gene transfer from outside. The function-coding information quantity of a genome consists of two parts, p-coding information quantity which encodes functional protein and n-coding information quantity which encodes other functional elements except amino acid sequence. The evidences on the evolutionary law about the function-coding information quantity are listed. The needs of function is the motive force for the expansion of coding information quantity and the information quantity expansion is the way to make functional innovation and extension for a species. So, the increase of coding information quantity of a genome is a measure of the acquired new function and it determines the directionality of genome evolution. Key words: genome evolution, function-coding information quantity growing, p-coding information quantity, n- coding information quantity, C-value paradox The extension of the diversity of species and their evolution towards higher function more adaptive to environment shows that the life evolution obeys a law with definite direction. Darwin expressed the law as “survival of the fittest”. It means that the ‘designed’ properties of living things better adapted to survive will leave more offspring and automatically increase in frequency from one generation to the next, while the poorly adapted species will decrease in frequency.
    [Show full text]
  • Transposable Elements and Host Genome Evolution
    TRANSPOSABLE ELEMENTS AND HOST GENOME EVOLUTION Margaret G. Kidwell and Damon R. Lisch Margaret Kidwell is at the Dept of Ecology and Evolutionary Biology, The University of Arizona, 116 BSW Building, Tucson, AZ 85721, USA (email: [email protected]). Damon Lisch is at the Dept of Plant and Microbial Biology, 111 Koshland Hall, U.C Berkeley, Berkeley, CA 94720, USA (email: [email protected]) Corresponding author: Dr. Margaret G. Kidwell, Department of Ecology and Evolutionary Biology, The University of Arizona, 116 BSW Building, Tucson, AZ 85721, USA. Phone:(520) 621-1784. Fax: (520) 621- 9190. Email: [email protected] Keywords: Animal, Plant, Transposable Elements, Enhancer Elements, Evolution, Gene Expression, Gene Regulation, Molecular Sequence Data, Repetitive Sequences, DNA Methylation 1 A number of recent reports have challenged the idea that TEs are mainly "selfish" or "junk" DNA with little importance for host evolution. It has been proposed that TEs have the potential to provide host genomes with the ability to enhance their own evolution. They might also be a major source of genetic diversity that allows response to environmental changes. Because the relationships between TEs and host genomes are highly variable and the selfish, junk and beneficial DNA hypotheses are by no means mutually exclusive, a single label for these relationships appears to be inappropriate and potentially misleading. Transposable elements (TEs) are mobile DNA sequences that are widely distributed in bacteria, plants and animals. At least two levels of selection can apply to TEs: selection at the DNA level and selection at the level of the host organism. Positive selection at the DNA level results from the ability of TE sequences to replicate faster than those of the host genome.
    [Show full text]
  • Genome Evolution FRI, 12:30-1:30,12:30-1:30 NCB-117
    BIOLOGY 4200B/9561B: WINTER 20172017 ROOM TC-203——————— (MON, WED) MON & WED,ROOM 12:30-1:30, NCB-117 TC-203 (FRI) genome evolution FRI, 12:30-1:30,12:30-1:30 NCB-117 instructor: David Smith | office: BGS3028 | office hours: FRI 4:30-5:30 | [email protected] About the class: Ever wonder why some genomes are gigantic and others are so tiny? Why some are simple, circular molecules while others are fragmented into hundreds of linear chromosomes? This course will try to answer these & other questions about genome evolution. It will explore the diversity in genomic architecture across the eukaryotic tree of life. Through lectures, student presentations, and group discussions, we will examine strange and bizarre genomes – genomes that break all of the rules. We will discuss controversial hypotheses about genome evolution and the scientists who developed them. The course also has a strong “communications” component, with lectures on scientific writing, speaking, and social media – all with a bend on genomics, of course. Prerequisites: 4200B: 1.5 Biol courses at 3000 level or above & registration in Year 4 of an Honors specialization module. 9561B: Graduate student in Biology. Text: All materials will be provided in class or online. Course website: www.arrogantgenome.com/genome-evolution/ [password: genome] Evaluation1: take-home exam class presentation •short-essay questions •describe your favourite genome •genome trivia •hypothesize about the architectural 30% 30% origins •or delve into a topic on science communication 10% journal club presentations & class discussions/debates 30% •who will speak for the genomes? 1,000- to 1,500-word essay •a person, a genome, a hypothesis, or anything pop-science.
    [Show full text]
  • Chromosome-Centric View of Genome Organization and Evolution
    G C A T T A C G G C A T genes Editorial Chromosome-Centric View of Genome Organization and Evolution Maria Sharakhova 1,* and Vladimir Trifonov 2,* 1 Department of Entomology and Fralin Life Sciences Institute, Virginia Tech, Blacksburg, VA 24061, USA 2 Department of Genome Diversity and Evolution, Institute of Molecular and Cellular Biology, SB RAS, 630090 Novosibirsk, Russia * Correspondence: [email protected] (M.S.); [email protected] (V.T.) Genetic material in all cellular organisms is packed into chromosomes, which repre- sent essential units of inheritance, recombination, and evolution. Thus, our understanding of genome function is incomplete without knowledge of genome organization at the chro- mosome level. Recent advances in genome technologies, including long-read sequencing, chromosome flow sorting, Hi-C scaffolding, and optical mapping, allow the procurement of genome assemblies at the level of complete chromosomes. Physical genome mapping based on fluorescence in situ hybridization (FISH) enables direct correspondence of genomic sequences with particular chromosome bands or specific chromosome structures. Such chromosome-scale genome assemblies provide new opportunities for both cytogenetic and genome research. This Special Issue, entitled “Chromosome-Centric View of Genome Organization and Evolution” focuses on modern cytogenetic studies based on utilization of genome assemblies that are currently available for multiple organisms, including a key model organism, Drosophila melanogaster, and non-model organisms of vertebrates, insects, plants, and finally, humans. The issue contains twelve original research articles and 3 review papers devoted to recent achievements in the field of genomic studies of Citation: Sharakhova, M.; Trifonov, eukaryotic chromosomes. V. Chromosome-Centric View of The classical model organism D.
    [Show full text]
  • Quantum Theory on Genome Evolution
    Quantum patterns of genome size variation in angiosperms Liaofu Luo1 2 Lirong Zhang1 1 School of Physical Science and Technology, Inner Mongolia University, Hohhot, Inner Mongolia, 010021, P. R. China 2 School of Life Science and Technology, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia,014010, P. R. China Email to LZ: [email protected] ; LL: [email protected] Abstract The nuclear DNA amount in angiosperms is studied from the eigen-value equation of the genome evolution operator H. The operator H is introduced by physical simulation and it is defined as a function of the genome size N and the derivative with respective to the size. The discontinuity of DNA size distribution and its synergetic occurrence in related angiosperms species are successfully deduced from the solution of the equation. The results agree well with the existing experimental data of Aloe, Clarkia, Nicotiana, Lathyrus, Allium and other genera. It may indicate that the evolutionary constrains on angiosperm genome are essentially of quantum origin. Key words: Genome size; DNA amount; Evolution; Angiosperms; Quantum Introduction DNA amount is relatively constant and tends to be highly characteristic for a species. The nuclear DNA amounts of angiosperm plants were estimated by at least eight different techniques and mainly (over 96%) by flow cytometry and Feulgen microdensitometry. The C-values for more than 6000 angiosperm species were reported till 2011(1). It is found that these C-values are highly variable, differing over 1000-fold. Changes in DNA amount in evolution often appear non-random in amount and distribution (2-4).
    [Show full text]