Genesis by Meiotic Unequal Crossover of a De Novo Deletion That
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13 Genomics and Bioinformatics
Enderle / Introduction to Biomedical Engineering 2nd ed. Final Proof 5.2.2005 11:58am page 799 13 GENOMICS AND BIOINFORMATICS Spencer Muse, PhD Chapter Contents 13.1 Introduction 13.1.1 The Central Dogma: DNA to RNA to Protein 13.2 Core Laboratory Technologies 13.2.1 Gene Sequencing 13.2.2 Whole Genome Sequencing 13.2.3 Gene Expression 13.2.4 Polymorphisms 13.3 Core Bioinformatics Technologies 13.3.1 Genomics Databases 13.3.2 Sequence Alignment 13.3.3 Database Searching 13.3.4 Hidden Markov Models 13.3.5 Gene Prediction 13.3.6 Functional Annotation 13.3.7 Identifying Differentially Expressed Genes 13.3.8 Clustering Genes with Shared Expression Patterns 13.4 Conclusion Exercises Suggested Reading At the conclusion of this chapter, the reader will be able to: & Discuss the basic principles of molecular biology regarding genome science. & Describe the major types of data involved in genome projects, including technologies for collecting them. 799 Enderle / Introduction to Biomedical Engineering 2nd ed. Final Proof 5.2.2005 11:58am page 800 800 CHAPTER 13 GENOMICS AND BIOINFORMATICS & Describe practical applications and uses of genomic data. & Understand the major topics in the field of bioinformatics and DNA sequence analysis. & Use key bioinformatics databases and web resources. 13.1 INTRODUCTION In April 2003, sequencing of all three billion nucleotides in the human genome was declared complete. This landmark of modern science brought with it high hopes for the understanding and treatment of human genetic disorders. There is plenty of evidence to suggest that the hopes will become reality—1631 human genetic diseases are now associated with known DNA sequences, compared to the less than 100 that were known at the initiation of the Human Genome Project (HGP) in 1990. -
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. -
Genetic Effects on Microsatellite Diversity in Wild Emmer Wheat (Triticum Dicoccoides) at the Yehudiyya Microsite, Israel
Heredity (2003) 90, 150–156 & 2003 Nature Publishing Group All rights reserved 0018-067X/03 $25.00 www.nature.com/hdy Genetic effects on microsatellite diversity in wild emmer wheat (Triticum dicoccoides) at the Yehudiyya microsite, Israel Y-C Li1,3, T Fahima1,MSRo¨der2, VM Kirzhner1, A Beiles1, AB Korol1 and E Nevo1 1Institute of Evolution, University of Haifa, Mount Carmel, Haifa 31905, Israel; 2Institute for Plant Genetics and Crop Plant Research, Corrensstrasse 3, 06466 Gatersleben, Germany This study investigated allele size constraints and clustering, diversity. Genome B appeared to have a larger average and genetic effects on microsatellite (simple sequence repeat number (ARN), but lower variance in repeat number 2 repeat, SSR) diversity at 28 loci comprising seven types of (sARN), and smaller number of alleles per locus than genome tandem repeated dinucleotide motifs in a natural population A. SSRs with compound motifs showed larger ARN than of wild emmer wheat, Triticum dicoccoides, from a shade vs those with perfect motifs. The effects of replication slippage sun microsite in Yehudiyya, northeast of the Sea of Galilee, and recombinational effects (eg, unequal crossing over) on Israel. It was found that allele distribution at SSR loci is SSR diversity varied with SSR motifs. Ecological stresses clustered and constrained with lower or higher boundary. (sun vs shade) may affect mutational mechanisms, influen- This may imply that SSR have functional significance and cing the level of SSR diversity by both processes. natural constraints. -
Gene Prediction and Genome Annotation
