Expression of Periaxin (PRX) Specifically in the Human
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Inherited Neuropathies
407 Inherited Neuropathies Vera Fridman, MD1 M. M. Reilly, MD, FRCP, FRCPI2 1 Department of Neurology, Neuromuscular Diagnostic Center, Address for correspondence Vera Fridman, MD, Neuromuscular Massachusetts General Hospital, Boston, Massachusetts Diagnostic Center, Massachusetts General Hospital, Boston, 2 MRC Centre for Neuromuscular Diseases, UCL Institute of Neurology Massachusetts, 165 Cambridge St. Boston, MA 02114 and The National Hospital for Neurology and Neurosurgery, Queen (e-mail: [email protected]). Square, London, United Kingdom Semin Neurol 2015;35:407–423. Abstract Hereditary neuropathies (HNs) are among the most common inherited neurologic Keywords disorders and are diverse both clinically and genetically. Recent genetic advances have ► hereditary contributed to a rapid expansion of identifiable causes of HN and have broadened the neuropathy phenotypic spectrum associated with many of the causative mutations. The underlying ► Charcot-Marie-Tooth molecular pathways of disease have also been better delineated, leading to the promise disease for potential treatments. This chapter reviews the clinical and biological aspects of the ► hereditary sensory common causes of HN and addresses the challenges of approaching the diagnostic and motor workup of these conditions in a rapidly evolving genetic landscape. neuropathy ► hereditary sensory and autonomic neuropathy Hereditary neuropathies (HN) are among the most common Select forms of HN also involve cranial nerves and respiratory inherited neurologic diseases, with a prevalence of 1 in 2,500 function. Nevertheless, in the majority of patients with HN individuals.1,2 They encompass a clinically heterogeneous set there is no shortening of life expectancy. of disorders and vary greatly in severity, spanning a spectrum Historically, hereditary neuropathies have been classified from mildly symptomatic forms to those resulting in severe based on the primary site of nerve pathology (myelin vs. -
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. -
A Case Report on Charcot-Marie-Tooth Disease with a Novel Periaxin Gene Mutation
Open Access Case Report DOI: 10.7759/cureus.5111 A Case Report on Charcot-Marie-Tooth Disease with a Novel Periaxin Gene Mutation Sorabh Datta 1 , Saurabh Kataria 1 , Raghav Govindarajan 1 1. Neurology, University of Missouri, Columbia, USA Corresponding author: Sorabh Datta, [email protected] Abstract Charcot-Marie-Tooth (CMT) disease is one of the most common primary hereditary neuropathies causing peripheral neuropathies. More than 60 different gene mutations are causing this disease. The PRX gene codes for Periaxin proteins that are expressed by Schwann cells and are necessary for the formation and maintenance of myelination of peripheral nerves. Dejerine-Sottas neuropathy and Charcot-Marie-Tooth type 4F (CMT4F) are the two different clinical phenotypes observed in association with PRX gene mutation. This article describes a case of an elderly male with a novel mutation involving the PRX gene. Categories: Genetics, Internal Medicine, Neurology Keywords: neurology, sensorimotor neuropathy, congenital, gene expression, genetic mutation, protein, pes cavus, demyelinating diseases, charcot-marie-tooth, autosomal recessive disorder Introduction As per the Dyck classification in the year 1970, primary hereditary neuropathies are divided into hereditary motor sensory neuropathy (HMSN) and hereditary sensory autonomic neuropathy (HSAN) [1]. Charcot- Marie-Tooth (CMT) disease is a type of HMSN with an estimated prevalence of 1 in 2,500 [2]. CMT can follow autosomal recessive (ARCMT), X-linked recessive, and also an autosomal dominant pattern. CMT type 4 is a rapidly increasing ARCMT disease form in HMSN, although CMT type 1 and 2 still account for the most substantial proportion of the patient population [3]. CMT4F is a severe, demyelinating subtype of CMT type 4 and is characterized by childhood onset of slowly progressing weakness in the distal muscles associated with atrophy. -
