DOCSLIB.ORG

Supporting Information

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Supporting Information Supporting Information Xu et al. 10.1073/pnas.0908584106 SI Text (Fig. S1). Of the 15 families with a history of SCZ in a Supporting Information. While most of the genes in Table S3 have second-degree relative, 11 are avuncular pairs, three are grand- not been directly associated with schizophrenia (SCZ) in the parent-grandchild pairs, and one family is both. For our linkage literature, some of them have been implicated in psychiatric and studies, we genotyped 479 subjects from 130 families. Sixty-nine other neurobehavioral disorders or in mechanisms that may families are informative. In the 54 informative families with at underlie predisposition to such disorders. Two examples (NRG3 least two affected members, there are 60 and 79 affected relative and RAPGEF2) are discussed in the main text, but a few pairs for the narrow and broad affection categories, respectively. additional examples are provided below: Of the broadly affected relative pairs, 30 are sibling, 24 are parent-child, 14 are avuncular, six are cousin, three are second The Contactin Family. Burbach and van der Zwaag (1) recently cousin, and two are grandparent-grandchild. provided a detailed account of the contactin system and its All subjects were confirmed as Afrikaners by tracing ancestry potential contribution to a number of different psychiatric and back to the 1800s using state and church records and finally to neurobehavioral disorders, including SCZ and autism. In an the initial 2,000 founders through the Genealogies of Old South early study, Fernandez et al. (2, 3) showed that disruption of African Families. Diagnostic evaluations were conducted in- contactin 4 (CNTN4) results in developmental delay and other person by specially trained clinicians using the DIGS, which was features of the 3p deletion syndrome. In the present study, we translated and back-translated into Afrikaans. Upon completion identified a CNV at Ϸ130 kb downstream of CNTN6 (also named of the DIGS, the interviewers assigned DSM-IV diagnoses and NB3), another member of the contactin protein family. Inter- completed a detailed narrative report. All narratives and DIGS estingly, in an independent study, we identified another CNV were independently evaluated by appropriately trained clinicians disrupting the contactin associated protein 2 (CNTNAP2) that in New York. co-segregates with psychosis in one family. Structural variants in the CNTNAP2 gene have been reported in patients with psy- Sample Characteristics. The familial cases sample consisted of 31 chosis in at least two previous genome-wide scans (4, 5). Thus, males (65%) and 17 females (35%) and both their biological our results support the notion that abnormalities in the contactin parents. The sample enriched in sporadic cases consisted of 108 family proteins may be involved in SCZ and other psychiatric males (71%) and 44 females (29%) and both their unaffected conditions. biological parents. The control sample consisted of 93 females (58%) and 66 males (42%) and both their biological parents. It The CSMD1 (CUB and Sushi Multiple Domains 1) Gene. One CNV should be noted that both in this study and our previous Xu et identified in the present study is a duplication at 8p23.1–8p23.2 al. (11) study we did not find any sex-specific differences in involving the CSMD1 gene. A recent study (6) showed that a distribution of CNVs. We checked for population stratification transmitted duplication at 8p23.1–8p23.2 affecting the CSMD1 between cases and controls using principal component analysis gene may be associated with speech delay, autism, and learning as implemented in EIGENSTRAT (12). Both groups overlap in difficulties. the graphical representation of the top two principal compo- The ADARB1 (adenosine deaminase, RNA-specific, B1) gene: nents (eigenvectors), indicating no evidence of stratification. ADARB1 (also named ADAR2) encodes for adenosine deami- The phenotypic variables analyzed in the CNV scan, were nase, a key RNA editing enzyme. Although ADARB1 has not defined as follows: History of developmental delay was recorded been directly associated with psychiatric conditions, mRNAs for as positive when there was clear history of maturation lag or several important neuronal receptors such as 5-HT2CR and milestone delays before the age of 6 (i.e., delayed crawling, GLUR2 undergo posttranscriptional editing. Abnormal editing of HT2CR has been implicated in depression and SCZ (7). walking, speaking, etc.). History of learning disabilities was Other potentially interesting genes include the RXFP2 (relax- recorded as positive if there had been a diagnosis of a learning in/insulin-like family peptide receptor 2) gene (also known as disability, or clear history of being a ‘‘slow learner,’’ requiring LGR8), a member of the relaxin family peptide receptor system remediation at school, or placement in a special class. Age at whose members are distributed in both excitatory and inhibitory onset was defined