DOCSLIB.ORG

Mouse Genome Database (MGD): Knowledgebase for Mouse- Human Comparative Biology

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Mouse Genome Database (MGD): Knowledgebase for Mouse- Human Comparative Biology The Jackson Laboratory The Mouseion at the JAXlibrary Faculty Research 2021 Faculty Research 1-8-2021 Mouse Genome Database (MGD): Knowledgebase for mouse- human comparative biology. Judith A. Blake Richard M. Baldarelli James A. Kadin Joel E Richardson Cynthia Smith See next page for additional authors Follow this and additional works at: https://mouseion.jax.org/stfb2021 Part of the Life Sciences Commons, and the Medicine and Health Sciences Commons Authors Judith A. Blake, Richard M. Baldarelli, James A. Kadin, Joel E Richardson, Cynthia Smith, Carol J Bult, and Mouse Genome Database Group Published online 24 November 2020 Nucleic Acids Research, 2021, Vol. 49, Database issue D981–D987 doi: 10.1093/nar/gkaa1083 Mouse Genome Database (MGD): Knowledgebase for mouse–human comparative biology Judith A. Blake *, Richard Baldarelli, James A. Kadin, Joel E. Richardson, Cynthia L. Smith , Carol J. Bult and the Mouse Genome Database Group The Jackson Laboratory, Bar Harbor, ME, USA Downloaded from https://academic.oup.com/nar/article/49/D1/D981/5999894 by Jackson Laboratory user on 28 January 2021 Received September 15, 2020; Revised October 18, 2020; Editorial Decision October 19, 2020; Accepted November 22, 2020 ABSTRACT lying human biology and disease. MGD serves three ma- jor user communities: (i) biomedical researchers who use The Mouse Genome Database (MGD; http://www. mouse experimentation to investigate genetic and molecu- informatics.jax.org) is the community model organ- lar principles of biology and disease processes, (ii) transla- ism knowledgebase for the laboratory mouse, a tional scientists who use the laboratory mouse to model hu- widely used animal model for comparative studies man disease and (iii) bioinformaticians/computational bi- of the genetic and genomic basis for human health ologists who use the rich integrated data MGD provides to and disease. MGD is the authoritative source for bio- develop algorithms and bioinformatics tools for data anal- logical reference data related to mouse genes, gene ysis and interpretation. MGD processes and data support functions, phenotypes and mouse models of human and comply with FAIR principles (2) with a variety of for- disease. MGD is the primary source for official gene, mats for data distribution. allele, and mouse strain nomenclature based on the MGD maintains a comprehensive catalog of mouse genes and genome features connected to genomic sequence data guidelines set by the International Committee on and biological annotations. As the community model or- Standardized Nomenclature for Mice. MGD’s biocu- ganism knowledgebase for the laboratory mouse, MGD ration scientists curate information from the biomed- contains comprehensive information about mouse gene ical literature and from large and small datasets con- function, genotype-to-phenotype annotations, and mouse tributed directly by investigators. In this report we de- models of human disease. Annotations include: (i) molecu- scribe significant enhancements to the content and lar function, biological process and cellular location of gene interfaces at MGD, including (i) improvements in the products using terms and relations from the Gene Ontol- Multi Genome Viewer for exploring the genomes of ogy (GO) (3), (ii) mouse mutations, variants and human dis- multiple mouse strains, (ii) inclusion of many more ease models with genotypes annotated to the Mammalian mouse strains and new mouse strain pages with ex- Phenotype Ontology (MP) (4) and the Disease Ontology tended query options and (iii) integration of extensive (DO) (5) and (iii) standardized nomenclature and identi- fiers for mouse gene names, symbols, alleles and strains. The data about mouse strain variants. We also describe rigorous application of nomenclature and annotation stan- improvements to the efficiency of literature curation dards in MGD ensures that the information in the resource processes and the implementation of an information is curated consistently to support robust and comprehen- portal focused on mouse models and genes for the sive data retrieval for accurate identification of genes that study of COVID-19. share biological properties and data mining for knowledge discovery (Table 1). INTRODUCTION MGD is a core resource within