Comparative Genomics: the Key to Understanding the Human Genome Project M.S
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The New Science of Metagenomics: Revealing the Secrets of Our Microbial Planet Is Available from the National Academies Press, 500 Fifth Street, NW, Washington, D.C
THE NATIONALA REPORTIN BRIEF C The New Science of Metagenomics Revealing the Secrets of Our Microbial Planet ADEMIES Although we can’t see them, microbes are essential for every part of human life— indeed all life on Earth. The emerging field of metagenomics provides a new way of viewing the microbial world that will not only transform modern microbiology, but also may revolu- tionize understanding of the entire living world. very part of the biosphere is impacted Eby the seemingly endless ability of microorganisms to transform the world around them. It is microorganisms, or microbes, that convert the key elements of life—carbon, nitrogen, oxygen, and sulfur—into forms accessible to other living things. They also make necessary nutrients, minerals, and vitamins available to plants and animals. The billions of microbes living in the human gut help humans digest food, break down toxins, and fight off disease-causing pathogens. Microbes also clean up pollutants in the environment, such as oil and Bacteria in human saliva. Trillions of chemical spills. All of these activities are carried bacteria make up the normal microbial com- out not by individual microbes but by complex munity found in and on the human body. microbial communities—intricate, balanced, and The new science of metagenomics can help integrated entities that have a remarkable ability to us understand the role of microbial commu- adapt swiftly to environmental change. nities in human health and the environment. Historically, microbiology has focused on (Image courtesy of Michael Abbey) single species in pure laboratory culture, and thus understanding of microbial communities has lagged behind understanding of their individual mem- bers. -
Genomics and Its Impact on Science and Society: the Human Genome Project and Beyond
DOE/SC-0083 Genomics and Its Impact on Science and Society The Human Genome Project and Beyond U.S. Department of Energy Genome Research Programs: genomics.energy.gov A Primer ells are the fundamental working units of every living system. All the instructions Cneeded to direct their activities are contained within the chemical DNA (deoxyribonucleic acid). DNA from all organisms is made up of the same chemical and physical components. The DNA sequence is the particular side-by-side arrangement of bases along the DNA strand (e.g., ATTCCGGA). This order spells out the exact instruc- tions required to create a particular organism with protein complex its own unique traits. The genome is an organism’s complete set of DNA. Genomes vary widely in size: The smallest known genome for a free-living organism (a bac- terium) contains about 600,000 DNA base pairs, while human and mouse genomes have some From Genes to Proteins 3 billion (see p. 3). Except for mature red blood cells, all human cells contain a complete genome. Although genes get a lot of attention, the proteins DNA in each human cell is packaged into 46 chro- perform most life functions and even comprise the mosomes arranged into 23 pairs. Each chromosome is majority of cellular structures. Proteins are large, complex a physically separate molecule of DNA that ranges in molecules made up of chains of small chemical com- length from about 50 million to 250 million base pairs. pounds called amino acids. Chemical properties that A few types of major chromosomal abnormalities, distinguish the 20 different amino acids cause the including missing or extra copies or gross breaks and protein chains to fold up into specific three-dimensional rejoinings (translocations), can be detected by micro- structures that define their particular functions in the cell. -
The Human Genome Project Focus of the Human Genome Project
TOOLS OF GENETIC RESEARCH THE HUMAN GENOME PROJECT FOCUS OF THE HUMAN GENOME PROJECT The primary work of the Human Genome Project has been to Francis S. Collins, M.D., Ph.D.; produce three main research tools that will allow investigators to and Leslie Fink identify genes involved in normal biology as well as in both rare and common diseases. These tools are known as positional cloning The Human Genome Project is an ambitious research effort aimed at deciphering the chemical makeup of the entire human (Collins 1992). These advanced techniques enable researchers to ge ne tic cod e (i.e. , the g enome). The primary wor k of the search for diseaselinked genes directly in the genome without first having to identify the gene’s protein product or function. (See p ro j e c t i s t o d ev e lop t h r e e r e s e a r c h tool s t h a t w i ll a ll o w the article by Goate, pp. 217–220.) Since 1986, when researchers scientists to identify genes involved in both rare and common 2 diseases. Another project priority is to examine the ethical, first found the gene for chronic granulomatous disease through legal, and social implications of new genetic technologies and positional cloning, this technique has led to the isolation of consid to educate the public about these issues. Although it has been erably more than 40 diseaselinked genes and will allow the identi in existence for less than 6 years, the Human Genome Project fication of many more genes in the future (table 1). -