Figure S1. Representative Report Generated by the Ion Torrent System Server for Each of the KCC71 Panel Analysis and Pcafusion Analysis
Figure S1. Representative report generated by the Ion Torrent system server for each of the KCC71 panel analysis and PCaFusion analysis. (A) Details of the run summary report followed by the alignment summary report for the KCC71 panel analysis sequencing. (B) Details of the run summary report for the PCaFusion panel analysis. A Figure S1. Continued. Representative report generated by the Ion Torrent system server for each of the KCC71 panel analysis and PCaFusion analysis. (A) Details of the run summary report followed by the alignment summary report for the KCC71 panel analysis sequencing. (B) Details of the run summary report for the PCaFusion panel analysis. B Figure S2. Comparative analysis of the variant frequency found by the KCC71 panel and calculated from publicly available cBioPortal datasets. For each of the 71 genes in the KCC71 panel, the frequency of variants was calculated as the variant number found in the examined cases. Datasets marked with different colors and sample numbers of prostate cancer are presented in the upper right. *Significantly high in the present study. Figure S3. Seven subnetworks extracted from each of seven public prostate cancer gene networks in TCNG (Table SVI). Blue dots represent genes that include initial seed genes (parent nodes), and parent‑child and child‑grandchild genes in the network. Graphical representation of node‑to‑node associations and subnetwork structures that differed among and were unique to each of the seven subnetworks. TCNG, The Cancer Network Galaxy. Figure S4. REVIGO tree map showing the predicted biological processes of prostate cancer in the Japanese. Each rectangle represents a biological function in terms of a Gene Ontology (GO) term, with the size adjusted to represent the P‑value of the GO term in the underlying GO term database. -
Bioinformatics Analyses of Genomic Imprinting
Bioinformatics Analyses of Genomic Imprinting Dissertation zur Erlangung des Grades des Doktors der Naturwissenschaften der Naturwissenschaftlich-Technischen Fakultät III Chemie, Pharmazie, Bio- und Werkstoffwissenschaften der Universität des Saarlandes von Barbara Hutter Saarbrücken 2009 Tag des Kolloquiums: 08.12.2009 Dekan: Prof. Dr.-Ing. Stefan Diebels Berichterstatter: Prof. Dr. Volkhard Helms Priv.-Doz. Dr. Martina Paulsen Vorsitz: Prof. Dr. Jörn Walter Akad. Mitarbeiter: Dr. Tihamér Geyer Table of contents Summary________________________________________________________________ I Zusammenfassung ________________________________________________________ I Acknowledgements _______________________________________________________II Abbreviations ___________________________________________________________ III Chapter 1 – Introduction __________________________________________________ 1 1.1 Important terms and concepts related to genomic imprinting __________________________ 2 1.2 CpG islands as regulatory elements ______________________________________________ 3 1.3 Differentially methylated regions and imprinting clusters_____________________________ 6 1.4 Reading the imprint __________________________________________________________ 8 1.5 Chromatin marks at imprinted regions___________________________________________ 10 1.6 Roles of repetitive elements ___________________________________________________ 12 1.7 Functional implications of imprinted genes _______________________________________ 14 1.8 Evolution and parental conflict ________________________________________________ -
1 Supporting Information for a Microrna Network Regulates
