RNA Polymerase I Transcription and Pre-Rrna Processing Are Linked by Specific SSU Processome Components
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The DEAD-Box RNA Helicase-Like Utp25 Is an SSU Processome Component
Downloaded from rnajournal.cshlp.org on September 25, 2021 - Published by Cold Spring Harbor Laboratory Press The DEAD-box RNA helicase-like Utp25 is an SSU processome component J. MICHAEL CHARETTE1,2 and SUSAN J. BASERGA1,2,3 1Department of Molecular Biophysics & Biochemistry, Yale University School of Medicine, New Haven, Connecticut 06520, USA 2Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, Connecticut 06520, USA 3Department of Genetics, Yale University School of Medicine, New Haven, Connecticut 06520, USA ABSTRACT The SSU processome is a large ribonucleoprotein complex consisting of the U3 snoRNA and at least 43 proteins. A database search, initiated in an effort to discover additional SSU processome components, identified the uncharacterized, conserved and essential yeast nucleolar protein YIL091C/UTP25 as one such candidate. The C-terminal DUF1253 motif, a domain of unknown function, displays limited sequence similarity to DEAD-box RNA helicases. In the absence of the conserved DEAD-box sequence, motif Ia is the only clearly identifiable helicase element. Since the yeast homolog is nucleolar and interacts with components of the SSU processome, we examined its role in pre-rRNA processing. Genetic depletion of Utp25 resulted in slowed growth. Northern analysis of pre-rRNA revealed an 18S rRNA maturation defect at sites A0,A1, and A2. Coimmunoprecipitation confirmed association with U3 snoRNA and with Mpp10, and with components of the t-Utp/UtpA, UtpB, and U3 snoRNP subcomplexes. Mutation of the conserved motif Ia residues resulted in no discernable temperature- sensitive or cold-sensitive growth defects, implying that this motif is dispensable for Utp25 function. -
Bayesian Hierarchical Modeling of High-Throughput Genomic Data with Applications to Cancer Bioinformatics and Stem Cell Differentiation
BAYESIAN HIERARCHICAL MODELING OF HIGH-THROUGHPUT GENOMIC DATA WITH APPLICATIONS TO CANCER BIOINFORMATICS AND STEM CELL DIFFERENTIATION by Keegan D. Korthauer A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Statistics) at the UNIVERSITY OF WISCONSIN–MADISON 2015 Date of final oral examination: 05/04/15 The dissertation is approved by the following members of the Final Oral Committee: Christina Kendziorski, Professor, Biostatistics and Medical Informatics Michael A. Newton, Professor, Statistics Sunduz Kele¸s,Professor, Biostatistics and Medical Informatics Sijian Wang, Associate Professor, Biostatistics and Medical Informatics Michael N. Gould, Professor, Oncology © Copyright by Keegan D. Korthauer 2015 All Rights Reserved i in memory of my grandparents Ma and Pa FL Grandma and John ii ACKNOWLEDGMENTS First and foremost, I am deeply grateful to my thesis advisor Christina Kendziorski for her invaluable advice, enthusiastic support, and unending patience throughout my time at UW-Madison. She has provided sound wisdom on everything from methodological principles to the intricacies of academic research. I especially appreciate that she has always encouraged me to eke out my own path and I attribute a great deal of credit to her for the successes I have achieved thus far. I also owe special thanks to my committee member Professor Michael Newton, who guided me through one of my first collaborative research experiences and has continued to provide key advice on my thesis research. I am also indebted to the other members of my thesis committee, Professor Sunduz Kele¸s,Professor Sijian Wang, and Professor Michael Gould, whose valuable comments, questions, and suggestions have greatly improved this dissertation. -
Analysis of Gene Expression Data for Gene Ontology
ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION A Thesis Presented to The Graduate Faculty of The University of Akron In Partial Fulfillment of the Requirements for the Degree Master of Science Robert Daniel Macholan May 2011 ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION Robert Daniel Macholan Thesis Approved: Accepted: _______________________________ _______________________________ Advisor Department Chair Dr. Zhong-Hui Duan Dr. Chien-Chung Chan _______________________________ _______________________________ Committee Member Dean of the College Dr. Chien-Chung Chan Dr. Chand K. Midha _______________________________ _______________________________ Committee Member Dean of the Graduate School Dr. Yingcai Xiao Dr. George R. Newkome _______________________________ Date ii ABSTRACT A tremendous increase in genomic data has encouraged biologists to turn to bioinformatics in order to assist in its interpretation and processing. One of the present challenges that need to be overcome in order to understand this data more completely is the development of a reliable method to accurately predict the function of a protein from its genomic information. This study focuses on developing an effective algorithm for protein function prediction. The algorithm is based on proteins that have similar expression patterns. The similarity of the expression data is determined using a novel measure, the slope matrix. The slope matrix introduces a normalized method for the comparison of expression levels throughout a proteome. The algorithm is tested using real microarray gene expression data. Their functions are characterized using gene ontology annotations. The results of the case study indicate the protein function prediction algorithm developed is comparable to the prediction algorithms that are based on the annotations of homologous proteins. -
Integrated Bioinformatic Analysis of RNA Binding Proteins in Hepatocellular Carcinoma
www.aging-us.com AGING 2021, Vol. 13, No. 2 Research Paper Integrated bioinformatic analysis of RNA binding proteins in hepatocellular carcinoma Ling Wang1,*, Zhen Zhang2,3,*, Yuan Li1, Yanyan Wan1, Baocai Xing1,& 1Key Laboratory of Carcinogenesis and Translational Research, Ministry of Education, Hepatopancreatobiliary Surgery Department I, Peking University Cancer Hospital and Institute, Beijing 100142, China 2Department of Gastroenterological Surgery, Peking University People’s Hospital, Beijing 100044, China 3Laboratory of Surgical Oncology, Beijing Key Laboratory of Colorectal Cancer Diagnosis and Treatment Research, Peking University People’s Hospital, Beijing 100044, China *Equal contribution Correspondence to: Baocai Xing; email: [email protected] Keywords: RNA binding protein, hepatocellular carcinoma, biomarker, transcriptomics, proteomics Received: June 8, 2020 Accepted: November 3, 2020 Published: December 19, 2020 Copyright: © 2020 Wang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. ABSTRACT RNA binding proteins (RBPs) are aberrantly expressed in a tissue-specific manner across many tumors. These proteins, which play a vital role in post-transcriptional gene regulation, are involved in RNA splicing, maturation, transport, stability, degradation, and translation. We set out to establish an accurate risk score model based on RBPs to estimate prognosis in hepatocellular carcinoma (HCC). RNA-sequencing data, proteomic data and corresponding clinical information were acquired from the Cancer Genome Atlas database and the Clinical Proteomic Tumor Analysis Consortium database respectively. We identified 406 differentially expressed RBPs between HCC tumor and normal tissues at the transcriptional and protein level. -
Predicting Clinical Response to Treatment with a Soluble Tnf-Antagonist Or Tnf, Or a Tnf Receptor Agonist
(19) TZZ _ __T (11) EP 2 192 197 A1 (12) EUROPEAN PATENT APPLICATION (43) Date of publication: (51) Int Cl.: 02.06.2010 Bulletin 2010/22 C12Q 1/68 (2006.01) (21) Application number: 08170119.5 (22) Date of filing: 27.11.2008 (84) Designated Contracting States: (72) Inventor: The designation of the inventor has not AT BE BG CH CY CZ DE DK EE ES FI FR GB GR yet been filed HR HU IE IS IT LI LT LU LV MC MT NL NO PL PT RO SE SI SK TR (74) Representative: Habets, Winand Designated Extension States: Life Science Patents AL BA MK RS PO Box 5096 6130 PB Sittard (NL) (71) Applicant: Vereniging voor Christelijk Hoger Onderwijs, Wetenschappelijk Onderzoek en Patiëntenzorg 1081 