A Crash Course in Gene and Genome Annotation Lieven Sterck, Bioinformatics & Systems Biology VIB-UGent [email protected] ProCoGen Dissemination Workshop, Riga, 5 nov 2013 “Conifer sequencing: basic concepts in conifer genomics” “This Project is financially supported by the European Commission under the 7th Framework Programme” Genome annotation: finding the biological relevant features on a raw genomic sequence (in a high throughput manner) ProCoGen Dissemination Workshop, Riga, 5 nov 2013 Thx to: BSB - annotation team • Lieven Sterck (Ectocarpus, higher plants, conifers, … ) • Yao-cheng Lin (Fungi, conifers, …) • Stephane Rombauts (green alga, mites, …) • Bram Verhelst (green algae) • Pierre Rouzé • Yves Van de Peer ProCoGen Dissemination Workshop, Riga, 5 nov 2013 Annotation experience • Plant genomes : A.thaliana & relatives (e.g. A.lyrata), Poplar, Physcomitrella patens, Medicago, Tomato, Vitis, Apple, Eucalyptus, Zostera, Spruce, Oak, Orchids … • Fungal genomes: Laccaria bicolor, Melampsora laricis- populina, Heterobasidion, other basidiomycetes, Glomus intraradices, Pichia pastoris, Geotrichum Candidum, Candida ... • Algal genomes: Ostreococcus spp, Micromonas, Bathycoccus, Phaeodactylum (and other diatoms), E.hux, Ectocarpus, Amoebophrya … • Animal genomes: Tetranychus urticae, Brevipalpus spp (mites), ... ProCoGen Dissemination Workshop, Riga, 5 nov 2013 Why genome annotation? • Raw sequence data is not useful for most biologists • To be meaningful to them it has to be converted into biological significant knowledge -
Small Variants Frequently Asked Questions (FAQ) Updated September 2011
Small Variants Frequently Asked Questions (FAQ) Updated September 2011 Summary Information for each Genome .......................................................................................................... 3 How does Complete Genomics map reads and call variations? ........................................................................... 3 How do I assess the quality of a genome produced by Complete Genomics?................................................ 4 What is the difference between “Gross mapping yield” and “Both arms mapped yield” in the summary file? ............................................................................................................................................................................. 5 What are the definitions for Fully Called, Partially Called, Half-Called and No-Called?............................ 5 In the summary-[ASM-ID].tsv file, how is the number of homozygous SNPs calculated? ......................... 5 In the summary-[ASM-ID].tsv file, how is the number of heterozygous SNPs calculated? ....................... 5 In the summary-[ASM-ID].tsv file, how is the total number of SNPs calculated? .......................................... 5 In the summary-[ASM-ID].tsv file, what regions of the genome are included in the “exome”? .............. 6 In the summary-[ASM-ID].tsv file, how is the number of SNPs in the exome calculated? ......................... 6 In the summary-[ASM-ID].tsv file, how are variations in potentially redundant regions of the genome counted? ..................................................................................................................................................................... -
Single Nucleotide Polymorphism (SNP)
Aquaculture Genome Technologies Zhanjiang (John) Liu Copyright © 2007 by Blackwell Publishing Chapter 6 Single Nucleotide Polymorphism (SNP) Zhanjiang Liu Single nucleotide polymorphism (SNP) describes polymorphisms caused by point mutations that give rise to different alleles containing alternative bases at a given nucleotide position within a locus. Such sequence differences due to base substitu- tions have been well characterized since the beginning of DNA sequencing in 1977, but the ability to genotype SNPs rapidly in large numbers of samples was not possible until several major technological advances in the late 1990s. With the development of the TaqMan technology, gene chip technology, pyrosequencing, and MALDI-TOF, which is matrix-assisted laser desorption ionization-time of flight mass spectrometry (Haff et al. 1997, Tost et al. 2005), SNPs are again becoming a focal point in molecular marker development because they are the most abundant polymorphism in any organ- ism (as shown in Table 6.1), adaptable to automation, and reveal hidden