Lack of Trna-I6a Modification Causes Mitochondrial-Like Metabolic Deficiency in S
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A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
Ehrlichia Chaffeensis
RESEARCH ARTICLE Ehrlichia chaffeensis TRP47 enters the nucleus via a MYND-binding domain-dependent mechanism and predominantly binds enhancers of host genes associated with signal transduction, cytoskeletal organization, and immune response a1111111111 1 1 2 1 1 a1111111111 Clayton E. KiblerID , Sarah L. Milligan , Tierra R. Farris , Bing Zhu , Shubhajit Mitra , Jere a1111111111 W. McBride1,2,3,4,5* a1111111111 a1111111111 1 Department of Pathology, University of Texas Medical Branch, Galveston, Texas, United States of America, 2 Department of Microbiology and Immunology, University of Texas Medical Branch, Galveston, Texas, United States of America, 3 Center for Biodefense and Emerging Infectious Diseases, University of Texas Medical Branch, Galveston, Texas, United States of America, 4 Sealy Center for Vaccine Development, University of Texas Medical Branch, Galveston, Texas, United States of America, 5 Institute for Human Infections and Immunity, University of Texas Medical Branch, Galveston, Texas, United States of OPEN ACCESS America Citation: Kibler CE, Milligan SL, Farris TR, Zhu B, * [email protected] Mitra S, McBride JW (2018) Ehrlichia chaffeensis TRP47 enters the nucleus via a MYND-binding domain-dependent mechanism and predominantly binds enhancers of host genes associated with Abstract signal transduction, cytoskeletal organization, and immune response. PLoS ONE 13(11): e0205983. Ehrlichia chaffeensis is an obligately intracellular bacterium that establishes infection in https://doi.org/10.1371/journal.pone.0205983 mononuclear phagocytes through largely undefined reprogramming strategies including Editor: Gary M. Winslow, State University of New modulation of host gene transcription. In this study, we demonstrate that the E. chaffeensis York Upstate Medical University, UNITED STATES effector TRP47 enters the host cell nucleus and binds regulatory regions of host genes rele- Received: April 25, 2018 vant to infection. -
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Systematic Evaluation of Genes and Genetic Variants Associated with Type 1 Diabetes Susceptibility This information is current as Ramesh Ram, Munish Mehta, Quang T. Nguyen, Irma of September 23, 2021. Larma, Bernhard O. Boehm, Flemming Pociot, Patrick Concannon and Grant Morahan J Immunol 2016; 196:3043-3053; Prepublished online 24 February 2016; doi: 10.4049/jimmunol.1502056 Downloaded from http://www.jimmunol.org/content/196/7/3043 Supplementary http://www.jimmunol.org/content/suppl/2016/02/19/jimmunol.150205 Material 6.DCSupplemental http://www.jimmunol.org/ References This article cites 44 articles, 5 of which you can access for free at: http://www.jimmunol.org/content/196/7/3043.full#ref-list-1 Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision by guest on September 23, 2021 • No Triage! Every submission reviewed by practicing scientists • Fast Publication! 4 weeks from acceptance to publication *average Subscription Information about subscribing to The Journal of Immunology is online at: http://jimmunol.org/subscription Permissions Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Email Alerts Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2016 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. The Journal of Immunology Systematic Evaluation of Genes and Genetic Variants Associated with Type 1 Diabetes Susceptibility Ramesh Ram,*,† Munish Mehta,*,† Quang T. -
27Th Trna Conference-Abstractsbook-3