HV Amsterdam (NL) (54) Predicting clinical response to treatment with a soluble tnf-antagonist or tnf, or a tnf receptor agonist (57) The invention relates to methods for predicting a clinical response to a therapy with a soluble TNF antagonist, TNF or a TNF receptor agonist and a kit for use in said methods. EP 2 192 197 A1 Printed by Jouve, 75001 PARIS (FR) EP 2 192 197 A1 Description [0001] The invention relates to methods for predicting a clinical response to a treatment with a soluble TNF antagonist, with TNF or a TNF receptor agonist using expression levels of genes of the Type I INF pathway and a kit for use in said 5 methods. In another aspect, the invention relates to a method for evaluating a pharmacological effect of a treatment with a soluble TNF antagonist, TNF or a TNF receptor agonist. -
Rrna Types in Zebrafish Development
UvA-DARE (Digital Academic Repository) Distinct maternal and somatic rRNA types in zebrafish development Locati, M. Publication date 2017 Document Version Final published version License Other Link to publication Citation for published version (APA): Locati, M. (2017). Distinct maternal and somatic rRNA types in zebrafish development. General rights It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). Disclaimer/Complaints regulations If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: https://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible. UvA-DARE is a service provided by the library of the University of Amsterdam (https://dare.uva.nl) Download date:04 Oct 2021 DISTINCT MATERNAL AND SOMATIC rRNA TYPES IN ZEBRAFISH DEVELOPMENT MAURO LOCATI DISTINCT MATERNAL AND SOMATIC rRNA TYPES IN ZEBRAFISH DEVELOPMENT MAURO LOCATI Distinct Maternal and Somatic rRNA Types in Zebrafish Development ACADEMISCH PROEFSCHRIFT ter verkrijging van de graad van doctor aan de Universiteit van Amsterdam op gezag van de Rector Magnificus prof. dr. ir. K.I.J. Maex ten overstaan van een door het College voor Promoties ingestelde commissie, in het openbaar te verdedigen in de Aula der Universiteit op woensdag 6 december 2017, te 13:00 uur door Mauro Locati geboren te Palermo, Italië Promotiecommissie: Promotor: Prof. -
Mouse Utp15 Conditional Knockout Project (CRISPR/Cas9)
https://www.alphaknockout.com Mouse Utp15 Conditional Knockout Project (CRISPR/Cas9) Objective: To create a Utp15 conditional knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Utp15 gene (NCBI Reference Sequence: NM_178918 ; Ensembl: ENSMUSG00000041747 ) is located on Mouse chromosome 13. 13 exons are identified, with the ATG start codon in exon 2 and the TAA stop codon in exon 13 (Transcript: ENSMUST00000040972). Exon 3~4 will be selected as conditional knockout region (cKO region). Deletion of this region should result in the loss of function of the Mouse Utp15 gene. To engineer the targeting vector, homologous arms and cKO region will be generated by PCR using BAC clone RP23-267C22 as template. Cas9, gRNA and targeting vector will be co-injected into fertilized eggs for cKO Mouse production. The pups will be genotyped by PCR followed by sequencing analysis. Note: Exon 3 starts from about 5.74% of the coding region. The knockout of Exon 3~4 will result in frameshift of the gene. The size of intron 2 for 5'-loxP site insertion: 1332 bp, and the size of intron 4 for 3'-loxP site insertion: 1090 bp. The size of effective cKO region: ~862 bp. The cKO region does not have any other known gene. Page 1 of 7 https://www.alphaknockout.com Overview of the Targeting Strategy Wildtype allele gRNA region 5' gRNA region 3' 1 2 3 4 5 6 13 Targeting vector Targeted allele Constitutive KO allele (After Cre recombination) Legends Exon of mouse Utp15 Homology arm cKO region loxP site Page 2 of 7 https://www.alphaknockout.com Overview of the Dot Plot Window size: 10 bp Forward Reverse Complement Sequence 12 Note: The sequence of homologous arms and cKO region is aligned with itself to determine if there are tandem repeats. -
Intersections Spring Symposium