the Mouse Genome Informatics (MGI) consortium (http://www.informatics. As the cost of genome-scale sequencing continues to de- jax.org). Other MGI consortium databases include the crease and new technologies for genome editing become Gene Expression Database (GXD) (6), the Mouse Mod- widely adopted, the laboratory mouse is more important els of Human Cancer Database (MMHC; formerly the than ever as a model system for understanding the bio- Mouse Tumor Biology database) (7), the Gene Ontol- logical significance of human genetic variation and forad- ogy project (3), MouseMine (8), the International Mouse vancing the emergence of genomic medicine. The Mouse Strain Resource (IMSR) (9) and the CrePortal database Genome Database (MGD) (1) has a unique and strategic of recombinase expressing mice (http://www.informatics. role as a community resource for facilitating the use of the jax.org/home/recombinase). Data included in all resources laboratory mouse for understanding the genomics under- *To whom correspondence should be addressed. Tel: +1 207 288 6248; Email: [email protected] C The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. D982 Nucleic Acids Research, 2021, Vol. 49, Database issue Table 1. Data for which MGD serves as the authoritative source Data type Community relationship Unified genome feature catalog MGD compares/integrates predictions from Ensembl, NCBI, Havana/Vega, produces unified catalog used by NCBI, IMPC. Gene Ontology (GO) annotations for MGD does primary curation, integrates data from others, provides definitive mouse GO annotation sets mouse to GO site. Mouse Phenotype annotations MGD does primary curation & integrates data from publications & large scale projects. Mouse models of human diseases MGD does primary mouse model curation using disease terms & human gene associations from OMIM and NCBI. Gene-to-nucleotide sequence association Co-curation with MGA (Mouse Genome Annotation) group. Gene-to-protein sequence association Co-curation with UniProt and Protein Ontology. Mammalian Phenotype (MP) Ontology MGD develops & distributes MP. MP is actively used by many groups, e.g., RGD, MRC Harwell, Sanger, IMPC, etc. Downloaded from https://academic.oup.com/nar/article/49/D1/D981/5999894 by Jackson Laboratory user on 28 January 2021 Symbols & names for genes & genome MGD provides access to International Nomenclature guides, implements policies, coordinates with features human and rat groups. Strain designations MGD assigns official nomenclature; provides to repositories. hosted at the MGI website are obtained through a combina- with use of ‘canonical’ identifiers to assert homology be- tion of expert curation of the biomedical literature and au- tween genes in strains within a species. The interface di- tomated or semi-automated processing of data sets down- rectly supports viewing and navigating complex orthol- loaded from more than fifty other data resources. A sum- ogy relationships. mary of the current content of MGD is presented in Table • Uses orthology relationships to infer paralogs, which are 2. used to return additional genes in certain contexts, and In this report we describe significant enhancements to to draw additional connections between displayed genes. MGD, including two new graphical user interfaces: (i) im- Users can turn this feature on/off. provements to the Multiple Genome Viewer for exploring • The user has many controls to adjust the display, such the genomes of multiple mouse strains (ii) enhancement and as specifying which gene labels are displayed, whether to inclusion of information of now over 64 000 strains of mice display all transcripts or just one representative per gene, including collaborative cross strains and (iii) incorporation the ability to download the current display as an PNG or of SNP data with extensive updates in query and visualiza- SVG file, and more. tion of variant × strain data. Other improvements include improvements to literature curation processes, and specific New mouse strain data pages access to data about mouse models for the study of coron- avirus infections. New mouse strain data pages are now available, including information for over 64 000 inbred, mutant congenic and co-isogenic strains, Collaborative Cross strains, recombi- NEW FEATURES AND CURATION WORKFLOW EN- nant inbred and other mouse strain types (Figure 2). The HANCEMENTS newly revamped Strain and SNPs mini-home page (http: //www.informatics.jax.org/home/strain) includes a search Enhancements to the multiple sequence viewer form for mouse strains by nomenclature or by strain at- The Multiple Genome Viewer (MGV, http://www. tribute, quick links to lists of strain collections such as the informatics.jax.org/mgv) is a web-based browser de- Collaborative Cross, and links to tools and strain resources. signed for navigating and comparing multiple related Strain detail pages show standardized nomenclature, genomes simultaneously. The first release of MGV in unique identifiers,