as the age at which full DSM criteria for neurons in the brain and modulate diverse behaviors (8), as well schizophrenia or schizoaffective disorder were met. as the LRFN5 (leucine-rich repeat and fibronectin type III domain containing 5) gene (also named SALM5), which is Genotyping. For the linkage analysis, genotyping for 2005 di-, tri-, expressed exclusively in neuronal tissues, especially in mature and tetra-nucleotide repeat microsatellite markers was per- neurons. Several members of the LRFN protein family were formed by deCODE (Reykjavik, Iceland), through their fee-for- shown to associate with PSD-95 (9, 10). service genotyping facility. Among them, 1,904 autosomal mark- ers and 76 chromosome X markers passed our internal quality SI Methods checks. Of the 960,395 possible genotypes, 878,046 were suc- Patient Cohorts. We performed a genome-wide survey of rare cessfully called, corresponding to an average (ϮSD) per marker inherited CNVs in a total of 182 individuals, consisting of 48 genotyping rate of 91% (Ϯ7%). probands with familial SCZ (positive disease history in a first- For the CNV analysis, the families were genotyped using degree (n ϭ 33) or second-degree (n ϭ 15) relative and both of Human Genome-Wide SNP Array 5.0 (Affymetrix), which con- their biological parents, as well as all additional affected relatives tains 500,568 SNPs, as well as 420,000 additional nonpolymor- that were available for genotyping. Of the 33 families with a phic probes that can assess other genetic differences, such as CN history of SCZ in a first-degree relative, 17 are parent-child variation. Samples were processed as previously described (11). pairs, 12 are sibling pairs, and four families are both. In eight of Average call rate on arrays used in this study was 99.43%. All these 33 families, in addition to the first-degree relative, there is microarray experiments were performed in the Vanderbilt Mi- at least one second-degree relative who is also affected with SCZ croarray Shared Resource directed by Dr. Shawn Levy. Xu et al. www.pnas.org/cgi/content/short/0908584106 1of15 CNV Identification, Inherited CNV Detection, and Inherited CNV Ver- in length. The borders listed are the outermost borders defined ification. CEL files from all chips were analyzed using two by either analysis. software packages, DNA-Chip Analyzer (dChip) and Partek (iii) Rare inherited CNV detection: The CNV list generated Genomics Suite (Partek software, version 6.3 Beta, build above was first divided into two lists, a deletion list (mean CN Ͻ #6.07.1127; Partek), as previously described (11). The entire 1.25 for autosomal or mean CN Ͻ 0.25 for chromosome X) and procedure included five steps: (i) quality control; (ii) CNV a duplication list (mean CN Ͼ 2.75 for autosomal or mean CN Ͼ identification; (iii) inherited CNV detection; (iv) inherited CNV 1.75 for chromosome X). Deletion and duplication analyses were verification by intensity and genotyping filters; and (v) inherited conducted separately. A candidate inherited CNV was consid- CNV confirmation by MLPA. ered for further analysis only if there was more than 50% overlap (i) Quality control: A quality control step was conducted to in size with a variant at the same locus in the biological parental exclude families with one or more hybridization failures. chromosomes (size of overlap/total size of merged CNVs Ͼ 0.5), (ii) CNV identification: All CEL files that passed the quality but less than 50% overlap in size with any variant in the other control step were imported and analyzed by dCHIP (13–15) and parental chromosomes. Partek according to the authors’ instructions. For the dCHIP (iv) Inherited CNV verification using genotype information analysis, data were processed in batches, each batch containing and median smoothing inferred CN: The vast majority of CNVs arrays processed simultaneously in 96-well plate formats. An are inherited from parents (16) and since the false-positive or array with median overall intensity within each batch was chosen false-negative prediction rate is relatively high in all available as the baseline to adjust the brightness of all arrays to a CNV detection algorithms (17), it is important to use indepen- comparable level. Arrays were then normalized at probe inten- dent CNV inferring methods, as well as family information for sity level using the Invariant Set Normalization procedure (14). validation of inherited CNV calling results. Genotyping calls and Following normalization, a CNV identification step ensued. A Median smoothing inferred CN calls for all samples were stored reference signal value was first calculated for each probe set in MySQL database (version 5.1) along with the related pedigree using a model-based method. To obtain reference signal distri- information. For each identified candidate CNV, all genotypes bution (blind to the affected status information), we assumed and inferred CN of SNPs within the region were retrieved for that for any locus, less than 10% of all of the samples show each triad (the subject and his/her parents).