P1.1 The protein-only RNase P PRORP1 interacts with the nuclease MNU2 in Arabidopsis mitochondria G. Bonnard, M. Arrivé, A. Bouchoucha, A. Gobert, C. Schelcher, F. Waltz, P. Giegé Institut de biologie moléculaire des plantes, CNRS, Université de Strasbourg, Strasbourg, France The essential endonuclease activity that removes 5’ leader sequences from transfer RNA precursors is called RNase P. While ribonucleoprotein RNase P enzymes containing a ribozyme are found in all domains of life, another type of RNase P called “PRORP”, for “PROtein-only RNase P”, only composed of protein occurs in a wide variety of eukaryotes, in organelles and the nucleus. Although PRORP proteins function as single subunit enzymes in vitro, we find that PRORP1 occurs in protein complexes and is present in polysome fractions in Arabidopsis mitochondria. The analysis of immuno- precipitated protein complexes identifies proteins involved in mitochondrial gene expression processes. In particular, direct interaction is established between PRORP1 and MNU2 another mitochondrial nuclease involved in RNA 5’ processing. A specific domain of MNU2 and a conserved signature of PRORP1 are found to be directly accountable for this protein interaction. Altogether, results reveal the existence of an RNA 5’ maturation complex in Arabidopsis mitochondria and suggest that PRORP proteins might cooperate with other gene expression regulators for RNA maturation in vivo. 111 P1.2 CytoRP, a cytosolic RNase P to target TLS-RNA phytoviruses 1 1 2 1 A. Gobert , Y. Quan , I. Jupin , P. Giegé 1Institut de biologie moléculaire des plantes, CNRS, Université de Strasbourg, Strasbourg, France 1Institut Jacques Monod, CNRS, Université Paris Diderot, Paris, France In plants, PRORP enzymes are responsible for RNase P activity that involves the removal of the 5’ extremity of tRNA precursors. -
Content Based Search in Gene Expression Databases and a Meta-Analysis of Host Responses to Infection
Content Based Search in Gene Expression Databases and a Meta-analysis of Host Responses to Infection A Thesis Submitted to the Faculty of Drexel University by Francis X. Bell in partial fulfillment of the requirements for the degree of Doctor of Philosophy November 2015 c Copyright 2015 Francis X. Bell. All Rights Reserved. ii Acknowledgments I would like to acknowledge and thank my advisor, Dr. Ahmet Sacan. Without his advice, support, and patience I would not have been able to accomplish all that I have. I would also like to thank my committee members and the Biomed Faculty that have guided me. I would like to give a special thanks for the members of the bioinformatics lab, in particular the members of the Sacan lab: Rehman Qureshi, Daisy Heng Yang, April Chunyu Zhao, and Yiqian Zhou. Thank you for creating a pleasant and friendly environment in the lab. I give the members of my family my sincerest gratitude for all that they have done for me. I cannot begin to repay my parents for their sacrifices. I am eternally grateful for everything they have done. The support of my sisters and their encouragement gave me the strength to persevere to the end. iii Table of Contents LIST OF TABLES.......................................................................... vii LIST OF FIGURES ........................................................................ xiv ABSTRACT ................................................................................ xvii 1. A BRIEF INTRODUCTION TO GENE EXPRESSION............................. 1 1.1 Central Dogma of Molecular Biology........................................... 1 1.1.1 Basic Transfers .......................................................... 1 1.1.2 Uncommon Transfers ................................................... 3 1.2 Gene Expression ................................................................. 4 1.2.1 Estimating Gene Expression ............................................ 4 1.2.2 DNA Microarrays ...................................................... -
Processing, Modification and Anticodon–Codon
biomolecules Review Factors That Shape Eukaryotic tRNAomes: Processing, Modification and Anticodon–Codon Use Richard J. Maraia 1,2,* and Aneeshkumar G. Arimbasseri 3,* 1 Intramural Research Program, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD 20892, USA 2 Commissioned Corps, U.S. Public Health Service, Rockville, MD 20016, USA 3 Molecular Genetics Laboratory, National Institute of Immunology, Aruna Asaf Ali Marg, New Delhi 110067, India * Correspondence: [email protected] (R.J.M.); [email protected] (A.G.A.) Academic Editor: Valérie de Crécy-Lagard Received: 9 January 2017; Accepted: 24 February 2017; Published: 8 March 2017 Abstract: Transfer RNAs (tRNAs) contain sequence diversity beyond their anticodons and the large variety of nucleotide modifications found in all kingdoms of life. Some modifications stabilize structure and fit in the ribosome whereas those to the anticodon loop modulate messenger RNA (mRNA) decoding activity more directly. The identities of tRNAs with some universal anticodon loop modifications vary among distant and parallel species, likely to accommodate fine tuning for their translation systems. This plasticity in positions 34 (wobble) and 37 is reflected in codon use bias. Here, we review convergent evidence that suggest that expansion of the eukaryotic tRNAome was supported by its dedicated RNA polymerase III transcription system and coupling to the precursor-tRNA chaperone, La protein. We also review aspects of eukaryotic tRNAome evolution involving G34/A34 anticodon-sparing, relation to A34 modification to inosine, biased codon use and regulatory information in the redundancy (synonymous) component of the genetic code. We then review interdependent anticodon loop modifications involving position 37 in 3 eukaryotes. -
A De Novo 1P34.2 Microdeletion Identifies the Synaptic Vesicle Gene
Original article A de novo 1p34.2 microdeletion identifies the J Med Genet: first published as 10.1136/jmg.2008.065821 on 21 June 2009. Downloaded from synaptic vesicle gene RIMS3 as a novel candidate for autism Ravinesh A Kumar,1 Jyotsna Sudi,1 Timothy D Babatz,1 Camille W Brune,2 Donald Oswald,3 Mayon Yen,4 Norma J Nowak,5 Edwin H Cook,2 Susan L Christian,1 William B Dobyns1,6,7 < Supplementary figures and ABSTRACT including recurrent microdeletions and duplications tables are published online only Background A child with autism and mild microcephaly of 16p11.2 that have been reported in w1% of at http://jmg.bmj.com/content/ was found to have a de novo 3.3 Mb microdeletion on autism patients.81112Importantly, the discovery vol47/issue2 chromosome 1p34.2p34.3. The hypothesis is tested that of chromosomal abnormalities and CNVs has led 1 Department of Human this microdeletion contains one or more genes that to the identification of rare intragenic mutat- Genetics, University of Chicago, Chicago, Illinois, USA 2Institute underlie the autism phenotype in this child and in other ions through deep resequencing of autism candi- 13 for Juvenile Research, children with autism spectrum disorders. date genes, including NLGN3 and NLGN4, e e Department of Psychiatry, Methods To search for submicroscopic chromosomal NRXN1,10 14 15 SHANK316 18 and CNTNAP2.19 21 University of Illinois at Chicago, rearrangements in the child, array comparative genomic Although mutations in these genes account for only Chicago, Illinois, USA hybridisation (aCGH) was performed using a 19 K whole 3Department of Psychology, a small proportion of individuals with autism, they Virginia Commonwealth genome human bacterial artificial chromosome (BAC) nonetheless provide insight into potential biological University, Richmond, Virginia, array and the Illumina 610-Quad BeadChip microarray. -
Coexpression Networks Based on Natural Variation in Human Gene Expression at Baseline and Under Stress
University of Pennsylvania ScholarlyCommons Publicly Accessible Penn Dissertations Fall 2010 Coexpression Networks Based on Natural Variation in Human Gene Expression at Baseline and Under Stress Renuka Nayak University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/edissertations Part of the Computational Biology Commons, and the Genomics Commons Recommended Citation Nayak, Renuka, "Coexpression Networks Based on Natural Variation in Human Gene Expression at Baseline and Under Stress" (2010). Publicly Accessible Penn Dissertations. 