Supplementary Table 3 Gene Microarray Analysis: PRL+E2 Vs
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TBXA2R Rsnps, Transcriptional Factor Binding Sites and Asthma in Asians
Open Journal of Pediatrics, 2014, 4, 148-161 Published Online June 2014 in SciRes. http://www.scirp.org/journal/ojped http://dx.doi.org/10.4236/ojped.2014.42021 TBXA2R rSNPs, Transcriptional Factor Binding Sites and Asthma in Asians Norman E. Buroker Department of Pediatrics, University of Washington, Seattle, USA Email: [email protected] Received 25 January 2014; revised 20 February 2014; accepted 27 February 2014 Copyright © 2014 by author and Scientific Research Publishing Inc. This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/ Abstract Four regulatory single nucleotide polymorphisms (rSNPs) (rs2238631, rs2238632, rs2238633 and rs2238634) in intron one, two rSNPs (rs1131882 and rs4523) in exon 3 and one rSNP (rs5756) in the 3’UTR of the thromboxane A2 receptor (TBXA2R) gene have been associated with childhood- onset asthma in Asians. These rSNP alleles alter the DNA landscape for potential transcriptional factors (TFs) to attach resulting in changes in transcriptional factor binding sites (TFBS). These TFBS changes are examined with respect to asthma which has been found to be significantly asso- ciated with the rSNPs. Keywords TBXA2R, rSNPs, TFBS, Asthma 1. Introduction Asthma is a chronic inflammatory condition of the airways characterized by recurrent episodes of reversible air- way obstruction and increased bronchial hyper-responsiveness which results from the interactions between gen- es and environmental factors [1]-[3]. Asthma causes episodes of wheeze, cough, and shortness of breath [4]. Re- cent studies indicate that the genetic factors of childhood-onset asthma differ from those of adult-onset asthma [3] [5]. -
The Wiskott-Aldrich Syndrome: the Actin Cytoskeleton and Immune Cell Function
Disease Markers 29 (2010) 157–175 157 DOI 10.3233/DMA-2010-0735 IOS Press The Wiskott-Aldrich syndrome: The actin cytoskeleton and immune cell function Michael P. Blundella, Austen Wortha,b, Gerben Boumaa and Adrian J. Thrashera,b,∗ aMolecular Immunology Unit, UCL Institute of Child Health, London, UK bDepartment of Immunology, Great Ormond Street Hospital NHS Trust, Great Ormond Street, London, UK Abstract. Wiskott-Aldrich syndrome (WAS) is a rare X-linked recessive primary immunodeficiency characterised by immune dysregulation, microthrombocytopaenia, eczema and lymphoid malignancies. Mutations in the WAS gene can lead to distinct syndrome variations which largely, although not exclusively, depend upon the mutation. Premature termination and deletions abrogate Wiskott-Aldrich syndrome protein (WASp) expression and lead to severe disease (WAS). Missense mutations usually result in reduced protein expression and the phenotypically milder X-linked thrombocytopenia (XLT) or attenuated WAS [1–3]. More recently however novel activating mutations have been described that give rise to X-linked neutropenia (XLN), a third syndrome defined by neutropenia with variable myelodysplasia [4–6]. WASP is key in transducing signals from the cell surface to the actin cytoskeleton, and a lack of WASp results in cytoskeletal defects that compromise multiple aspects of normal cellular activity including proliferation, phagocytosis, immune synapse formation, adhesion and directed migration. Keywords: Wiskott-Aldrich syndrome, actin polymerization, lymphocytes, -
Viewed Under 23 (B) Or 203 (C) fi M M Male Cko Mice, and Largely Unaffected Magni Cation; Scale Bars, 500 M (B) and 50 M (C)