Load more

Recommended publications
  • The Title of the Article
    Mechanism-Anchored Profiling Derived from Epigenetic Networks Predicts Outcome in Acute Lymphoblastic Leukemia Xinan Yang, PhD1, Yong Huang, MD1, James L Chen, MD1, Jianming Xie, MSc2, Xiao Sun, PhD2, Yves A Lussier, MD1,3,4§ 1Center for Biomedical Informatics and Section of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL 60637 USA 2State Key Laboratory of Bioelectronics, Southeast University, 210096 Nanjing, P.R.China 3The University of Chicago Cancer Research Center, and The Ludwig Center for Metastasis Research, The University of Chicago, Chicago, IL 60637 USA 4The Institute for Genomics and Systems Biology, and the Computational Institute, The University of Chicago, Chicago, IL 60637 USA §Corresponding author Email addresses: XY: [email protected] YH: [email protected] JC: [email protected] JX: [email protected] XS: [email protected] YL: [email protected] - 1 - Abstract Background Current outcome predictors based on “molecular profiling” rely on gene lists selected without consideration for their molecular mechanisms. This study was designed to demonstrate that we could learn about genes related to a specific mechanism and further use this knowledge to predict outcome in patients – a paradigm shift towards accurate “mechanism-anchored profiling”. We propose a novel algorithm, PGnet, which predicts a tripartite mechanism-anchored network associated to epigenetic regulation consisting of phenotypes, genes and mechanisms. Genes termed as GEMs in this network meet all of the following criteria: (i) they are co-expressed with genes known to be involved in the biological mechanism of interest, (ii) they are also differentially expressed between distinct phenotypes relevant to the study, and (iii) as a biomodule, genes correlate with both the mechanism and the phenotype.
    [Show full text]
  • Bilateral Gene Interaction Hierarchy Analysis of the Cell Death Gene
    White et al. BMC Genomics (2016) 17:130 DOI 10.1186/s12864-016-2412-0 RESEARCH ARTICLE Open Access Bilateral gene interaction hierarchy analysis of the cell death gene response emphasizes the significance of cell cycle genes following unilateral traumatic brain injury Todd E. White1, Monique C. Surles-Zeigler1, Gregory D. Ford2, Alicia S. Gates1, Benem Davids1, Timothy Distel1,4, Michelle C. LaPlaca3 and Byron D. Ford1,4* Abstract Background: Delayed or secondary cell death that is caused by a cascade of cellular and molecular processes initiated by traumatic brain injury (TBI) may be reduced or prevented if an effective neuroprotective strategy is employed. Microarray and subsequent bioinformatic analyses were used to determine which genes, pathways and networks were significantly altered 24 h after unilateral TBI in the rat. Ipsilateral hemi-brain, the corresponding contralateral hemi-brain, and naïve (control) brain tissue were used for microarray analysis. Results: Ingenuity Pathway Analysis showed cell death and survival (CD) to be a top molecular and cellular function associated with TBI on both sides of the brain. One major finding was that the overall gene expression pattern suggested an increase in CD genes in ipsilateral brain tissue and suppression of CD genes contralateral to the injury which may indicate an endogenous protective mechanism. We created networks of genes of interest (GOI) and ranked the genes by the number of direct connections each had in the GOI networks, creating gene interaction hierarchies (GIHs). Cell cycle was determined from the resultant GIHs to be a significant molecular and cellular function in post-TBI CD gene response.