From the Human Genome Project to Genomic Medicine a Journey to Advance Human Health
From the Human Genome Project to Genomic Medicine A Journey to Advance Human Health Eric Green, M.D., Ph.D. Director, NHGRI The Origin of “Genomics”: 1987 Genomics (1987) “For the newly developing discipline of [genome] mapping/sequencing (including the analysis of the information), we have adopted the term GENOMICS… ‘The Genome Institute’ Office for Human Genome Research 1988-1989 National Center for Human Genome Research 1989-1997 National Human Genome Research Institute 1997-present NHGRI: Circa 1990-2003 Human Genome Project NHGRI Today: Characteristic Features . Relatively young (~28 years) . Relatively small (~1.7% of NIH) . Unusual historical origins (think ‘Human Genome Project’) . Emphasis on ‘Team Science’ (think managed ‘consortia’) . Rapidly disseminating footprint (think ‘genomics’) . Novel societal/bioethics research component (think ‘ELSI’) . Over-achievers for trans-NIH initiatives (think ‘Common Fund’) . Vibrant (and large) Intramural Research Program A Quarter Century of Genomics Human Genome Sequenced for First Time by the Human Genome Project Genomic Medicine An emerging medical discipline that involves using genomic information about an individual as part of their clinical care (e.g., for diagnostic or therapeutic decision- making) and the other implications of that clinical use The Path to Genomic Medicine ? Human Realization of Genome Genomic Project Medicine Nature Nature Base Pairs to Bedside 2003 Heli201x to 1Health A Quarter Century of Genomics Human Genome Sequenced for First Time by the Human Genome Project -
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 Prediction Using Deep Learning
FACULDADE DE ENGENHARIA DA UNIVERSIDADE DO PORTO Gene prediction using Deep Learning Pedro Vieira Lamares Martins Mestrado Integrado em Engenharia Informática e Computação Supervisor: Rui Camacho (FEUP) Second Supervisor: Nuno Fonseca (EBI-Cambridge, UK) July 22, 2018 Gene prediction using Deep Learning Pedro Vieira Lamares Martins Mestrado Integrado em Engenharia Informática e Computação Approved in oral examination by the committee: Chair: Doctor Jorge Alves da Silva External Examiner: Doctor Carlos Manuel Abreu Gomes Ferreira Supervisor: Doctor Rui Carlos Camacho de Sousa Ferreira da Silva July 22, 2018 Abstract Every living being has in their cells complex molecules called Deoxyribonucleic Acid (or DNA) which are responsible for all their biological features. This DNA molecule is condensed into larger structures called chromosomes, which all together compose the individual’s genome. Genes are size varying DNA sequences which contain a code that are often used to synthesize proteins. Proteins are very large molecules which have a multitude of purposes within the individual’s body. Only a very small portion of the DNA has gene sequences. There is no accurate number on the total number of genes that exist in the human genome, but current estimations place that number between 20000 and 25000. Ever since the entire human genome has been sequenced, there has been an effort to consistently try to identify the gene sequences. The number was initially thought to be much higher, but it has since been furthered down following improvements in gene finding techniques. Computational prediction of genes is among these improvements, and is nowadays an area of deep interest in bioinformatics as new tools focused on the theme are developed. -
The Genome Project–Write Issues, Enabling Inclusive Decision-Making on the Topics Mentioned Above (7)
Human chromosomes and nucleus as visualized by scanning electron microscopy. Through open and ongoing dialogue, com- mon goals can be identified. Informed consent must take local and regional val- ues into account and enable true decision- making on particularly sensitive use of cells and DNA from certain sources. Finally, the highest biosafety standards should guide project work and safety for lab workers and research participants, and ecosystems should pervade the design process. A prior- ity will be cost reduction of both genome engineering and testing tools to aid in equi- POLICY FORUM table distribution of benefits—e.g., enabling research on crop plants and infectious agents and vectors in developing nations. GENOME ENGINEERING To ensure responsible innovation and on- going consideration of ELSI, a percentage of all research funds could be dedicated to these The Genome Project–Write issues, enabling inclusive decision-making