BRIEF COMMUNICATION www.jasn.org Renal Fanconi Syndrome and Hypophosphatemic Rickets in the Absence of Xenotropic and Polytropic Retroviral Receptor in the Nephron Camille Ansermet,* Matthias B. Moor,* Gabriel Centeno,* Muriel Auberson,* † † ‡ Dorothy Zhang Hu, Roland Baron, Svetlana Nikolaeva,* Barbara Haenzi,* | Natalya Katanaeva,* Ivan Gautschi,* Vladimir Katanaev,*§ Samuel Rotman, Robert Koesters,¶ †† Laurent Schild,* Sylvain Pradervand,** Olivier Bonny,* and Dmitri Firsov* BRIEF COMMUNICATION *Department of Pharmacology and Toxicology and **Genomic Technologies Facility, University of Lausanne, Lausanne, Switzerland; †Department of Oral Medicine, Infection, and Immunity, Harvard School of Dental Medicine, Boston, Massachusetts; ‡Institute of Evolutionary Physiology and Biochemistry, St. Petersburg, Russia; §School of Biomedicine, Far Eastern Federal University, Vladivostok, Russia; |Services of Pathology and ††Nephrology, Department of Medicine, University Hospital of Lausanne, Lausanne, Switzerland; and ¶Université Pierre et Marie Curie, Paris, France ABSTRACT Tight control of extracellular and intracellular inorganic phosphate (Pi) levels is crit- leaves.4 Most recently, Legati et al. have ical to most biochemical and physiologic processes. Urinary Pi is freely filtered at the shown an association between genetic kidney glomerulus and is reabsorbed in the renal tubule by the action of the apical polymorphisms in Xpr1 and primary fa- sodium-dependent phosphate transporters, NaPi-IIa/NaPi-IIc/Pit2. However, the milial brain calcification disorder.5 How- molecular identity of the protein(s) participating in the basolateral Pi efflux remains ever, the role of XPR1 in the maintenance unknown. Evidence has suggested that xenotropic and polytropic retroviral recep- of Pi homeostasis remains unknown. Here, tor 1 (XPR1) might be involved in this process. Here, we show that conditional in- we addressed this issue in mice deficient for activation of Xpr1 in the renal tubule in mice resulted in impaired renal Pi Xpr1 in the nephron. -
An Order Estimation Based Approach to Identify Response Genes
AN ORDER ESTIMATION BASED APPROACH TO IDENTIFY RESPONSE GENES FOR MICRO ARRAY TIME COURSE DATA A Thesis Presented to The Faculty of Graduate Studies of The University of Guelph by ZHIHENG LU In partial fulfilment of requirements for the degree of Doctor of Philosophy September, 2008 © Zhiheng Lu, 2008 Library and Bibliotheque et 1*1 Archives Canada Archives Canada Published Heritage Direction du Branch Patrimoine de I'edition 395 Wellington Street 395, rue Wellington Ottawa ON K1A0N4 Ottawa ON K1A0N4 Canada Canada Your file Votre reference ISBN: 978-0-494-47605-5 Our file Notre reference ISBN: 978-0-494-47605-5 NOTICE: AVIS: The author has granted a non L'auteur a accorde une licence non exclusive exclusive license allowing Library permettant a la Bibliotheque et Archives and Archives Canada to reproduce, Canada de reproduire, publier, archiver, publish, archive, preserve, conserve, sauvegarder, conserver, transmettre au public communicate to the public by par telecommunication ou par Plntemet, prefer, telecommunication or on the Internet, distribuer et vendre des theses partout dans loan, distribute and sell theses le monde, a des fins commerciales ou autres, worldwide, for commercial or non sur support microforme, papier, electronique commercial purposes, in microform, et/ou autres formats. paper, electronic and/or any other formats. The author retains copyright L'auteur conserve la propriete du droit d'auteur ownership and moral rights in et des droits moraux qui protege cette these. this thesis. Neither the thesis Ni la these ni des extraits substantiels de nor substantial extracts from it celle-ci ne doivent etre imprimes ou autrement may be printed or otherwise reproduits sans son autorisation. -