    [Show full text]
  • 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.
    [Show full text]
  • Regulation and Evolutionary Origins of Repulsive
    REGULATION AND EVOLUTIONARY ORIGINS OF REPULSIVE GUIDANCE MOLECULE C / HEMOJUVELIN EXPRESSION: A MUSCLE-ENRICHED GENE INVOLVED IN IRON METABOLISM by Christopher John Severyn B.A. (University of California, Berkeley) 2002 A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in BIOCHEMISTRY AND MOLECULAR BIOLOGY Presented to the Department of Biochemistry & Molecular Biology OREGON HEALTH & SCIENCE UNIVERSITY School of Medicine July 2010 Department of Biochemistry & Molecular Biology, School of Medicine OREGON HEALTH & SCIENCE UNIVERSITY _________________________________________________ CERTIFICATE OF APPROVAL _________________________________________________ This is to certify that the Ph.D. dissertation of Christopher J. Severyn has been approved by the following: __________________________ Peter Rotwein, M.D., dissertation advisor Professor of Biochemistry and Department Chair __________________________ Maureen Hoatlin, Ph.D., committee chair Associate Professor of Biochemistry __________________________ Matt Thayer, Ph.D., committee member Professor of Biochemistry __________________________ Ujwal Shinde, Ph.D., committee member Professor of Biochemistry __________________________ Jim Lundblad, M.D., Ph.D., committee member Associate Professor of Medicine and Chief of Endocrinology TABLE OF CONTENTS Page List of Tables iii List of Figures iv List of Abbreviations vii Acknowledgements xiv Publications arising from this Dissertation xvi Abstract xvii Key words xix Chapter 1: Introduction 1. 1 General Overview 2 1. 2 Expression and Regulation of RGMc 3 1. 3 Gene Regulation: Transcription from an evolutionary perspective 4 1. 4 Gene Regulation: Translation 6 1. 5 Iron Metabolism in Eukaryotes 6 1. 6 Dissertation Overview 7 Chapter 2: Repulsive Guidance Molecule Family 2. 1 Summary 15 2. 2 Introduction 16 2. 3 RGMa 16 2. 4 RGMb 21 2.
    [Show full text]
  • Copy Number Variation in Fetal Alcohol Spectrum Disorder
    Biochemistry and Cell Biology Copy number variation in fetal alcohol spectrum disorder Journal: Biochemistry and Cell Biology Manuscript ID bcb-2017-0241.R1 Manuscript Type: Article Date Submitted by the Author: 09-Nov-2017 Complete List of Authors: Zarrei, Mehdi; The Centre for Applied Genomics Hicks, Geoffrey G.; University of Manitoba College of Medicine, Regenerative Medicine Reynolds, James N.; Queen's University School of Medicine, Biomedical and Molecular SciencesDraft Thiruvahindrapuram, Bhooma; The Centre for Applied Genomics Engchuan, Worrawat; Hospital for Sick Children SickKids Learning Institute Pind, Molly; University of Manitoba College of Medicine, Regenerative Medicine Lamoureux, Sylvia; The Centre for Applied Genomics Wei, John; The Centre for Applied Genomics Wang, Zhouzhi; The Centre for Applied Genomics Marshall, Christian R.; The Centre for Applied Genomics Wintle, Richard; The Centre for Applied Genomics Chudley, Albert; University of Manitoba Scherer, Stephen W.; The Centre for Applied Genomics Is the invited manuscript for consideration in a Special Fetal Alcohol Spectrum Disorder Issue? : Keyword: Fetal alcohol spectrum disorder, FASD, copy number variations, CNV https://mc06.manuscriptcentral.com/bcb-pubs Page 1 of 354 Biochemistry and Cell Biology 1 Copy number variation in fetal alcohol spectrum disorder 2 Mehdi Zarrei,a Geoffrey G. Hicks,b James N. Reynolds,c,d Bhooma Thiruvahindrapuram,a 3 Worrawat Engchuan,a Molly Pind,b Sylvia Lamoureux,a John Wei,a Zhouzhi Wang,a Christian R. 4 Marshall,a Richard F. Wintle,a Albert E. Chudleye,f and Stephen W. Scherer,a,g 5 aThe Centre for Applied Genomics and Program in Genetics and Genome Biology, The Hospital 6 for Sick Children, Toronto, Ontario, Canada 7 bRegenerative Medicine Program, University of Manitoba, Winnipeg, Canada 8 cCentre for Neuroscience Studies, Queen's University, Kingston, Ontario, Canada.