Load more

Recommended publications
  • Genome Analysis and Knowledge
    Dahary et al. BMC Medical Genomics (2019) 12:200 https://doi.org/10.1186/s12920-019-0647-8 SOFTWARE Open Access Genome analysis and knowledge-driven variant interpretation with TGex Dvir Dahary1*, Yaron Golan1, Yaron Mazor1, Ofer Zelig1, Ruth Barshir2, Michal Twik2, Tsippi Iny Stein2, Guy Rosner3,4, Revital Kariv3,4, Fei Chen5, Qiang Zhang5, Yiping Shen5,6,7, Marilyn Safran2, Doron Lancet2* and Simon Fishilevich2* Abstract Background: The clinical genetics revolution ushers in great opportunities, accompanied by significant challenges. The fundamental mission in clinical genetics is to analyze genomes, and to identify the most relevant genetic variations underlying a patient’s phenotypes and symptoms. The adoption of Whole Genome Sequencing requires novel capacities for interpretation of non-coding variants. Results: We present TGex, the Translational Genomics expert, a novel genome variation analysis and interpretation platform, with remarkable exome analysis capacities and a pioneering approach of non-coding variants interpretation. TGex’s main strength is combining state-of-the-art variant filtering with knowledge-driven analysis made possible by VarElect, our highly effective gene-phenotype interpretation tool. VarElect leverages the widely used GeneCards knowledgebase, which integrates information from > 150 automatically-mined data sources. Access to such a comprehensive data compendium also facilitates TGex’s broad variant annotation, supporting evidence exploration, and decision making. TGex has an interactive, user-friendly, and easy adaptive interface, ACMG compliance, and an automated reporting system. Beyond comprehensive whole exome sequence capabilities, TGex encompasses innovative non-coding variants interpretation, towards the goal of maximal exploitation of whole genome sequence analyses in the clinical genetics practice. This is enabled by GeneCards’ recently developed GeneHancer, a novel integrative and fully annotated database of human enhancers and promoters.
    [Show full text]
  • The Mouse Genome Database: Integration of and Access to Knowledge About the Laboratory Mouse Judith A
    D810–D817 Nucleic Acids Research, 2014, Vol. 42, Database issue Published online 26 November 2013 doi:10.1093/nar/gkt1225 The Mouse Genome Database: integration of and access to knowledge about the laboratory mouse Judith A. Blake*, Carol J. Bult, Janan T. Eppig, James A. Kadin and Joel E. Richardson The Mouse Genome Database Groupy Bioinformatics and Computational Biology, The Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04609, USA Received October 1, 2013; Revised November 4, 2013; Accepted November 5, 2013 ABSTRACT genes and as a comprehensive data integration site and repository for mouse genetic, genomic and phenotypic The Mouse Genome Database (MGD) (http://www. data derived from primary literature as well as from informatics.jax.org) is the community model major data providers (1,2). organism database resource for the laboratory The central mission of the MGD is to support the trans- mouse, a premier animal model for the study of lation of information from experimental mouse models to genetic and genomic systems relevant to human uncover the genetic basis of human diseases. As a highly biology and disease. MGD maintains a comprehen- curated and comprehensive model organism database, sive catalog of genes, functional RNAs and other MGD provides web and programmatic access to a genome features as well as heritable phenotypes complete catalog of mouse genes and genome features and quantitative trait loci. The genome feature including genomic sequence and variant information. catalog is generated by the integration of computa- MGD curates and maintains the comprehensive listing of functional annotations for mouse genes using Gene tional and manual genome annotations generated Ontology (GO) terms and contributes to the development by NCBI, Ensembl and Vega/HAVANA.