Table 2. Significant
Table 2. Significant (Q < 0.05 and |d | > 0.5) transcripts from the meta-analysis Gene Chr Mb Gene Name Affy ProbeSet cDNA_IDs d HAP/LAP d HAP/LAP d d IS Average d Ztest P values Q-value Symbol ID (study #5) 1 2 STS B2m 2 122 beta-2 microglobulin 1452428_a_at AI848245 1.75334941 4 3.2 4 3.2316485 1.07398E-09 5.69E-08 Man2b1 8 84.4 mannosidase 2, alpha B1 1416340_a_at H4049B01 3.75722111 3.87309653 2.1 1.6 2.84852656 5.32443E-07 1.58E-05 1110032A03Rik 9 50.9 RIKEN cDNA 1110032A03 gene 1417211_a_at H4035E05 4 1.66015788 4 1.7 2.82772795 2.94266E-05 0.000527 NA 9 48.5 --- 1456111_at 3.43701477 1.85785922 4 2 2.8237185 9.97969E-08 3.48E-06 Scn4b 9 45.3 Sodium channel, type IV, beta 1434008_at AI844796 3.79536664 1.63774235 3.3 2.3 2.75319499 1.48057E-08 6.21E-07 polypeptide Gadd45gip1 8 84.1 RIKEN cDNA 2310040G17 gene 1417619_at 4 3.38875643 1.4 2 2.69163229 8.84279E-06 0.0001904 BC056474 15 12.1 Mus musculus cDNA clone 1424117_at H3030A06 3.95752801 2.42838452 1.9 2.2 2.62132809 1.3344E-08 5.66E-07 MGC:67360 IMAGE:6823629, complete cds NA 4 153 guanine nucleotide binding protein, 1454696_at -3.46081884 -4 -1.3 -1.6 -2.6026947 8.58458E-05 0.0012617 beta 1 Gnb1 4 153 guanine nucleotide binding protein, 1417432_a_at H3094D02 -3.13334396 -4 -1.6 -1.7 -2.5946297 1.04542E-05 0.0002202 beta 1 Gadd45gip1 8 84.1 RAD23a homolog (S. -
Supplementary Table S1. Upregulated Genes Differentially
Supplementary Table S1. Upregulated genes differentially expressed in athletes (p < 0.05 and 1.3-fold change) Gene Symbol p Value Fold Change 221051_s_at NMRK2 0.01 2.38 236518_at CCDC183 0.00 2.05 218804_at ANO1 0.00 2.05 234675_x_at 0.01 2.02 207076_s_at ASS1 0.00 1.85 209135_at ASPH 0.02 1.81 228434_at BTNL9 0.03 1.81 229985_at BTNL9 0.01 1.79 215795_at MYH7B 0.01 1.78 217979_at TSPAN13 0.01 1.77 230992_at BTNL9 0.01 1.75 226884_at LRRN1 0.03 1.74 220039_s_at CDKAL1 0.01 1.73 236520_at 0.02 1.72 219895_at TMEM255A 0.04 1.72 201030_x_at LDHB 0.00 1.69 233824_at 0.00 1.69 232257_s_at 0.05 1.67 236359_at SCN4B 0.04 1.64 242868_at 0.00 1.63 1557286_at 0.01 1.63 202780_at OXCT1 0.01 1.63 1556542_a_at 0.04 1.63 209992_at PFKFB2 0.04 1.63 205247_at NOTCH4 0.01 1.62 1554182_at TRIM73///TRIM74 0.00 1.61 232892_at MIR1-1HG 0.02 1.61 204726_at CDH13 0.01 1.6 1561167_at 0.01 1.6 1565821_at 0.01 1.6 210169_at SEC14L5 0.01 1.6 236963_at 0.02 1.6 1552880_at SEC16B 0.02 1.6 235228_at CCDC85A 0.02 1.6 1568623_a_at SLC35E4 0.00 1.59 204844_at ENPEP 0.00 1.59 1552256_a_at SCARB1 0.02 1.59 1557283_a_at ZNF519 0.02 1.59 1557293_at LINC00969 0.03 1.59 231644_at 0.01 1.58 228115_at GAREM1 0.01 1.58 223687_s_at LY6K 0.02 1.58 231779_at IRAK2 0.03 1.58 243332_at LOC105379610 0.04 1.58 232118_at 0.01 1.57 203423_at RBP1 0.02 1.57 AMY1A///AMY1B///AMY1C///AMY2A///AMY2B// 208498_s_at 0.03 1.57 /AMYP1 237154_at LOC101930114 0.00 1.56 1559691_at 0.01 1.56 243481_at RHOJ 0.03 1.56 238834_at MYLK3 0.01 1.55 213438_at NFASC 0.02 1.55 242290_at TACC1 0.04 1.55 ANKRD20A1///ANKRD20A12P///ANKRD20A2/// -
Supplementary Data