on the topics mentioned above (7). In addi- We need technology and an ethical framework tion, there should be equitable distribution of any early and future benefits in view of on July 29, 2016 for genome-scale engineering diverse and pressing needs in different global regions. The broad scope and novelty of the By Jef D. Boeke,* George Church,* large-scale synthesis and editing of genomes. project call for consideration of appropriate Andrew Hessel,* Nancy J. Kelley,* Adam To this end, we propose the Human Genome regulation alongside development of the sci- Arkin, Yizhi Cai, Rob Carlson, Aravinda Project–Write (HGP-write), named to honor ence and societal debates. National and in- Chakravarti, Virginia W. Cornish, Liam HGP-read but embracing synthesis of all ternational laws and regulations differ, and Holt, Farren J. -
"An Overview of Gene Identification: Approaches, Strategies, and Considerations"
An Overview of Gene Identification: UNIT 4.1 Approaches, Strategies, and Considerations Modern biology has officially ushered in a new era with the completion of the sequencing of the human genome in April 2003. While often erroneously called the “post-genome” era, this milestone truly marks the beginning of the “genome era,” a time in which the availability of sequence data for many genomes will have a significant effect on how science is performed in the 21st century. While complete human sequence data is now available at an overall accuracy of 99.99%, the mere availability of all of these As, Cs, Ts, and Gs still does not answer some of the basic questions regarding the human genome—how many genes actually comprise the genome, how many of these genes code for multiple gene products, and where those genes actually lie along the complement of human chromosomes. Current estimates, based on preliminary analyses of the draft sequence, place the number of human genes at ∼30,000 (International Human Genome Sequencing Consortium, 2001). This number is in stark contrast to previously-suggested estimates, which had ranged as high as 140,000. A number that is in the 30,000 range brings into question the one-gene, one-protein hypothesis, underscoring the importance of processes such as alternative splicing in the generation of multiple gene products from a single gene. Finding all of the genes and the positions of those genes within the human genome sequence—and in other model organism genome sequences as well—requires the devel- opment and application of robust computational methods, some of which are listed in Table 4.1.1. -
Gene Prediction and Verification in a Compact Genome with Numerous Small Introns
Downloaded from genome.cshlp.org on October 9, 2021 - Published by Cold Spring Harbor Laboratory Press Methods Gene prediction and verification in a compact genome with numerous small introns Aaron E. Tenney,1 Randall H. Brown,1 Charles Vaske,1,4 Jennifer K. Lodge,2 Tamara L. Doering,3 and Michael R. Brent1,5 1Laboratory for Computational Genomics and Department of Computer Science, Washington University, St. Louis, Missouri 63130, USA; 2Department of Biochemistry and Molecular Biology, Saint Louis University School of Medicine, St. Louis, Missouri 63104, USA; 3Department of Molecular Microbiology, Washington University Medical School, St. Louis, Missouri 63110-1093, USA The genomes of clusters of related eukaryotes are now being sequenced at an increasing rate, creating a need for accurate, low-cost annotation of exon–intron structures. In this paper, we demonstrate that reverse transcription-polymerase chain reaction (RT–PCR) and direct sequencing based on predicted gene structures satisfy this need, at least for single-celled eukaryotes. The TWINSCAN gene prediction algorithm was adapted for the fungal pathogen Cryptococcus neoformans by using a precise model of intron lengths in combination with ungapped alignments between the genome sequences of the two closely related Cryptococcus varieties. This approach resulted in ∼60% of known genes being predicted exactly right at every coding base and splice site. When previously unannotated TWINSCAN predictions were tested by RT–PCR and direct sequencing, 75% of targets spanning two predicted introns were amplified and produced high-quality sequence. When targets spanning the complete predicted open reading frame were tested, 72% of them amplified and produced high-quality sequence. -
Bioinformatic Analysis of Cis-Encoded Antisense Transcription