    [Show full text]
  • Produktinformation
    Produktinformation Diagnostik & molekulare Diagnostik Laborgeräte & Service Zellkultur & Verbrauchsmaterial Forschungsprodukte & Biochemikalien Weitere Information auf den folgenden Seiten! See the following pages for more information! Lieferung & Zahlungsart Lieferung: frei Haus Bestellung auf Rechnung SZABO-SCANDIC Lieferung: € 10,- HandelsgmbH & Co KG Erstbestellung Vorauskassa Quellenstraße 110, A-1100 Wien T. +43(0)1 489 3961-0 Zuschläge F. +43(0)1 489 3961-7 [email protected] • Mindermengenzuschlag www.szabo-scandic.com • Trockeneiszuschlag • Gefahrgutzuschlag linkedin.com/company/szaboscandic • Expressversand facebook.com/szaboscandic SANTA CRUZ BIOTECHNOLOGY, INC. OR2M5 siRNA (h): sc-88564 BACKGROUND STORAGE AND RESUSPENSION Olfactory receptors are G protein-coupled receptor proteins that localize to the Store lyophilized siRNA duplex at -20° C with desiccant. Stable for at least cilia of olfactory sensory neurons where they display affinity for and bind to one year from the date of shipment. Once resuspended, store at -20° C, a variety of odor molecules. The genes encoding olfactory receptors comprise avoid contact with RNAses and repeated freeze thaw cycles. the largest family in the human genome. The binding of olfactory receptor Resuspend lyophilized siRNA duplex in 330 µl of the RNAse-free water proteins to odor molecules triggers a signal transduction cascade that leads provided. Resuspension of the siRNA duplex in 330 µl of RNAse-free water to the production of cAMP via an olfactory-enriched adenylate cyclase. This makes a 10 µM solution in a 10 µM Tris-HCl, pH 8.0, 20 mM NaCl, 1 mM event ultimately leads to transmission of action potentials to the brain and EDTA buffered solution. the subsequent perception of smell.
    [Show full text]
  • The Genetic Basis of Dupuytren's Disease Gloria Sue Yale School of Medicine, [email protected]
    Yale University EliScholar – A Digital Platform for Scholarly Publishing at Yale Yale Medicine Thesis Digital Library School of Medicine January 2014 The Genetic Basis Of Dupuytren's Disease Gloria Sue Yale School of Medicine, [email protected] Follow this and additional works at: http://elischolar.library.yale.edu/ymtdl Recommended Citation Sue, Gloria, "The Genetic Basis Of Dupuytren's Disease" (2014). Yale Medicine Thesis Digital Library. 1926. http://elischolar.library.yale.edu/ymtdl/1926 This Open Access Thesis is brought to you for free and open access by the School of Medicine at EliScholar – A Digital Platform for Scholarly Publishing at Yale. It has been accepted for inclusion in Yale Medicine Thesis Digital Library by an authorized administrator of EliScholar – A Digital Platform for Scholarly Publishing at Yale. For more information, please contact [email protected]. The Genetic Basis of Dupuytren’s Disease A Thesis Submitted to the Yale University School of Medicine In Partial Fulfillment of the Requirements for the Degree of Doctor of Medicine by Gloria R. Sue 2014 THE GENETIC BASIS OF DUPUYTREN’S DISEASE. Gloria R. Sue, Deepak Narayan. Section of Plastic and Reconstructive Surgery, Department of Surgery, Yale University School of Medicine, New Haven, CT. Dupuytren’s disease is a common heritable connective tissue disorder of poorly understood etiology. It is thought that oxidative stress pathways may play a critical role in the development of Dupuytren’s disease, given the various disease associations that have been observed. We sought to sequence the mitochondrial and nuclear genomes of patients affected with Dupuytren’s disease using next-generation sequencing technology to potentially identify genes of potential pathogenetic interest.