    [Show full text]
  • Mouse Genome Informatics (MGI) Resource: Genetic, Genomic, and Biological Knowledgebase for the Laboratory Mouse Janan T
    ILAR Journal, 2017, Vol. 58, No. 1, 17–41 doi: 10.1093/ilar/ilx013 Article Mouse Genome Informatics (MGI) Resource: Genetic, Genomic, and Biological Knowledgebase for the Laboratory Mouse Janan T. Eppig Janan T. Eppig, PhD, is Professor Emeritus at The Jackson Laboratory in Bar Harbor, Maine. Address correspondence to Dr. Janan T. Eppig, The Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04609 or email [email protected] Abstract The Mouse Genome Informatics (MGI) Resource supports basic, translational, and computational research by providing high-quality, integrated data on the genetics, genomics, and biology of the laboratory mouse. MGI serves a strategic role for the scientific community in facilitating biomedical, experimental, and computational studies investigating the genetics and processes of diseases and enabling the development and testing of new disease models and therapeutic interventions. This review describes the nexus of the body of growing genetic and biological data and the advances in computer technology in the late 1980s, including the World Wide Web, that together launched the beginnings of MGI. MGI develops and maintains a gold-standard resource that reflects the current state of knowledge, provides semantic and contextual data integration that fosters hypothesis testing, continually develops new and improved tools for searching and analysis, and partners with the scientific community to assure research data needs are met. Here we describe one slice of MGI relating to the development of community-wide large-scale mutagenesis and phenotyping projects and introduce ways to access and use these MGI data. References and links to additional MGI aspects are provided. Key words: database; genetics; genomics; human disease model; informatics; model organism; mouse; phenotypes Introduction strains and special purpose strains that have been developed The laboratory mouse is an essential model for understanding provide fertile ground for population studies and the potential human biology, health, and disease.
    [Show full text]
  • 22Q11.2 Duplications North Carolina, 27526, Ontario, USA Canada on P4N 6N5 Tel +1 (919) 567-8167 [email protected] Or [email protected]
    Support and Information Rare Chromosome Disorder Support Group The Stables, Station Road West, Oxted, Surrey RH8 9EE, United Kingdom Tel: +44(0)1883 723356 [email protected] I www.rarechromo.org Join Unique for family links, information and support. Unique is a charity without government funding, existing entirely on donations and grants. If you can, please make a donation via our website at www.rarechromo.org/donate Please help us to help you! Chromosome 22 Central www.c22c.org or c/o Murney Rinholm, c/o Stephanie St-Pierre, 7108 Partinwood Drive, 338 Spruce Street North, Fuquay-Varina, Timmins, 22q11.2 duplications North Carolina, 27526, Ontario, USA Canada ON P4N 6N5 Tel +1 (919) 567-8167 [email protected] or [email protected] Facebook www.facebook.com/groups/214854295210303 This guide was developed by Unique with generous support from the James Tudor Foundation. Unique lists external message boards and websites in order to be helpful to families looking for information and support. This does not imply that we endorse their content or have any responsibility for it. This information guide is not a substitute for personal medical advice. Families should consult a medically qualified clinician in all matters relating to genetic diagnosis, management and health. Information on genetic changes is a very fast-moving field and while the information in this guide is believed to be the best available at the time of publication, some facts may later change. Unique does its best to keep abreast of changing information and to review its published guides as needed. The guide was compiled by Unique and reviewed by Dr Melissa Carter, Clinical Geneticist specializing in developmental disabilities at The Hospital for Sick Children in Toronto, Canada , and by Professor Maj Hultén, Professor of Medical Genetics, University of Warwick, UK and Karolinska Institutet, Stockholm, Sweden.
    [Show full text]
  • LARGE Expression in Different Types of Muscular Dystrophies Other Than Dystroglycanopathy Burcu Balci-Hayta1*, Beril Talim2, Gulsev Kale2 and Pervin Dincer1
    Balci-Hayta et al. BMC Neurology (2018) 18:207 https://doi.org/10.1186/s12883-018-1207-0 RESEARCHARTICLE Open Access LARGE expression in different types of muscular dystrophies other than dystroglycanopathy Burcu Balci-Hayta1*, Beril Talim2, Gulsev Kale2 and Pervin Dincer1 Abstract Background: Alpha-dystroglycan (αDG) is an extracellular peripheral glycoprotein that acts as a receptor for both extracellular matrix proteins containing laminin globular domains and certain arenaviruses. An important enzyme, known as Like-acetylglucosaminyltransferase (LARGE), has been shown to transfer repeating units of -glucuronic acid-β1,3-xylose-α1,3- (matriglycan) to αDG that is required for functional receptor as an extracellular matrix protein scaffold. The reduction in the amount of LARGE-dependent matriglycan result in heterogeneous forms of dystroglycanopathy that is associated with hypoglycosylation of αDG and a consequent lack of ligand-binding activity. Our aim was to investigate whether LARGE expression showed correlation with glycosylation of αDG and histopathological parameters in different types of muscular dystrophies, except for dystroglycanopathies. Methods: The expression level of LARGE and glycosylation status of αDG were examined in skeletal muscle biopsies from 26 patients with various forms of muscular dystrophy [Duchenne muscular dystrophy (DMD), Becker muscular dystrophy (BMD), sarcoglycanopathy, dysferlinopathy, calpainopathy, and merosin and collagen VI deficient congenital muscular dystrophies (CMDs)] and correlation of results with different histopathological features was investigated. Results: Despite the fact that these diseases are not caused by defects of glycosyltransferases, decreased expression of LARGE was detected in many patient samples, partly correlating with the type of muscular dystrophy. Although immunolabelling of fully glycosylated αDG with VIA4–1 was reduced in dystrophinopathy patients, no significant relationship between reduction of LARGE expression and αDG hypoglycosylation was detected.
