Whole-Genome Duplication Followed by Massive Gene Loss and Specialization Has Long Been Postulated As a Powerful Mechanism of Evolutionary Innovation
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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. -
Copying out Our Abcs the Role of Gene Redundancy in Interpreting Genetic Hierarchies
Genomic imprinting in mammals COMMENT Outlook 14 Nicholls, R.D. et al. (1998) Imprinting in Prader–Willi and 21 Feil, R. et al. (1997) Parental chromosome-specific chromatin 28 Macleod, D. et al. (1994) Sp1 sites in the mouse Aprt gene Angelman syndromes. Trends Genet. 14, 194–199 conformation in the imprinted U2af1-rs1 gene in the mouse. promoter are required to prevent methylation of the CpG 15 Hark, A.T. and Tilghman, S.M. (1998) Chromatin conformation J. Biol. Chem. 272, 20893–20900 island. Genes Dev. 8, 2282–2292 of the H19 epigenetic mark. Hum. Mol. Genet. 7, 1979–1985 22 Schweizer, J. et al. (1999) In vivo nuclease hypersensitivity 29 Brandeis, M. et al. (1994) SP1 elements protect a CpG island 16 Szabó, P.E. et al. (1998) Characterization of novel parent- studies reveal multiple sites of parental-origin-dependent from de novo methylation. Nature 371, 435–438 specific epigenetic modifications upstream of the imprinted differential chromatin conformation in the 150 kb SNRPN 30 Kirillov, A. et al. (1996) A role for nuclear NF-kB in mouse H19 gene. Mol. Cell. Biol. 18, 6767–6776 transcription unit. Hum. Mol. Genet. 8, 555–566 B-cell-specific demethylation of the Igk locus. Nat. Genet. 13, 17 Khosla, S. et al. (1999) Parental allele-specific chromatin 23 Lyko, F. et al. (1998) Identification of a silencing element in 435–441 configuration in a boundary/imprinting-control element the human 15q11–q13 imprinting center by using 31 Hsieh, C-L. (1999) Evidence that protein-binding upstream of the mouse H19 gene. -
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. -
Gene Loss and Adaptation in Saccharomyces Genomes
Genetics: Published Articles Ahead of Print, published on December 1, 2005 as 10.1534/genetics.105.048900 After the duplication: gene loss and adaptation in Saccharomyces genomes Paul F. Cliften*,1, Robert S. Fulton§, Richard K. Wilson*, §, and Mark Johnston* *Department of Genetics and §Genome Sequencing Center, Washington University School of Medicine, 660 South Euclid Ave., St. Louis, MO, 63110; 1Current address: Department of Biology, Utah State University, 5305 Old Main Hill, Logan, UT, 84322 Running head: Saccharomyces genomic duplications Key words: genomic duplication, comparative sequence analysis, Saccharomyces phylogeny, yeast Corresponding author: Mark Johnston Department of Genetics Campus Box 8232 Washington University Medical School 4566 Scott Ave. St. Louis, MO 63110 TEL: 314-362-2735 FAX: 314-362-2157 [email protected] ABSTRACT The ancient duplication of the Saccharomyces cerevisiae genome and subsequent massive loss of duplicated genes is apparent when it is compared to the genomes of related species that diverged before the duplication event. To learn more about the evolutionary effects of the duplication event, we compared the S. cerevisiae genome to other Saccharomyces genomes. We demonstrate that the whole genome duplication occurred before S. castellii diverged from S. cerevisiae. In addition to more accurately dating the duplication event, this finding allowed us to study the effects of the duplication on two separate lineages. Analyses of the duplication regions of the genomes indicate that most of the duplicated genes (approximately 85%) were lost before the speciation. Only a small amount of paralogous gene loss (4-6%) occurred after speciation. On the other hand, S. castellii appears to have lost several hundred genes that were not retained as duplicated paralogs. -
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). -
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. -
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. -
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 -
Genetic Variation of the Serine Acetyltransferase Gene Family for Sulfur Assimilation in Maize
G C A T T A C G G C A T genes Article Genetic Variation of the Serine Acetyltransferase Gene Family for Sulfur Assimilation in Maize Zhixuan Zhao 1, Shuai Li 1, Chen Ji 2 , Yong Zhou 2, Changsheng Li 2 and Wenqin Wang 1,* 1 School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, China; [email protected] (Z.Z.); [email protected] (S.L.) 2 National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology & Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200032, China; [email protected] (C.J.); [email protected] (Y.Z.); [email protected] (C.L.) * Correspondence: [email protected]; Tel.: +86-21-34206942 Abstract: Improving sulfur assimilation in maize kernels is essential due to humans and animals’ inability to synthesize methionine. Serine acetyltransferase (SAT) is a critical enzyme that controls cystine biosynthesis in plants. In this study, all SAT gene members were genome-wide characterized by using a sequence homology search. The RNA-seq quantification indicates that they are highly expressed in leaves, other than root and seeds, consistent with their biological functions in sulfur assimilation. With the recently released 25 genomes of nested association mapping (NAM) founders representing the diverse maize stock, we had the opportunity to investigate the SAT genetic variation comprehensively. The abundant transposon insertions into SAT genes indicate their driving power in terms of gene structure and genome evolution. We found that the transposon insertion into exons could change SAT gene transcription, whereas there was no significant correlation between transposable element (TE) insertion into introns and their gene expression, indicating that other Citation: Zhao, Z.; Li, S.; Ji, C.; Zhou, regulatory elements such as promoters could also be involved. -
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. -
Evolution of Multigene Families by Gene Duplication: a Haploid Model
Copyright 1998 by the Genetics Society of America Evolution of Multigene Families by Gene Duplication: A Haploid Model Hidenori Tachida and Tohru Kuboyama Department of Biology, Faculty of Science, Kyushu University 33, Fukuoka 812-8581, Japan Manuscript received October 12, 1997 Accepted for publication May 13, 1998 ABSTRACT Evolution of multigene families by gene duplication and subsequent diversi®cation is analyzed assuming a haploid model without interchromosomal crossing over. Chromosomes with more different genes are assumed to have higher ®tness. Advantageous and deleterious mutations and duplication/deletion also affect the evolution, as in previous studies. In addition, negative selection on the total number of genes (copy number selection) is incorporated in the model. First, a Markov chain approximation is used to obtain formulas for the average numbers of different alleles, genes without pseudogene mutations, and pseudogenes assuming that mutation rates and duplication/deletion rates are all very small. Computer simulation shows that the approximation works well if the products of population size with mutation and duplication/deletion rates are all small compared to 1. However, as they become large, the approximation underestimates gene numbers, especially the number of pseudogenes. Based on the approximation, the following was found: (1) Gene redundancy measured by the average number of redundant genes decreases as advantageous selection becomes stronger. (2) The number of different genes can be approximately described by a linear pure-birth process and thus has a coef®cient of variation around 1. (3) The birth rate is an increasing function of population size without copy number selection, but not necessarily so otherwise. -
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].