polymor- phism not detected with other markers and methods. SNP markers are regarded by many as the projected markers of choice for the future. In this chapter, I will summa- rize methods for SNP discovery, review the traditional approaches for SNP genotyp- ing and their principles, present several major platforms for SNP genotyping using recently developed technologies, and discuss the pros and cons of SNP markers for aquaculture genome research. What Are SNP Markers and Why Are They the Future Markers of Choice? SNP can be defined as base variation at any site of the genome among individuals, or an alternative base at a given DNA site (Figure 6.1). -
Genetic, Epidemiological and Biological Analysis of Interleukin-10
Genes and Immunity (2009) 10, 174–180 & 2009 Macmillan Publishers Limited All rights reserved 1466-4879/09 $32.00 www.nature.com/gene ORIGINAL ARTICLE Genetic, epidemiological and biological analysis of interleukin-10 promoter single-nucleotide polymorphisms suggests a definitive role for À819C/T in leprosy susceptibility AC Pereira1,5, VN Brito-de-Souza1,5, CC Cardoso2, IMF Dias-Baptista1, FPC Parelli1,3, J Venturini1,3, FR Villani-Moreno1, AG Pacheco4 and MO Moraes2 1Instituto Lauro de Souza Lima, Bauru, Sa˜o Paulo, Brazil; 2Laborato´rio de Hansenı´ase, Departamento de Micobacterioses, Instituto Oswaldo Cruz, Rio de Janeiro, Brazil; 3Tropical Diseases Area, Botucatu Medical School, Sao Paulo State University, UNESP, Botucatu, Sa˜o Paulo, Brazil and 4Departamento de Epidemiologia e Me´todos Quantitativos em Sau´de (DEMQS), Escola Nacional de Sau´de Pu´blica (ENSP)/PROCC, FIOCRUZ, Rio de Janeiro, Brazil Leprosy is a complex infectious disease influenced by genetic and environmental factors. The genetic contributing factors are considered heterogeneous and several genes have been consistently associated with susceptibility like PARK2, tumor necrosis factor (TNF), lymphotoxin-a (LTA) and vitamin-D receptor (VDR). Here, we combined a case–control study (374 patients and 380 controls), with meta-analysis (5 studies; 2702 individuals) and biological study to test the epidemiological and physiological relevance of the interleukin-10 (IL-10) genetic markers in leprosy. We observed that the À819T allele is associated with leprosy susceptibility either in the case–control or in the meta-analysis studies. Haplotypes combining promoter single-nucleotide polymorphisms also implicated a haplotype carrying the À819T allele in leprosy susceptibility (odds ratio (OR) ¼ 1.40; P ¼ 0.01). -
Epigenetics Analysis and Integrated Analysis of Multiomics Data, Including Epigenetic Data, Using Artificial Intelligence in the Era of Precision Medicine
biomolecules Review Epigenetics Analysis and Integrated Analysis of Multiomics Data, Including Epigenetic Data, Using Artificial Intelligence in the Era of Precision Medicine Ryuji Hamamoto 1,2,*, Masaaki Komatsu 1,2, Ken Takasawa 1,2 , Ken Asada 1,2 and Syuzo Kaneko 1 1 Division of Molecular Modification and Cancer Biology, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan; [email protected] (M.K.); [email protected] (K.T.); [email protected] (K.A.); [email protected] (S.K.) 2 Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan * Correspondence: [email protected]; Tel.: +81-3-3547-5271 Received: 1 December 2019; Accepted: 27 December 2019; Published: 30 December 2019 Abstract: To clarify the mechanisms of diseases, such as cancer, studies analyzing genetic mutations have been actively conducted for a long time, and a large number of achievements have already been reported. Indeed, genomic medicine is considered the core discipline of precision medicine, and currently, the clinical application of cutting-edge genomic medicine aimed at improving the prevention, diagnosis and treatment of a wide range of diseases is promoted. However, although the Human Genome Project was completed in 2003 and large-scale genetic analyses have since been accomplished worldwide with the development of next-generation sequencing (NGS), explaining the mechanism of disease onset only using genetic variation has been recognized as difficult. Meanwhile, the importance of epigenetics, which describes inheritance by mechanisms other than the genomic DNA sequence, has recently attracted attention, and, in particular, many studies have reported the involvement of epigenetic deregulation in human cancer. -