    [Show full text]
  • Cross-Modulatory Actions of Cell Cycle Machinery on Estrogen Receptor-Α Level and Transcriptional Activity in Breast Cancer Cells
    CROSS-MODULATORY ACTIONS OF CELL CYCLE MACHINERY ON ESTROGEN RECEPTOR-α LEVEL AND TRANSCRIPTIONAL ACTIVITY IN BREAST CANCER CELLS BY SHWETA BHATT DISSERTATION Submitted In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Biochemistry in the Graduate College of the University of Illinois at Urbana-Champaign, 2010 Urbana, Illinois Doctoral Committee: Professor Benita S. Katzenellenbogen (Chair) Professor David J. Shapiro Professor Milan K. Bagchi Professor Paul J. Hergenrother THESIS ABSTRACT Breast cancer is one of the most highly diagnosed cancers in women and the second largest cause of death of women in United States. The anti-estrogen tamoxifen which blocks gene expression through estradiol bound ERα, and hence the growth stimulatory effects of estradiol, has been widely used for decades for treating patients with ERα positive or hormone dependent breast cancer. Despite its obvious benefits, in as high as 40% of the patients receiving tamoxifen therapy there is an eventual relapse of the disease largely due to acquired resistance to the drug, underlying mechanism for which is rather poorly understood. Elucidating the molecular basis underlying “acquired tamoxifen resistance” and agonistic effects of tamoxifen on cellular growth was the primary focus of my doctoral research. We addressed this by two approaches, one being studying the molecular mechanism for the regulation of cellular levels of ERα so as to prevent its loss in ERα positive or restore its levels in ERα negative breast cancers and second to investigate the role of tamoxifen in modulating the expression of ERα target genes independent of estradiol as a function of its stimulatory or estrogenic effects on breast cancer cell growth.
    [Show full text]
  • Olfactory Receptors in Non-Chemosensory Organs: the Nervous System in Health and Disease
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Sissa Digital Library REVIEW published: 05 July 2016 doi: 10.3389/fnagi.2016.00163 Olfactory Receptors in Non-Chemosensory Organs: The Nervous System in Health and Disease Isidro Ferrer 1,2,3*, Paula Garcia-Esparcia 1,2,3, Margarita Carmona 1,2,3, Eva Carro 2,4, Eleonora Aronica 5, Gabor G. Kovacs 6, Alice Grison 7 and Stefano Gustincich 7 1 Institute of Neuropathology, Bellvitge University Hospital, Hospitalet de Llobregat, University of Barcelona, Barcelona, Spain, 2 Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain, 3 Bellvitge Biomedical Research Institute (IDIBELL), Hospitalet de Llobregat, Barcelona, Spain, 4 Neuroscience Group, Research Institute Hospital, Madrid, Spain, 5 Department of Neuropathology, Academic Medical Center, University of Amsterdam, Amsterdam, Netherlands, 6 Institute of Neurology, Medical University of Vienna, Vienna, Austria, 7 Scuola Internazionale Superiore di Studi Avanzati (SISSA), Area of Neuroscience, Trieste, Italy Olfactory receptors (ORs) and down-stream functional signaling molecules adenylyl cyclase 3 (AC3), olfactory G protein a subunit (Gaolf), OR transporters receptor transporter proteins 1 and 2 (RTP1 and RTP2), receptor expression enhancing protein 1 (REEP1), and UDP-glucuronosyltransferases (UGTs) are expressed in neurons of the human and murine central nervous system (CNS). In vitro studies have shown that these receptors react to external stimuli and therefore are equipped to be functional. However, ORs are not directly related to the detection of odors. Several molecules delivered from the blood, cerebrospinal fluid, neighboring local neurons and glial cells, distant cells through the extracellular space, and the cells’ own self-regulating internal homeostasis Edited by: Filippo Tempia, can be postulated as possible ligands.