    [Show full text]
  • Genome-Wide Identification of Directed Gene Networks Using Large-Scale Population Genomics Data
    ARTICLE DOI: 10.1038/s41467-018-05452-6 OPEN Genome-wide identification of directed gene networks using large-scale population genomics data René Luijk1, Koen F. Dekkers1, Maarten van Iterson1, Wibowo Arindrarto 2, Annique Claringbould3, Paul Hop1, BIOS Consortium#, Dorret I. Boomsma4, Cornelia M. van Duijn5, Marleen M.J. van Greevenbroek6,7, Jan H. Veldink8, Cisca Wijmenga3, Lude Franke 3, Peter A.C. ’t Hoen 9, Rick Jansen 10, Joyce van Meurs11, Hailiang Mei2, P. Eline Slagboom1, Bastiaan T. Heijmans 1 & Erik W. van Zwet12 1234567890():,; Identification of causal drivers behind regulatory gene networks is crucial in understanding gene function. Here, we develop a method for the large-scale inference of gene–gene interactions in observational population genomics data that are both directed (using local genetic instruments as causal anchors, akin to Mendelian Randomization) and specific (by controlling for linkage disequilibrium and pleiotropy). Analysis of genotype and whole-blood RNA-sequencing data from 3072 individuals identified 49 genes as drivers of downstream transcriptional changes (Wald P <7×10−10), among which transcription factors were over- represented (Fisher’s P = 3.3 × 10−7). Our analysis suggests new gene functions and targets, including for SENP7 (zinc-finger genes involved in retroviral repression) and BCL2A1 (target genes possibly involved in auditory dysfunction). Our work highlights the utility of population genomics data in deriving directed gene expression networks. A resource of trans-effects for all 6600 genes with a genetic instrument can be explored individually using a web-based browser. 1 Molecular Epidemiology Section, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, Zuid-Holland 2333 ZC, The Netherlands.
    [Show full text]
  • Deep Evolutionary Analysis Reveals the Design Principles of Fold A
    RESEARCH ARTICLE Deep evolutionary analysis reveals the design principles of fold A glycosyltransferases Rahil Taujale1,2, Aarya Venkat3, Liang-Chin Huang1, Zhongliang Zhou4, Wayland Yeung1, Khaled M Rasheed4, Sheng Li4, Arthur S Edison1,2,3, Kelley W Moremen2,3, Natarajan Kannan1,3* 1Institute of Bioinformatics, University of Georgia, Athens, Georgia; 2Complex Carbohydrate Research Center, University of Georgia, Athens, Georgia; 3Department of Biochemistry and Molecular Biology, University of Georgia, Athens, Georgia; 4Department of Computer Science, University of Georgia, Athens, Georgia Abstract Glycosyltransferases (GTs) are prevalent across the tree of life and regulate nearly all aspects of cellular functions. The evolutionary basis for their complex and diverse modes of catalytic functions remain enigmatic. Here, based on deep mining of over half million GT-A fold sequences, we define a minimal core component shared among functionally diverse enzymes. We find that variations in the common core and emergence of hypervariable loops extending from the core contributed to GT-A diversity. We provide a phylogenetic framework relating diverse GT-A fold families for the first time and show that inverting and retaining mechanisms emerged multiple times independently during evolution. Using evolutionary information encoded in primary sequences, we trained a machine learning classifier to predict donor specificity with nearly 90% accuracy and deployed it for the annotation of understudied GTs. Our studies provide an evolutionary framework for investigating complex relationships connecting GT-A fold sequence, structure, function and regulation. *For correspondence: [email protected] Introduction Competing interests: The Complex carbohydrates make up a large bulk of the biomass of any living cell and play essential authors declare that no roles in biological processes ranging from cellular interactions, pathogenesis, immunity, quality con- competing interests exist.