INTERSECTIONS SPRING SYMPOSIUM APRIL TH, 8 Last Name First Name Project Title Page Analyzing the Effect of Urbanization on Abboud Bissan Phylogenetic signal in the Species Columba 1 Abouzahra Sharifah Peripheral IV Catheter Sterilization Device 2 Development of a Liquid Crystal Based Electron Adkins Raymond Shower Detector 2 Purification of Secreted Protein, Acidic and Rich in Cysteine (SPARC) Implicated for its Effects on Al Bahrani Zaid Intraocular Pressure 3 A Window into Metabolite Changes of Live Aljawad Yaqeen Bacteria Following Drug Infusion 3 Anderson Emily In-situ Resource Utilization on Mars 4 The Relationship Between Subjective and Objective Language Assessments For Second- Arredondo Kaitlynn Language Learners 4 Atkinson Scott MotionSense Wave: Toucheless Faucet 5 Ayyar Aneeka Hand Tremor Reduction Device 6 Modifying Low-Emissivity Glass for Use with Bailey Jessica Surface Enhanced Raman Spectroscopy 5 Automated Segmentation and Radiomic Characterization of Visceral Fat on Bowel MRIs for Barbur Iulia Crohn's Disease 6 Periodic Liquid Crystal Order: Theory and Barnaby Gavin-Rae Simulations 7 The Role of Dentistry in the U.S. Opioid Epidemic: Basore Makenna A Literature Review 7 Berends Hannah A Leader’s Role in a Nation’s Stability 8 A Study on Daily Cycles in Activity Levels of Bhatia Shireen Coyotes (Canis latrans) 8 Co-creation of an Intervention with African American Older Adults to Manage Stress Blackshire Gabrielle Associated with Self-management of 9 Developing to Developed: Entrepreneurship in Blatt Noah Latin America -
Kras Mutant Genetically Engineered Mouse Models of Human Cancers
Kras mutant genetically engineered mouse models of PNAS PLUS human cancers are genomically heterogeneous Wei-Jen Chunga,1,2, Anneleen Daemena,1, Jason H. Chengb, Jason E. Longb, Jonathan E. Cooperb, Bu-er Wangb, Christopher Tranb, Mallika Singhb,3, Florian Gnada,4, Zora Modrusanc, Oded Foremand, and Melissa R. Junttilab,5 aBioinformatics & Computational Biology, Genentech, Inc., South San Francisco, CA 94080; bTranslational Oncology, Genentech, Inc., South San Francisco, CA 94080; cMolecular Biology, Genentech, Inc., South San Francisco, CA 94080; and dPathology, Genentech, Inc., South San Francisco, CA 94080 Edited by Anton Berns, The Netherlands Cancer Institute, Amsterdam, The Netherlands, and approved November 6, 2017 (received for review May 23, 2017) KRAS mutant tumors are largely recalcitrant to targeted therapies. treatment susceptibility and tumor evolution under selective pres- Genetically engineered mouse models (GEMMs) of Kras mutant sure of drug therapy. cancer recapitulate critical aspects of this disease and are widely used for preclinical validation of targets and therapies. Through Results comprehensive profiling of exomes and matched transcriptomes Spontaneous Acquisition of Genomic Aberrations in KrasG12D-Initiated of >200 KrasG12D-initiated GEMM tumors from one lung and two GEMM Tumors. To better define the genomic landscape of estab- pancreatic cancer models, we discover that significant intratumoral lished Kras mutant tumor models, we focused on three models of and intertumoral genomic heterogeneity evolves during tumorigen- Kras mutant cancer: a nonsmall cell lung cancer (NSCLC) model esis. Known oncogenes and tumor suppressor genes, beyond those with adenovirus-induced expression of KrasG12D and homozygous engineered, are mutated, amplified, and deleted. Unlike human tu- p53 targeting (KP:KrasLSL.G12D/wt;p53frt/frt) (11, 13), and two models mors, the GEMM genomic landscapes are dominated by copy num- ber alterations, while protein-altering mutations are rare. -
The Genetic Basis for Individual Differences in Mrna Splicing and APOBEC1 Editing Activity in Murine Macrophages