Supporting Information for A microRNA Network Regulates Expression and Biosynthesis of CFTR and CFTR-ΔF508 Shyam Ramachandrana,b, Philip H. Karpc, Peng Jiangc, Lynda S. Ostedgaardc, Amy E. Walza, John T. Fishere, Shaf Keshavjeeh, Kim A. Lennoxi, Ashley M. Jacobii, Scott D. Rosei, Mark A. Behlkei, Michael J. Welshb,c,d,g, Yi Xingb,c,f, Paul B. McCray Jr.a,b,c Author Affiliations: Department of Pediatricsa, Interdisciplinary Program in Geneticsb, Departments of Internal Medicinec, Molecular Physiology and Biophysicsd, Anatomy and Cell Biologye, Biomedical Engineeringf, Howard Hughes Medical Instituteg, Carver College of Medicine, University of Iowa, Iowa City, IA-52242 Division of Thoracic Surgeryh, Toronto General Hospital, University Health Network, University of Toronto, Toronto, Canada-M5G 2C4 Integrated DNA Technologiesi, Coralville, IA-52241 To whom correspondence should be addressed: Email: [email protected] (M.J.W.); yi- [email protected] (Y.X.); Email: [email protected] (P.B.M.) This PDF file includes: Materials and Methods References Fig. S1. miR-138 regulates SIN3A in a dose-dependent and site-specific manner. Fig. S2. miR-138 regulates endogenous SIN3A protein expression. Fig. S3. miR-138 regulates endogenous CFTR protein expression in Calu-3 cells. Fig. S4. miR-138 regulates endogenous CFTR protein expression in primary human airway epithelia. Fig. S5. miR-138 regulates CFTR expression in HeLa cells. Fig. S6. miR-138 regulates CFTR expression in HEK293T cells. Fig. S7. HeLa cells exhibit CFTR channel activity. Fig. S8. miR-138 improves CFTR processing. Fig. S9. miR-138 improves CFTR-ΔF508 processing. Fig. S10. SIN3A inhibition yields partial rescue of Cl- transport in CF epithelia. -
Methods in and Applications of the Sequencing of Short Non-Coding Rnas" (2013)
University of Pennsylvania ScholarlyCommons Publicly Accessible Penn Dissertations 2013 Methods in and Applications of the Sequencing of Short Non- Coding RNAs Paul Ryvkin University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/edissertations Part of the Bioinformatics Commons, Genetics Commons, and the Molecular Biology Commons Recommended Citation Ryvkin, Paul, "Methods in and Applications of the Sequencing of Short Non-Coding RNAs" (2013). Publicly Accessible Penn Dissertations. 922. https://repository.upenn.edu/edissertations/922 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/edissertations/922 For more information, please contact [email protected]. Methods in and Applications of the Sequencing of Short Non-Coding RNAs Abstract Short non-coding RNAs are important for all domains of life. With the advent of modern molecular biology their applicability to medicine has become apparent in settings ranging from diagonistic biomarkers to therapeutics and fields angingr from oncology to neurology. In addition, a critical, recent technological development is high-throughput sequencing of nucleic acids. The convergence of modern biotechnology with developments in RNA biology presents opportunities in both basic research and medical settings. Here I present two novel methods for leveraging high-throughput sequencing in the study of short non- coding RNAs, as well as a study in which they are applied to Alzheimer's Disease (AD). The computational methods presented here include High-throughput Annotation of Modified Ribonucleotides (HAMR), which enables researchers to detect post-transcriptional covalent modifications ot RNAs in a high-throughput manner. In addition, I describe Classification of RNAs by Analysis of Length (CoRAL), a computational method that allows researchers to characterize the pathways responsible for short non-coding RNA biogenesis. -
Association of Gene Ontology Categories with Decay Rate for Hepg2 Experiments These Tables Show Details for All Gene Ontology Categories
Supplementary Table 1: Association of Gene Ontology Categories with Decay Rate for HepG2 Experiments These tables show details for all Gene Ontology categories. Inferences for manual classification scheme shown at the bottom. Those categories used in Figure 1A are highlighted in bold. Standard Deviations are shown in parentheses. P-values less than 1E-20 are indicated with a "0". Rate r (hour^-1) Half-life < 2hr. Decay % GO Number Category Name Probe Sets Group Non-Group Distribution p-value In-Group Non-Group Representation p-value GO:0006350 transcription 1523 0.221 (0.009) 0.127 (0.002) FASTER 0 13.1 (0.4) 4.5 (0.1) OVER 0 GO:0006351 transcription, DNA-dependent 1498 0.220 (0.009) 0.127 (0.002) FASTER 0 13.0 (0.4) 4.5 (0.1) OVER 0 GO:0006355 regulation of transcription, DNA-dependent 1163 0.230 (0.011) 0.128 (0.002) FASTER 5.00E-21 14.2 (0.5) 4.6 (0.1) OVER 0 GO:0006366 transcription from Pol II promoter 845 0.225 (0.012) 0.130 (0.002) FASTER 1.88E-14 13.0 (0.5) 4.8 (0.1) OVER 0 GO:0006139 nucleobase, nucleoside, nucleotide and nucleic acid metabolism3004 0.173 (0.006) 0.127 (0.002) FASTER 1.28E-12 8.4 (0.2) 4.5 (0.1) OVER 0 GO:0006357 regulation of transcription from Pol II promoter 487 0.231 (0.016) 0.132 (0.002) FASTER 6.05E-10 13.5 (0.6) 4.9 (0.1) OVER 0 GO:0008283 cell proliferation 625 0.189 (0.014) 0.132 (0.002) FASTER 1.95E-05 10.1 (0.6) 5.0 (0.1) OVER 1.50E-20 GO:0006513 monoubiquitination 36 0.305 (0.049) 0.134 (0.002) FASTER 2.69E-04 25.4 (4.4) 5.1 (0.1) OVER 2.04E-06 GO:0007050 cell cycle arrest 57 0.311 (0.054) 0.133 (0.002) -
(12) Patent Application Publication (10) Pub. No.: US 2008/0057509 A1 Lupski Et Al
US 2008005.7509A1 (19) United States (12) Patent Application Publication (10) Pub. No.: US 2008/0057509 A1 Lupski et al. (43) Pub. Date: Mar. 6, 2008 (54) DEFECTS IN PERIAXIN ASSOCIATED WITH (60) Provisional application No. 60/255.217, filed on Dec. MYELINOPATHIES 13, 2000. (76) Inventors: James R. Lupski, Houston, TX (US); Publication Classification Cornelius F. Boerkoel III, Houston, TX (US); Hiroshi Takashima, Houston, (51) Int. Cl. TX (US) CI2O I/68 (2006.01) (52) U.S. Cl. .................................................................. 435/6 Correspondence Address: FULBRIGHT & JAWORSKI, LLP 1301 MCKNNEY SUTE 51OO (57) ABSTRACT HOUSTON, TX 77010-3095 (US) (21) Appl. No.: 11/838,500 The present invention relates to defects in periaxin (PRX) associated with myelinopathies, including Charcot-Marie (22) Filed: Aug. 14, 2007 Tooth syndrome and/or Deerine-Sottas syndrome. Unre lated individuals having a myelinopathy from Dejerine Related U.S. Application Data Sottas syndrome have recessive PRX mutations. The PRX locus maps to a region associated with a severe autosomal (63) Continuation of application No. 10/021,955, filed on recessive demyelinating neuropathy and is also syntenic to Dec. 13, 2001, now Pat. No. 7,273,698. the Prx location on murine chromosome 7. PN-44. v Fifi is Gf * is f. f i? it it it it i? it is 86 if f : Gift it if is f. 6 it is a a is 8 is a B g g it a fit i AN AIK hetero 45A homoliSA homoASA CSX 7 Six Taar a via a unania t fi : Yi 3 y Clas?.(CENELY I II. Ex. -
Individual Protomers of a G Protein-Coupled Receptor Dimer Integrate Distinct Functional Modules
OPEN Citation: Cell Discovery (2015) 1, 15011; doi:10.1038/celldisc.2015.11 © 2015 SIBS, CAS All rights reserved 2056-5968/15 ARTICLE www.nature.com/celldisc Individual protomers of a G protein-coupled receptor dimer integrate distinct functional modules Nathan D Camp1, Kyung-Soon Lee2, Jennifer L Wacker-Mhyre2, Timothy S Kountz2, Ji-Min Park2, Dorathy-Ann Harris2, Marianne Estrada2, Aaron Stewart2, Alejandro Wolf-Yadlin1, Chris Hague2 1Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA; 2Department of Pharmacology, University of Washington School of Medicine, Seattle, WA, USA Recent advances in proteomic technology reveal G-protein-coupled receptors (GPCRs) are organized as large, macromolecular protein complexes in cell membranes, adding a new layer of intricacy to GPCR signaling. We previously reported the α1D-adrenergic receptor (ADRA1D)—a key regulator of cardiovascular, urinary and CNS function—binds the syntrophin family of PDZ domain proteins (SNTA, SNTB1, and SNTB2) through a C-terminal PDZ ligand inter- action, ensuring receptor plasma membrane localization and G-protein coupling. To assess the uniqueness of this novel GPCR complex, 23 human GPCRs containing Type I PDZ ligands were subjected to TAP/MS proteomic analysis. Syntrophins did not interact with any other GPCRs. Unexpectedly, a second PDZ domain protein, scribble (SCRIB), was detected in ADRA1D complexes. Biochemical, proteomic, and dynamic mass redistribution analyses indicate syntrophins and SCRIB compete for the PDZ ligand, simultaneously exist within an ADRA1D multimer, and impart divergent pharmacological properties to the complex. Our results reveal an unprecedented modular dimeric architecture for the ADRA1D in the cell membrane, providing unexpected opportunities for fine-tuning receptor function through novel protein interactions in vivo, and for intervening in signal transduction with small molecules that can stabilize or disrupt unique GPCR:PDZ protein interfaces. -