1559. https://repository.upenn.edu/edissertations/1559 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/edissertations/1559 For more information, please contact [email protected]. Coexpression Networks Based on Natural Variation in Human Gene Expression at Baseline and Under Stress Abstract Genes interact in networks to orchestrate cellular processes. Here, we used coexpression networks based on natural variation in gene expression to study the functions and interactions of human genes. We asked how these networks change in response to stress. First, we studied human coexpression networks at baseline. We constructed networks by identifying correlations in expression levels of 8.9 million gene pairs in immortalized B cells from 295 individuals comprising three independent samples. The resulting networks allowed us to infer interactions between biological processes. We used the network to predict the functions of poorly-characterized human genes, and provided some experimental support. Examining genes implicated in disease, we found that IFIH1, a diabetes susceptibility gene, interacts with YES1, which affects glucose transport. Genes predisposing to the same diseases are clustered non-randomly in the network, suggesting that the network may be used to identify candidate genes that influence disease susceptibility. -
Mod5 Protein Binds to Trna Gene Complexes and Affects Local
Correction and Retractions CORRECTION BIOCHEMISTRY Correction for “Mod5 protein binds to tRNA gene complexes and issue 33, August 13, 2013, of Proc Natl Acad Sci USA (110: affects local transcriptional silencing,” by Matthew Pratt-Hyatt, E3081–E3089; first published July 29, 2013;10.1073/pnas. Dave A. Pai, Rebecca A. Haeusler, Glenn G. Wozniak, Paul D. 1219946110). Good, Erin L. Miller, Ian X. McLeod, John R. Yates III, The authors note that Fig. 5 appeared incorrectly. The cor- Anita K. Hopper, and David R. Engelke, which appeared in rected figure and its legend appear below. A ATG/GTP binding site S. cerevisiae H. sapiens A. thaliana S. cerevisiae H. sapiens A. thaliana S. cerevisiae H. sapiens A. thaliana RETRACTIONS CORRECTION AND DMAPP binding site S. cerevisiae H. sapiens A. thaliana S. cerevisiae H. sapiens A. thaliana Zn-Finger motif S. cerevisiae H. sapiens A. thaliana S. cerevisiae H. sapiens A. thaliana B +His -His mod5Δ S. cerevisiae A. thaliana H. sapiens Fig. 5. Conservation of the Mod5 protein and silencing function in eukaryotes. (A) The alignment of three Mod5 proteins from S. cerevisiae, A. thaliana,and H. sapiens is depicted, with areas of conservation indicated by shaded boxes. All variants contain motifs for ATP/GTP binding and DMAPP binding, including E. coli (14, 40). Eukaryotic homologs also have a zinc finger motif in the C-terminal extensions. (B) tgm silencing functions of yeast Mod5 are conserved in plant and human proteins. It was previously shown that human and Arabidopsis Mod5 homologs are able to restore i6A modification of tRNAs in yeast in an mod5Δ strain (14, 24). -
Parkinson's Disease Genes Do Not Segregate with Breast Cancer Genes' Loci
Published OnlineFirst June 13, 2013; DOI: 10.1158/1055-9965.EPI-13-0472 Cancer Epidemiology, Null Results in Brief Biomarkers & Prevention Parkinson's Disease Genes Do Not Segregate with Breast Cancer Genes' Loci Efrat Kravitz1,2, Yael Laitman3, Sharon Hassin-Baer1,4, Rivka Inzelberg1,2,4, and Eitan Friedman3,4 Abstract Background: Breast cancer and skin cancer rates among patients with Parkinson’s disease are higher than in non-Parkinson’s disease cases, and Jewish-Ashkenazi LRRK2ÃG2019S mutation carriers have higher breast cancer rates than noncarriers. Because additional Parkinson’s disease predisposition genes are implicated in the malignant transformation process, we hypothesized that the association between breast cancer and Parkinson’s disease may be related to segregation of breast cancer loci with known Parkinson’s disease predisposition loci. Methods: Data mining for single-nucleotide polymorphisms (SNP), reportedly associated with breast cancer in genome-wide association study (GWAS) that localize to chromosomes bearing known Parkinson’s disease predisposition loci: PARK7, PINK1 (chromosome 1); SNCA (chromosome 4); PARK2 (chromosome 6); and LRRK2 (chromosome 12), was carried out. Results: A total of 188 breast cancer–associated SNPs were identified in 29 eligible manuscripts: 43 SNPs on chromosome 1 (PINK1), 46 SNPs on chromosome 4 (SNCA), 72 SNPs on chromosome 6 (PARK2), and 27 SNPs on chromosome 12 (LRRK2). No breast cancer–associated SNP was located at distance less than 500,000 bp from any of the analyzed Parkinson’s disease predisposition genes. Conclusions: The association between breast cancer and the most common genetic-inherited forms of Parkinson’s disease cannot be accounted for by allele cosegregation at the genomic level. -