Supplemental Data A novel mouse model of X-linked nephrogenic diabetes insipidus: Phenotypic analysis and therapeutic implications Jian Hua Li, Chung-Lin Chou, Bo Li, Oksana Gavrilova, Christoph Eisner, Jürgen Schnermann, Stasia A. Anderson, Chu-Xia Deng, Mark A. Knepper, and Jürgen Wess Supplemental Methods Metabolic cage studies. Animals were maintained in mouse metabolic cages (Hatteras Instruments, Cary, NC) under controlled temperature and light conditions (12 hr light and dark cycles). Mice received a fixed daily ration of 6.5 g of gelled diet per 20 g of body weight per day. The gelled diet was composed of 4 g of Basal Diet 5755 (Test Diet, Richmond, IN), 2.5 ml of deionized water, and 65 mg agar. Preweighted drinking water was provided ad libitum during the course of the study. Mice were acclimated in the metabolic cages for 1-2 days. Urine was collected under mineral oil in preweighted collection vials for successive 24 hr periods. Analysis of GPCR expression in mouse IMCD cells via TaqMan real-time qRT-PCR. Total RNA prepared from mouse IMCD tubule suspensions was reverse transcribed as described under Experimental Procedures. Tissues from ten 10-week old C57BL/6 WT mice were collected and pooled for each individual experiment. cDNA derived from 640 ng of RNA was mixed with an equal volume of TaqMan gene expression 2 x master mix (Applied Biosystems, Foster City, CA). 100 μl-aliquots of this mixture (corresponding to 80 ng of RNA) were added to each of the 8 fill ports of a 384-well plate of a mouse GPCR array panel (Applied Biosystems). -
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. -
Meta-Analyses of Expression Profiling Data in the Postmortem
META-ANALYSES OF EXPRESSION PROFILING DATA IN THE POSTMORTEM HUMAN BRAIN by Meeta Mistry B.Sc., McMaster University, 2005 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE STUDIES (Bioinformatics) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) July 2012 © Meeta Mistry, 2012 Abstract Schizophrenia is a severe psychiatric illness for which the precise etiology remains unknown. Studies using postmortem human brain have become increasingly important in schizophrenia research, providing an opportunity to directly investigate the diseased brain tissue. Gene expression profiling technologies have been used by a number of groups to explore the postmortem human brain and seek genes which show changes in expression correlated with schizophrenia. While this has been a valuable means of generating hypotheses, there is a general lack of consensus in the findings across studies. Expression profiling of postmortem human brain tissue is difficult due to the effect of various factors that can confound the data. The first aim of this thesis was to use control postmortem human cortex for identification of expression changes associated with several factors, specifically: age, sex, brain pH and postmortem interval. I conducted a meta-analysis across the control arm of eleven microarray datasets (representing over 400 subjects), and identified a signature of genes associated with each factor. These genes provide critical information towards the identification of problematic genes when investigating postmortem human brain in schizophrenia and other neuropsychiatric illnesses. The second aim of this thesis was to evaluate gene expression patterns in the prefrontal cortex associated with schizophrenia by exploring two methods of analysis: differential expression and coexpression. -
Supplementary Table 1: Adhesion Genes Data Set
Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like, -
Molecular Analysis of FOXC1 in Subjects Presenting with Severe Developmental Eye Anomalies