    [Show full text]
  • Breeding Strategies for Maintaining Colonies of Laboratory Mice a Jackson Laboratory Resource Manual
    Breeding Strategies for Maintaining Colonies of Laboratory Mice A Jackson Laboratory Resource Manual This manual describes breeding strategies and techniques for maintaining colonies of laboratory mice. These techniques have been developed and used by The Jackson Laboratory for nearly 80 years. They are safe, reliable, economical, efficient, and ensure that the mouse strains produced are genetically well-defined. Cover Photos Front cover: JAX® Mice strain B6SJL-Tg(SOD1*G93A)1Gur/J (002726) with red plastic enrichment toy. This strain is a model of amyotrophic lateral sclerosis (ALS), or Lou Gehrig’s disease. (left), JAX® Mice strain C57BL/6J (000664), our most popular strain, with litter of nine-day old pups.(middle), A technician at The Jackson Laboratory—West working with mice in one of our production rooms. (right). ©2009 The Jackson Laboratory Table of Contents Introduction .....................................................................................................................................1 Fundamentals of Mouse Reproduction ........................................................................................2 Mouse Breeding Performance .......................................................................................................4 Breeding Performance Factors ...............................................................................................4 Optimizing Breeding Performance ........................................................................................5 Breeding Schemes ............................................................................................................................7
    [Show full text]
  • Unlocking the Potential of Public Available Gene Expression Data for Large-Scale Analysis
    Faculty of Science and Bio-engineering Sciences Department of Computer Science Computational Modeling Lab Unlocking the potential of public available gene expression data for large-scale analysis Jonatan Taminau Dissertation submitted for the degree of Doctor of Philosophy in Sciences Supervisor: Prof. Dr. Ann Nowe´ Print: Silhouet, Maldegem ©2012 Jonatan Taminau 2012 Uitgeverij VUBPRESS Brussels University Press VUBPRESS is an imprint of ASP nv (Academic and Scientific Publishers nv) Ravensteingalerij 28 B-1000 Brussels Tel. +32 (0)2 289 26 50 Fax +32 (0)2 289 26 59 E-mail: [email protected] www.vubpress.be ISBN 978 90 5487 993 0 NUR 910 Legal Deposit D/2012/11.161/011 All rights reserved. No parts of this book may be reproduced or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the author. Voor Maaike en Hanne Committee members: Internal members: Prof. Dr. Ann Nowe´ Vrije Universiteit Brussel Prof. Dr. Bernard Manderick Vrije Universiteit Brussel Prof. Dr. Dominique Maes Vrije Universiteit Brussel External members: Prof. Dr. Hugues Bersini Universit´eLibre de Bruxelles Prof. Dr. Jacques De Greve` Universitair Ziekenhuis Brussel Dr. Willem Talloen Janssen Pharmaceutica NV, Beerse Dr. Benjamin Haibe-Kains Institut de Recherches Cliniques de Montr´eal Abstract After more than a decade of microarray gene expression research there is a vast amount of data publicly available through online repositories. It is clear that for the future the new challenges for this technology lie in the integration of this plethora of different data sets in order to obtain more robust, accurate and generalizable results.
    [Show full text]
  • Cell Specific Post-Translational Processing of Pikachurin, a Protein Involved in Retinal Synaptogenesis
    Cell Specific Post-Translational Processing of Pikachurin, A Protein Involved in Retinal Synaptogenesis Jianzhong Han*, Ellen Townes-Anderson Department of Neurology and Neuroscience, New Jersey Medical School, University of Medicine and Dentistry of New Jersey, Newark, New Jersey, United States of America Abstract Pikachurin is a recently identified, highly conserved, extracellular matrix-like protein. Murine pikachurin has 1,017 amino acids (,110 kDa), can bind to a-dystroglycan, and has been found to localize mainly in the synaptic cleft of photoreceptor ribbon synapses. Its knockout selectively disrupts synaptogenesis between photoreceptor and bipolar cells. To further characterize this synaptic protein, we used an antibody raised against the N-terminal of murine pikachurin on Western blots of mammalian and amphibian retinas and found, unexpectedly, that a low weight ,60-kDa band was the predominant signal for endogenous pikachurin. This band was predicted to be an N-terminal product of post-translational cleavage of pikachurin. A similar sized protein was also detected in human Y79 retinoblastoma cells, a cell line with characteristics of photoreceptor cells. In Y79 cells, endogenous pikachurin immunofluorescence was found on the cell surface of living cells. The expression of the N-fragment was not significantly affected by dystroglycan overexpression in spite of the biochemical evidence for pikachurin-a-dystroglycan binding. The presence of a corresponding endogenous C-fragment was not determined because of the lack of a suitable antibody. However, a protein of ,65 kDa was detected in Y79 cells expressing recombinant pikachurin with a C-terminal tag. In contrast, in QBI-HEK 293A cells, whose endogenous pikachurin protein level is negligible, recombinant pikachurin did not appear to be cleaved.