The Economic Impact and Functional Applications of Human Genetics and Genomics
The Economic Impact and Functional Applications of Human Genetics and Genomics Commissioned by the American Society of Human Genetics Produced by TEConomy Partners, LLC. Report Authors: Simon Tripp and Martin Grueber May 2021 TEConomy Partners, LLC (TEConomy) endeavors at all times to produce work of the highest quality, consistent with our contract commitments. However, because of the research and/or experimental nature of this work, the client undertakes the sole responsibility for the consequence of any use or misuse of, or inability to use, any information or result obtained from TEConomy, and TEConomy, its partners, or employees have no legal liability for the accuracy, adequacy, or efficacy thereof. Acknowledgements ASHG and the project authors wish to thank the following organizations for their generous support of this study. Invitae Corporation, San Francisco, CA Regeneron Pharmaceuticals, Inc., Tarrytown, NY The project authors express their sincere appreciation to the following indi- viduals who provided their advice and input to this project. ASHG Government and Public Advocacy Committee Lynn B. Jorde, PhD ASHG Government and Public Advocacy Committee (GPAC) Chair, President (2011) Professor and Chair of Human Genetics George and Dolores Eccles Institute of Human Genetics University of Utah School of Medicine Katrina Goddard, PhD ASHG GPAC Incoming Chair, Board of Directors (2018-2020) Distinguished Investigator, Associate Director, Science Programs Kaiser Permanente Northwest Melinda Aldrich, PhD, MPH Associate Professor, Department of Medicine, Division of Genetic Medicine Vanderbilt University Medical Center Wendy Chung, MD, PhD Professor of Pediatrics in Medicine and Director, Clinical Cancer Genetics Columbia University Mira Irons, MD Chief Health and Science Officer American Medical Association Peng Jin, PhD Professor and Chair, Department of Human Genetics Emory University Allison McCague, PhD Science Policy Analyst, Policy and Program Analysis Branch National Human Genome Research Institute Rebecca Meyer-Schuman, MS Human Genetics Ph.D. -
Application of NGS Technology in Understanding the Pathology of Autoimmune Diseases
Journal of Clinical Medicine Review Application of NGS Technology in Understanding the Pathology of Autoimmune Diseases Anna Wajda 1 , Larysa Sivitskaya 2,* and Agnieszka Paradowska-Gorycka 1 1 Department of Molecular Biology, National Institute of Geriatrics, Rheumatology and Rehabilitation, 02-637 Warsaw, Poland; [email protected] (A.W.); [email protected] (A.P.-G.) 2 Institute of Genetics and Cytology, National Academy of Sciences of Belarus, 220072 Minsk, Belarus * Correspondence: [email protected] Abstract: NGS technologies have transformed clinical diagnostics and broadly used from neonatal emergencies to adult conditions where the diagnosis cannot be made based on clinical symptoms. Autoimmune diseases reveal complicate molecular background and traditional methods could not fully capture them. Certainly, NGS technologies meet the needs of modern exploratory research, diagnostic and pharmacotherapy. Therefore, the main purpose of this review was to briefly present the application of NGS technology used in recent years in the understanding of autoimmune diseases paying particular attention to autoimmune connective tissue diseases. The main issues are presented in four parts: (a) panels, whole-genome and -exome sequencing (WGS and WES) in diagnostic, (b) Human leukocyte antigens (HLA) as a diagnostic tool, (c) RNAseq, (d) microRNA and (f) microbiome. Although all these areas of research are extensive, it seems that epigenetic impact on the development of systemic autoimmune diseases will set trends for future studies on this area. Citation: Wajda, A.; Sivitskaya, L.; Keywords: next-generation sequencing; autoimmune diseases; autoimmune connective tissue dis- Paradowska-Gorycka, A. Application eases; HLA; microRNA; microbiome of NGS Technology in Understanding the Pathology of Autoimmune Diseases. J. Clin. -