    [Show full text]
  • Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
    Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase
    [Show full text]
  • Whole Exome Sequencing in Families at High Risk for Hodgkin Lymphoma: Identification of a Predisposing Mutation in the KDR Gene
    Hodgkin Lymphoma SUPPLEMENTARY APPENDIX Whole exome sequencing in families at high risk for Hodgkin lymphoma: identification of a predisposing mutation in the KDR gene Melissa Rotunno, 1 Mary L. McMaster, 1 Joseph Boland, 2 Sara Bass, 2 Xijun Zhang, 2 Laurie Burdett, 2 Belynda Hicks, 2 Sarangan Ravichandran, 3 Brian T. Luke, 3 Meredith Yeager, 2 Laura Fontaine, 4 Paula L. Hyland, 1 Alisa M. Goldstein, 1 NCI DCEG Cancer Sequencing Working Group, NCI DCEG Cancer Genomics Research Laboratory, Stephen J. Chanock, 5 Neil E. Caporaso, 1 Margaret A. Tucker, 6 and Lynn R. Goldin 1 1Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 2Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 3Ad - vanced Biomedical Computing Center, Leidos Biomedical Research Inc.; Frederick National Laboratory for Cancer Research, Frederick, MD; 4Westat, Inc., Rockville MD; 5Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; and 6Human Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA ©2016 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol.2015.135475 Received: August 19, 2015. Accepted: January 7, 2016. Pre-published: June 13, 2016. Correspondence: [email protected] Supplemental Author Information: NCI DCEG Cancer Sequencing Working Group: Mark H. Greene, Allan Hildesheim, Nan Hu, Maria Theresa Landi, Jennifer Loud, Phuong Mai, Lisa Mirabello, Lindsay Morton, Dilys Parry, Anand Pathak, Douglas R. Stewart, Philip R. Taylor, Geoffrey S. Tobias, Xiaohong R. Yang, Guoqin Yu NCI DCEG Cancer Genomics Research Laboratory: Salma Chowdhury, Michael Cullen, Casey Dagnall, Herbert Higson, Amy A.
    [Show full text]
  • Identification of Candidate Biomarkers and Pathways Associated with Type 1 Diabetes Mellitus Using Bioinformatics Analysis
    bioRxiv preprint doi: https://doi.org/10.1101/2021.06.08.447531; this version posted June 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Identification of candidate biomarkers and pathways associated with type 1 diabetes mellitus using bioinformatics analysis Basavaraj Vastrad1, Chanabasayya Vastrad*2 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karnataka, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2021.06.08.447531; this version posted June 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Abstract Type 1 diabetes mellitus (T1DM) is a metabolic disorder for which the underlying molecular mechanisms remain largely unclear. This investigation aimed to elucidate essential candidate genes and pathways in T1DM by integrated bioinformatics analysis. In this study, differentially expressed genes (DEGs) were analyzed using DESeq2 of R package from GSE162689 of the Gene Expression Omnibus (GEO). Gene ontology (GO) enrichment analysis, REACTOME pathway enrichment analysis, and construction and analysis of protein-protein interaction (PPI) network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network, and validation of hub genes were then performed. A total of 952 DEGs (477 up regulated and 475 down regulated genes) were identified in T1DM. GO and REACTOME enrichment result results showed that DEGs mainly enriched in multicellular organism development, detection of stimulus, diseases of signal transduction by growth factor receptors and second messengers, and olfactory signaling pathway.
    [Show full text]