Molecular Vision 2009; 15:1366-1373 <http://www.molvis.org/molvis/v15/a144> © 2009 Molecular Vision Received 25 February 2009 | Accepted 10 July 2009 | Published 13 July 2009 Molecular analysis of FOXC1 in subjects presenting with severe developmental eye anomalies Kulvinder Kaur,1 Nicola K. Ragge,2,3 Jiannis Ragoussis1 1Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK; 2Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK; 3Moorfields Eye Hospital, London and Birmingham Children’s Hospital, Birmingham, UK Purpose: Haploinsufficiency through mutation or deletion of the forkhead transcription factor, FOXC1, causes Axenfeld- Rieger anomaly, which manifests as a range of anterior segment eye defects and glaucoma. The aim of this study is to establish whether mutation of FOXC1 contributes toward other developmental eye anomalies, namely anophthalmia, microphthalmia, and coloboma. Methods: The coding sequence and 3`-UTR of FOXC1 was analyzed in 114 subjects with severe developmental eye anomalies by bidirectional direct sequencing. Results: Four coding FOXC1 variations (two novel missense variations, one insertion, and one novel deletion) were identified in the cohort. Two noncoding variations were also identified in the 3′-UTR. The missense mutations were c. 889C_T and c.1103C_A, resulting in p.Pro297Ser and p.Thr368Asn, respectively. The c.889C_T transition was identified in 19 of the 100 unaffected control samples. The c.1103C_A transversion resulted in a conservative substitution in an unconserved amino acid and was deemed unlikely to be pathogenic. A c.1142_1144insGCG change resulting in p.Gly380ins, which was previously associated with kidney anomalies, was identified in 44 of the 114 affected individuals. -
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Published OnlineFirst January 23, 2019; DOI: 10.1158/0008-5472.CAN-18-1261 Cancer Genome and Epigenome Research Sleeping Beauty Insertional Mutagenesis Reveals Important Genetic Drivers of Central Nervous System Embryonal Tumors Pauline J. Beckmann1, Jon D. Larson1, Alex T. Larsson1, Jason P. Ostergaard1, Sandra Wagner1, Eric P. Rahrmann1,2, Ghaidan A. Shamsan3, George M. Otto1,4, Rory L. Williams1,5, Jun Wang6, Catherine Lee6, Barbara R. Tschida1, Paramita Das1, Adrian M. Dubuc7, Branden S. Moriarity1, Daniel Picard8,9, Xiaochong Wu10, Fausto J. Rodriguez11, Quincy Rosemarie1,12, Ryan D. Krebs1, Amy M. Molan1,13, Addison M. Demer1, Michelle M. Frees1, Anthony E. Rizzardi14, Stephen C. Schmechel14,15, Charles G. Eberhart16, Robert B. Jenkins17, Robert J. Wechsler-Reya6, David J. Odde3, Annie Huang18, Michael D. Taylor10, Aaron L. Sarver1, and David A. Largaespada1 Abstract Medulloblastoma and central nervous system primitive identified several putative proto-oncogenes including Arh- neuroectodermal tumors (CNS-PNET) are aggressive, poorly gap36, Megf10,andFoxr2. Genetic manipulation of these differentiated brain tumors with limited effective therapies. genes demonstrated a robust impact on tumorigenesis Using Sleeping Beauty (SB) transposon mutagenesis, we in vitro and in vivo. We also determined that FOXR2 interacts identified novel genetic drivers of medulloblastoma and with N-MYC, increases C-MYC protein stability, and acti- CNS-PNET. Cross-species gene expression analyses classified vates FAK/SRC signaling. Altogether, our study identified SB-driven tumors into distinct medulloblastoma and several promising therapeutic targets in medulloblastoma CNS-PNET subgroups, indicating they resemble human and CNS-PNET. Sonic hedgehog and group 3 and 4 medulloblastoma and CNS neuroblastoma with FOXR2 activation.