Feeling the Force: Role of Amotl2 in Normal Development and Cancer
Department of Oncology and Pathology Karolinska Institute, Stockholm, Sweden FEELING THE FORCE: ROLE OF AMOTL2 IN NORMAL DEVELOPMENT AND CANCER Aravindh Subramani Stockholm 2019 All previously published papers were reproduced with permission from the publisher. Front cover was modified from ©Renaud Chabrier and illustrated by Yu-Hsuan Hsu Published by Karolinska Institute. Printed by: US-AB Stockholm © Aravindh Subramani, 2019 ISBN 978-91-7831-426-3 Feeling the force: Role of AmotL2 in normal development and cancer. THESIS FOR DOCTORAL DEGREE (Ph.D.) J3:04, Torsten N Wiesel, U410033310, Bioclinicum, Karolinska University Hospital, Solna, Stockholm Friday, April 12th, 2019 at 13:00 By Aravindh Subramani Principal Supervisor: Opponent: Professor. Lars Holmgren Professor. Marius Sudol Karolinska Institute National University of Singapore Department of Oncology-Pathology Mechanobiology Institute (MBI) Co-supervisor(s): Examination Board: Docent. Jonas Fuxe Docent. Kaisa Lehti Karolinska Institute Karolinska institute Department of Microbiology, Tumor and Cell Department of Microbiology and Tumor Biology Biology (MTC) center (MTC) Associate Professor. Johan Hartman Docent. Ingvar Ferby Karolinska Institute Uppsala University Department of Oncology-Pathology Department of Medical Biochemistry and Microbiology Docent. Mimmi Shoshan Karolinska Institute Department of Oncology-Pathology To my mom and dad “Real knowledge is to know the extent of one's ignorance.” (Confucius) ABSTRACT Cells that fabricate the body, dwell in a very heterogeneous environment. Self-organization of individual cells into complex tissues and organs at the time of growth and revival is brought about by the combinatory action of biomechanical and biochemical signaling processes. Tissue generation and functional organogenesis, requires distinct cell types to unite together and associate with their corresponding microenvironment in a spatio-temporal manner. -
A Cell Junctional Protein Network Associated with Connexin-26
International Journal of Molecular Sciences Communication A Cell Junctional Protein Network Associated with Connexin-26 Ana C. Batissoco 1,2,* ID , Rodrigo Salazar-Silva 1, Jeanne Oiticica 2, Ricardo F. Bento 2 ID , Regina C. Mingroni-Netto 1 and Luciana A. Haddad 1 1 Human Genome and Stem Cell Research Center, Department of Genetics and Evolutionary Biology, Instituto de Biociências, Universidade de São Paulo, 05508-090 São Paulo, Brazil; [email protected] (R.S.-S.); [email protected] (R.C.M.-N.); [email protected] (L.A.H.) 2 Laboratório de Otorrinolaringologia/LIM32, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo, 01246-903 São Paulo, Brazil; [email protected] (J.O.); [email protected] (R.F.B.) * Correspondence: [email protected]; Tel.: +55-11-30617166 Received: 17 July 2018; Accepted: 21 August 2018; Published: 27 August 2018 Abstract: GJB2 mutations are the leading cause of non-syndromic inherited hearing loss. GJB2 encodes connexin-26 (CX26), which is a connexin (CX) family protein expressed in cochlea, skin, liver, and brain, displaying short cytoplasmic N-termini and C-termini. We searched for CX26 C-terminus binding partners by affinity capture and identified 12 unique proteins associated with cell junctions or cytoskeleton (CGN, DAAM1, FLNB, GAPDH, HOMER2, MAP7, MAPRE2 (EB2), JUP, PTK2B, RAI14, TJP1, and VCL) by using mass spectrometry. We show that, similar to other CX family members, CX26 co-fractionates with TJP1, VCL, and EB2 (EB1 paralogue) as well as the membrane-associated protein ASS1. The adaptor protein CGN (cingulin) co-immuno-precipitates with CX26, ASS1, and TJP1.