IMGT-Choreography for Immunogenetics and Immunoinformatics
In Silico Biology 5 (2005) 45–60 45 IOS Press IMGT-Choreography for Immunogenetics and Immunoinformatics Marie-Paule Lefranc∗, Oliver Clement,´ Quentin Kaas, Elodie Duprat, Patrick Chastellan, Isabelle Coelho, Kora Combres, Chantal Ginestoux, Veronique´ Giudicelli, Denys Chaume and Gerard´ Lefranc IMGT, the international ImMunoGeneTics information system , Universite´ Montpellier II, Laboratoire d’ImmunoGen´ etique´ Moleculaire´ LIGM, UPR CNRS 1142, Institut de Gen´ etique´ Humaine IGH, 141 rue de la Cardonille, 34396 Montpellier Cedex 5, France Tel.: +33 4 99 61 99 65; Fax: +33 4 99 61 99 01 Edited by H. Michael; received 11 September 2004; revised and accepted 14 December 2004; published 24 December 2004 ABSTRACT: IMGT, the international ImMunoGeneTics information system (http://imgt.cines.fr), was created in 1989 at Montpellier, France. IMGT is a high quality integrated knowledge resource specialized in immunoglobulins (IG), T cell receptors (TR), major histocompatibility complex (MHC) of human and other vertebrates, and related proteins of the immune system (RPI) which belong to the immunoglobulin superfamily (IgSF) and MHC superfamily (MhcSF). IMGT provides a common access to standardized data from genome, proteome, genetics and three-dimensional structures. The accuracy and the consistency of IMGT data are based on IMGT-ONTOLOGY, a semantic specification of terms to be used in immunogenetics and immunoinformatics. IMGT-ONTOLOGY has been formalized using XML Schema (IMGT-ML) for interoperability with other information systems. We are developing Web services to automatically query IMGT databases and tools. This is the first step towards IMGT-Choreography which will trigger and coordinate dynamic interactions between IMGT Web services to process complex significant biological and clinical requests. -
Multiple Sclerosis: Shall We Target CD33?
G C A T T A C G G C A T genes Article Multiple Sclerosis: Shall We Target CD33? Vasileios Siokas 1, Zisis Tsouris 1, Athina-Maria Aloizou 1 , Christos Bakirtzis 2, Ioannis Liampas 1 , Georgios Koutsis 3 , Maria Anagnostouli 4 , Dimitrios P. Bogdanos 5, Nikolaos Grigoriadis 2, Georgios M. Hadjigeorgiou 1,6 and Efthimios Dardiotis 1,* 1 Laboratory of Neurogenetics, Department of Neurology, University Hospital of Larissa, Faculty of Medicine, School of Health Sciences, University of Thessaly, 41110 Larissa, Greece; [email protected] (V.S.); [email protected] (Z.T.); [email protected] (A.-M.A.); [email protected] (I.L.); [email protected] (G.M.H.) 2 Multiple Sclerosis Center, B’ Department of Neurology, AHEPA University Hospital, Aristotle University of Thessaloniki, GR54636 Thessaloniki, Greece; [email protected] (C.B.); [email protected] (N.G.) 3 Neurogenetics Unit, 1st Department of Neurology, Eginition Hospital, School of Medicine, National and Kapodistrian University of Athens, Vassilissis Sofias 72-74 Ave, 11528 Athens, Greece; [email protected] 4 Multiple Sclerosis and Demyelinating Diseases Unit and Immunogenetics Laboratory, 1st Department of Neurology, Eginition Hospital, School of Medicine, National and Kapodistrian University of Athens, 115 28 Athens, Greece; [email protected] 5 Department of Rheumatology and Clinical Immunology, Faculty of Medicine, School of Health Sciences, University of Thessaly, 41110 Larissa, Greece; [email protected] 6 Department of Neurology, Medical School, University of Cyprus, 1678 Nicosia, Cyprus * Correspondence: [email protected]; Tel.: +30-241-350-1137 Received: 23 September 2020; Accepted: 5 November 2020; Published: 12 November 2020 Abstract: Background: Multiple sclerosis (MS) is a chronic disease of the central nervous system (CNS).