Biomedical Informatics
BIOMEDICAL INFORMATICS Abstract GENE LIST AUTOMATICALLY DERIVED FOR YOU (GLAD4U): DERIVING AND PRIORITIZING GENE LISTS FROM PUBMED LITERATURE JEROME JOURQUIN Thesis under the direction of Professor Bing Zhang Answering questions such as ―Which genes are related to breast cancer?‖ usually requires retrieving relevant publications through the PubMed search engine, reading these publications, and manually creating gene lists. This process is both time-consuming and prone to errors. We report GLAD4U (Gene List Automatically Derived For You), a novel, free web-based gene retrieval and prioritization tool. The quality of gene lists created by GLAD4U for three Gene Ontology terms and three disease terms was assessed using ―gold standard‖ lists curated in public databases. We also compared the performance of GLAD4U with that of another gene prioritization software, EBIMed. GLAD4U has a high overall recall. Although precision is generally low, its prioritization methods successfully rank truly relevant genes at the top of generated lists to facilitate efficient browsing. GLAD4U is simple to use, and its interface can be found at: http://bioinfo.vanderbilt.edu/glad4u. Approved ___________________________________________ Date _____________ GENE LIST AUTOMATICALLY DERIVED FOR YOU (GLAD4U): DERIVING AND PRIORITIZING GENE LISTS FROM PUBMED LITERATURE By Jérôme Jourquin Thesis Submitted to the Faculty of the Graduate School of Vanderbilt University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE in Biomedical Informatics May, 2010 Nashville, Tennessee Approved: Professor Bing Zhang Professor Hua Xu Professor Daniel R. Masys ACKNOWLEDGEMENTS I would like to express profound gratitude to my advisor, Dr. Bing Zhang, for his invaluable support, supervision and suggestions throughout this research work. -
Splicing Changes in SMA Mouse Motoneurons and SMN-Depleted Neuroblastoma Cells
RESEARCH PAPER RNA Biology 11:11, 1430--1446; November 2014; Published with license by Taylor & Francis Group, LLC Splicing changes in SMA mouse motoneurons and SMN-depleted neuroblastoma cells: Evidence for involvement of splicing regulatory proteins Qing Huo1,2, Melis Kayikci3, Philipp Odermatt1,2, Kathrin Meyer1,#, Olivia Michels1, Smita Saxena1,4, Jernej Ule3,C, and Daniel Schumperli€ 1,* 1Institute of Cell Biology; University of Bern; Bern, Switzerland; 2Graduate School for Cellular and Biomedical Sciences; University of Bern; Bern, Switzerland; 3MRC Laboratory of Molecular Biology; Cambridge, UK; 4Friedrich Miescher Institute for Biomedical Research; Basel, Switzerland Current affiliation: #Center for Gene Therapy; Nationwide Children’s Hospital; Columbus, OH USA;CDepartment of Molecular Neuroscience; UCL Institute of Neurology; London, UK Keywords: exon junction microarray, laser capture microdissection, major spliceosome, minor spliceosome, motoneurons, neurodegerative disease, snRNP assembly, Spinal Muscular Atrophy, splicing, splicing regulators Abbreviations: ESE, exonic splicing enhancer; FCS, fetal calf serum; hz, heterozygote, LCM; laser capture microdissection; MN, motoneuron; NMD, nonsense-mediated mRNA decay; NMJ, neuromuscular junction, PCR; polymerase chain reaction, qPCR; real-time (quantitative) PCR; RT, reverse transcription; sh, short hairpin; SMA, Spinal Muscular Atrophy; SMN, Survival Motor Neuron; snRNP, small nuclear ribonucleoprotein; snRNA, small nuclear ribonucleic acid; TcRb, T-cell receptor b chain. Spinal Muscular Atrophy (SMA) is caused by deletions or mutations in the Survival Motor Neuron 1 (SMN1) gene. The second gene copy, SMN2, produces some, but not enough, functional SMN protein. SMN is essential to assemble small nuclear ribonucleoproteins (snRNPs) that form the spliceosome. However, it is not clear whether SMA is caused by defects in this function that could lead to splicing changes in all tissues, or by the impairment of an additional, less well characterized, but motoneuron-specific SMN function.