    [Show full text]
  • Defining Functional DNA Elements in the Human Genome Manolis Kellisa,B,1,2, Barbara Woldc,2, Michael P
    PERSPECTIVE PERSPECTIVE Defining functional DNA elements in the human genome Manolis Kellisa,b,1,2, Barbara Woldc,2, Michael P. Snyderd,2, Bradley E. Bernsteinb,e,f,2, Anshul Kundajea,b,3, Georgi K. Marinovc,3, Lucas D. Warda,b,3, Ewan Birneyg, Gregory E. Crawfordh, Job Dekkeri, Ian Dunhamg, Laura L. Elnitskij, Peggy J. Farnhamk, Elise A. Feingoldj, Mark Gersteinl, Morgan C. Giddingsm, David M. Gilbertn, Thomas R. Gingeraso, Eric D. Greenj, Roderic Guigop, Tim Hubbardq, Jim Kentr, Jason D. Liebs, Richard M. Myerst, Michael J. Pazinj,BingRenu, John A. Stamatoyannopoulosv, Zhiping Wengi, Kevin P. Whitew, and Ross C. Hardisonx,1,2 aComputer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139; bBroad Institute, Cambridge, MA 02139; cDivision of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125; dDepartment of Genetics, Stanford University, Stanford, CA 94305; eHarvard Medical School and fMassachusetts General Hospital, Boston, MA 02114; gEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, Cambridge CB10 1SD, United Kingdom; hMedical Genetics, Duke University, Durham, NC 27708; iProgram in Systems Biology, University of Massachusetts Medical School, Worcester, MA 01605; jNational Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892; kBiochemistry and Molecular Biology, University of Southern California, Los Angeles, CA 90089; lProgram in Computational Biology and Bioinformatics, Yale University,
    [Show full text]
  • Large Domains of Heterochromatin Direct the Formation of Short Mitotic
    RESEARCH ARTICLE Large domains of heterochromatin direct the formation of short mitotic chromosome loops Maximilian H Fitz-James1, Pin Tong1, Alison L Pidoux1, Hakan Ozadam2, Liyan Yang2, Sharon A White1, Job Dekker2,3, Robin C Allshire1* 1Wellcome Centre for Cell Biology and Institute of Cell Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom; 2Program in Systems Biology, Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, United States; 3Howard Hughes Medical Institute, Chevy Chase, United States Abstract During mitosis chromosomes reorganise into highly compact, rod-shaped forms, thought to consist of consecutive chromatin loops around a central protein scaffold. Condensin complexes are involved in chromatin compaction, but the contribution of other chromatin proteins, DNA sequence and histone modifications is less understood. A large region of fission yeast DNA inserted into a mouse chromosome was previously observed to adopt a mitotic organisation distinct from that of surrounding mouse DNA. Here, we show that a similar distinct structure is common to a large subset of insertion events in both mouse and human cells and is coincident with the presence of high levels of heterochromatic H3 lysine nine trimethylation (H3K9me3). Hi-C and microscopy indicate that the heterochromatinised fission yeast DNA is organised into smaller chromatin loops than flanking euchromatic mouse chromatin. We conclude that heterochromatin alters chromatin loop size, thus contributing to the distinct appearance of heterochromatin on mitotic chromosomes. *For correspondence: [email protected] Introduction During mitosis, chromatin is dramatically reorganised and compacted to form individual rod-shaped Competing interest: See mitotic chromosomes that allow for proper segregation of the genetic material (Belmont, 2006).
    [Show full text]