The genetic basis for individual differences in mRNA splicing and APOBEC1 editing activity in murine macrophages The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Citation Hassan, M. A., V. Butty, K. D. C. Jensen, and J. P. J. Saeij. “The Genetic Basis for Individual Differences in mRNA Splicing and APOBEC1 Editing Activity in Murine Macrophages.” Genome Research 24, no. 3 (March 1, 2014): 377–389. As Published http://dx.doi.org/10.1101/gr.166033.113 Publisher Cold Spring Harbor Laboratory Press Version Final published version Citable link http://hdl.handle.net/1721.1/89091 Terms of Use Creative Commons Attribution-Noncommerical Detailed Terms http://creativecommons.org/licenses/by-nc/3.0/ Downloaded from genome.cshlp.org on August 27, 2014 - Published by Cold Spring Harbor Laboratory Press The genetic basis for individual differences in mRNA splicing and APOBEC1 editing activity in murine macrophages Musa A. Hassan, Vincent Butty, Kirk D.C. Jensen, et al. Genome Res. 2014 24: 377-389 originally published online November 18, 2013 Access the most recent version at doi:10.1101/gr.166033.113 Supplemental http://genome.cshlp.org/content/suppl/2014/01/07/gr.166033.113.DC1.html Material References This article cites 95 articles, 32 of which can be accessed free at: http://genome.cshlp.org/content/24/3/377.full.html#ref-list-1 Creative This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the Commons first six months after the full-issue publication date (see License http://genome.cshlp.org/site/misc/terms.xhtml). -
Utpa and Utpb Chaperone Nascent Pre-Ribosomal RNA and U3 Snorna to Initiate Eukaryotic Ribosome Assembly
ARTICLE Received 6 Apr 2016 | Accepted 27 May 2016 | Published 29 Jun 2016 DOI: 10.1038/ncomms12090 OPEN UtpA and UtpB chaperone nascent pre-ribosomal RNA and U3 snoRNA to initiate eukaryotic ribosome assembly Mirjam Hunziker1,*, Jonas Barandun1,*, Elisabeth Petfalski2, Dongyan Tan3, Cle´mentine Delan-Forino2, Kelly R. Molloy4, Kelly H. Kim5, Hywel Dunn-Davies2, Yi Shi4, Malik Chaker-Margot1,6, Brian T. Chait4, Thomas Walz5, David Tollervey2 & Sebastian Klinge1 Early eukaryotic ribosome biogenesis involves large multi-protein complexes, which co-transcriptionally associate with pre-ribosomal RNA to form the small subunit processome. The precise mechanisms by which two of the largest multi-protein complexes—UtpA and UtpB—interact with nascent pre-ribosomal RNA are poorly understood. Here, we combined biochemical and structural biology approaches with ensembles of RNA–protein cross-linking data to elucidate the essential functions of both complexes. We show that UtpA contains a large composite RNA-binding site and captures the 50 end of pre-ribosomal RNA. UtpB forms an extended structure that binds early pre-ribosomal intermediates in close proximity to architectural sites such as an RNA duplex formed by the 50 ETS and U3 snoRNA as well as the 30 boundary of the 18S rRNA. Both complexes therefore act as vital RNA chaperones to initiate eukaryotic ribosome assembly. 1 Laboratory of Protein and Nucleic Acid Chemistry, The Rockefeller University, New York, New York 10065, USA. 2 Wellcome Trust Centre for Cell Biology, University of Edinburgh, Michael Swann Building, Max Born Crescent, Edinburgh EH9 3BF, UK. 3 Department of Cell Biology, Harvard Medical School, Boston, Massachusetts 02115, USA. -
Broad Susceptibility of Nucleolar Proteins and Autoantigens to Complement C1 Protease Degradation
Broad Susceptibility of Nucleolar Proteins and Autoantigens to Complement C1 Protease Degradation This information is current as Yitian Cai, Seng Yin Kelly Wee, Junjie Chen, Boon Heng of September 25, 2021. Dennis Teo, Yee Leng Carol Ng, Khai Pang Leong and Jinhua Lu J Immunol published online 25 October 2017 http://www.jimmunol.org/content/early/2017/10/25/jimmun ol.1700728 Downloaded from Supplementary http://www.jimmunol.org/content/suppl/2017/10/25/jimmunol.170072 Material 8.DCSupplemental http://www.jimmunol.org/ Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision • No Triage! Every submission reviewed by practicing scientists • Fast Publication! 4 weeks from acceptance to publication by guest on September 25, 2021 *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 © 2017 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. Published October 25, 2017, doi:10.4049/jimmunol.1700728 The Journal of Immunology Broad Susceptibility of Nucleolar Proteins and Autoantigens to Complement C1 Protease Degradation Yitian Cai,*,1 Seng Yin Kelly Wee,*,1 Junjie Chen,* Boon Heng Dennis Teo,* Yee Leng Carol Ng,† Khai Pang Leong,† and Jinhua Lu* Anti-nuclear autoantibodies, which frequently target the nucleoli, are pathogenic hallmarks of systemic lupus erythematosus (SLE).