BIOINFORMATIC ANALYSIS OF CIS-ENCODED ANTISENSE TRANSCRIPTION by Anca Sorana Morrissy B.Sc., Simon Fraser University, 2002 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in The Faculty of Graduate Studies (Medical Genetics) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) December 2010 © Anca Sorana Morrissy, 2010 Abstract A key first step in understanding cellular processes is a quantitative and comprehensive measurement of gene expression profiles. The scale and complexity of the mammalian transcriptome is a significant challenge to efforts aiming to identify the complete set of expressed transcripts. Specifically, detection of low-abundance sequences, such as antisense transcripts, has historically been difficult to achieve using EST libraries, microarrays, or tag sequencing methods. Antisense transcripts are expressed from the opposite strand of a partner gene, and in some cases can regulate the processing of the sense transcript, highlighting their biological relevance. Recently, efficient profiling of low-frequency transcripts was made possible with the advent of next generation sequencing platforms. Thus, a major goal of my thesis was to assess the prevalence of antisense transcripts using Tag-seq, a tag sequencing method modified to take advantage of the Illumina sequencing platform. The increase in sampling depth provided by Tag-seq resulted in significantly improved detection of low abundance antisense transcripts, and allowed accurate measurements of their differential expression across normal and cancerous states. While antisense transcription is known to regulate sense transcript processing at a small number of loci, no genome wide assessments of this regulatory interaction exist. I addressed this knowledge gap using Affymetrix exon arrays, and found a significant correlation between antisense transcription and alternative splicing in normal human cells. -
Model-Based Integration of Genomics and Metabolomics Reveals SNP Functionality in Mycobacterium Tuberculosis
Model-based integration of genomics and metabolomics reveals SNP functionality in Mycobacterium tuberculosis Ove Øyåsa,b,1, Sonia Borrellc,d,1, Andrej Traunerc,d,1, Michael Zimmermanne, Julia Feldmannc,d, Thomas Liphardta,b, Sebastien Gagneuxc,d, Jörg Stellinga,b, Uwe Sauere, and Mattia Zampierie,2 aDepartment of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland; bSIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland; cDepartment of Medical Parasitoloy and Infection Biology, Swiss Tropical and Public Health Institute, 4051 Basel, Switzerland; dUniversity of Basel, 4058 Basel, Switzerland; and eInstitute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland Edited by Ralph R. Isberg, Tufts University School of Medicine, Boston, MA, and approved March 2, 2020 (received for review September 12, 2019) Human tuberculosis is caused by members of the Mycobacterium infection of macrophages (29–32). Beyond analyses of individual tuberculosis complex (MTBC) that vary in virulence and transmis- laboratory strains, however, no systematic characterization and sibility. While genome-wide association studies have uncovered comparative analysis of intrinsic metabolic differences across several mutations conferring drug resistance, much less is known human-adapted MTBC clinical strains has been performed. about the factors underlying other bacterial phenotypes. Variation If the metabolic and other phenotypic diversity between in the outcome of tuberculosis infection and diseases has been MTBC strains contributes to and modulates pathogenicity, an attributed primarily to patient and environmental factors, but obvious question is: Which elements of the limited genetic di- recent evidence indicates an additional role for the genetic diver- versity in the MTBC are responsible for phenotypic strain di- sity among MTBC clinical strains. -
6.047/6.878 Lecture 4: Comparative Genomics I: Genome Annotation Using Evolutionary Signatures
6.047/6.878 Lecture 4: Comparative Genomics I: Genome Annotation Using Evolutionary Signatures Mark Smith (Partially adapted from notes by: Angela Yen, Christopher Robde, Timo Somervuo and Saba Gul) 9/18/12 1 Contents 1 Introduction 4 1.1 Motivation and Challenge......................................4 1.2 Importance of many closely{related genomes...........................4 2 Conservation of genomic sequences5 2.1 Functional elements in Drosophila .................................5 2.2 Rates and patterns of selection...................................5 3 Excess Constraint 6 3.1 Causes of Excess Constraint.....................................7 3.2 Modeling Excess Constraint.....................................8 3.3 Excess Constraint in the Human Genome.............................9 3.4 Examples of Excess Constraint................................... 10 4 Diversity of evolutionary signatures: An Overview of Selection Patterns 10 4.1 Selective Pressures On Different Functional Elements....................... 11 5 Protein{Coding Signatures 12 5.1 Reading{Frame Conservation (RFC)................................ 13 5.2 Codon{Substitution Frequencies (CSFs).............................. 14 5.3 Classification of Drosophila Genome Sequences.......................... 16 5.4 Leaky Stop Codons.......................................... 17 6 microRNA (miRNA) genes 19 6.1 Computational Challenge...................................... 20 6.2 Unusual miRNA Genes........................................ 21 7 Regulatory Motifs 22 7.1 Computationally Detecting