DOCSLIB.ORG

PATHWAY TOOLS Ii Pathway Tools User’S Guide, Version 13.0

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
PATHWAY TOOLS Ii Pathway Tools User’S Guide, Version 13.0 VERSION 13.0 User’s Guide PATHWAY TOOLS ii Pathway Tools User’s Guide, Version 13.0 Copyright c 1996, 1999-2009 SRI International, 1997-1999 DoubleTwist, Inc. All rights reserved. Printed in the U.S.A. We gratefully acknowledge contributions to Pathway Tools, used by permission, from: Jeremy Zucker, Harvard Medical School The Laboratory of Christos Ouzounis, European Bioinformatics Institute DoubleTwist is a registered trademark of DoubleTwist, Inc. Medline is a registered trademark of the National Library of Medicine. Oracle is a registered trademark of Oracle Corporation. MySQL R is a registered trademark of MySQL AB in the United States, the European Union and other countries. The Generic Frame Protocol is Copyright c 1996, The Board of Trustees of the Leland Stanford Junior University and SRI International. All Rights Reserved. The Pathway Tools Software is Copyright c 1997-1999 DoubleTwist, Inc., SRI Interna- tional 1996, 1999-2007. All Rights Reserved. The EcoCyc Database is Copyright c SRI International 1996, 1999-2009, Marine Biologi- cal Laboratory 1996-2001, DoubleTwist Inc. 1997-1999. All Rights Reserved. The MetaCyc Database is Copyright c SRI International 1999-2009, Marine Biological Laboratory 1998-2001, DoubleTwist Inc. 1998, 1999. All Rights Reserved. Allegro Common Lisp is Copyright c 1985-2009, Franz Inc. All Rights Reserved. All other trademarks are property of their respective owners. Any rights not expressly granted herein are reserved. This product may include data from BIND (http://blueprint.org/bind/bind. php) to which the following two notices apply: (1) Bader GD, Betel D, Hogue CW. (2003) BIND: the Biomolecular Interaction Network Database. Nucleic Acids Res. 31(1):248-50 PMID: 12519993 (2) This data is distributed in the hope that it will be useful, but WITHOUT ANY WAR- RANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. The dictionary used by the Pathway Tools spell checker was provided courtesy of www.biology-online.org. SRI International 333 Ravenswood Ave. Menlo Park, CA 94025 U.S.A. [email protected] iii iv Contents Contents v Preface xvii 1 Introduction to the Pathway Tools Software 1 1.1 Databases and Tools . 1 1.1.1 Databases . 2 1.1.2 Pathway Tools . 3 2 Invoking Pathway Tools 5 2.1 Pathway Tools Init File . 6 2.1.1 Parameters for Running in Web Server Mode . 6 2.1.2 Additional Parameters for Running in Web Server Mode . 6 2.1.3 Parameters Used when Accessing PGDBs within a MySQL or Ora- cle Server . 8 2.1.4 Parameters Associated with User Accounts Defined for a Pathway Tools Web Server . 8 2.2 X-Windows Basics . 9 2.3 Running Pathway Tools from the Command Line . 9 2.3.1 Command Line Arguments . 11 3 Pathway/Genome Navigator 17 3.1 Using the Mouse To Navigate and Issue Commands . 17 3.2 Menus and Dialogs . 18 v 3.2.1 Menu Bar . 18 3.2.2 Single-Choice Menus . 18 3.2.3 Multiple-Choice Menus . 18 3.2.4 Dialogs . 18 3.2.5 Aborting Out of Menus and Dialogs . 19 3.3 Organism Summary Display . 19 3.4 Single Organism Display . 20 3.5 Notion of Current Organism . 21 3.6 Examples . 22 3.7 Query Facilities . 23 3.7.1 Direct Queries . 24 3.7.2 Indirect Queries: Navigation . 25 3.7.3 History List . 26 3.7.4 Programmatic Queries . 26 3.8 Object Displays and Queries . 27 3.8.1 Shared Display Characteristics . 28 3.8.2 Systems Level Overviews . 31 3.8.3 Pathways . 54 3.8.4 Reactions . 58 3.8.5 Proteins . 59 3.8.6 RNAs . 62 3.8.7 Genes . 62 3.8.8 Compounds . 64 3.8.9 Transcription Units . 65 3.8.10 Genome Browser . 66 3.8.11 Displaying External Tracks on the Genome Browser . 69 3.8.12 Comparative Genome Browser . 72 3.9 Advanced Queries using the BioVelo querying language . 73 vi 3.10 Miscellaneous Commands and Tools . 73 3.10.1 Home . 73 3.10.2 Back . 73 3.10.3 Forward . 73 3.10.4 History . 74 3.10.5 Next Answer . 74 3.10.6 Clone . 74 3.10.7 Print . 74 3.10.8 Tools Menu . 75 3.10.9 Help . 80 3.10.10 Exiting Pathway Tools . 80 3.10.11 User Preferences . 80 3.10.12 Keyboard Shortcuts . 84 3.10.13 Tips . 85 3.11 Comparative Operations . 86 3.11.1 Global Comparative Analyses . 86 3.11.2 Sequential Comparison . 89 3.11.3 Parallel Comparison . 91 4 The Import/Export Facility 97 4.1 Pathway Import/Export . 98 4.2 SBML Export . 99 4.3 Genbank Format Export . 99 4.4 Linking Table Export . 100 4.5 Full Flat File Dump . 100 4.6 Frame Import/Export . 100 4.6.1 Frame Export . 101 4.6.2 Frame Import . 103 4.6.3 Supported file formats for frame import and export: . 106 vii 4.7 Importing citations from PubMed . 107 5 Database Sharing Via the PGDB Registry 109 5.1 Downloading PGDBs from the Registry . 110 5.2 Publishing PGDBs in the Registry . 110 5.2.1 Details of what happens during each step: . 111 5.2.2 Preliminary Step: Setting Preferences . 112 5.2.3 Registering a PGDB . 114 5.2.4 About Click-Through Licenses . 116 6 PathoLogic: Automated Creation of Pathway/Genome Databases 117 6.1 Overview of PathoLogic Execution . 118 6.1.1 Database Generation Perspective . 118 6.1.2 PathoLogic Operation . 119 6.2 PathoLogic Input File Formats . 120 6.2.1 File genetic-elements.dat . 120 6.2.2 The PathoLogic File Format . 121 6.2.3 GenBank File Format . 124 6.2.4 Specifying Gene Ontology Terms . 127 6.2.5 Directory Structure for a PGDB . 128 6.3 Creating a Pathway/Genome Database . 129 6.3.1 Invoke PathoLogic . 129 6.3.2 Create New Organism . 130 6.3.3 Create genetic-elements.dat File . 132 6.3.4 Specify Reference PGDB . 132 6.3.5 Trial Parse . 134 6.3.6 Build Pathway/Genome Database . 136 6.3.7 Metabolic Pathway Prediction . 137 6.3.8 Update Build for New Annotation . 143 viii 6.3.9 Adding or Replacing a Sequence File . 145 6.3.10 PGDB Housekeeping Tasks . 145 6.4 Refining the PGDB . 148 6.4.1 Refine: Assign Probable Enzymes . 148 6.4.2 Refine: Rerun Name Matcher . 152 6.4.3 Refine: Rescore Pathways . 152 6.4.4 Refine: Create Protein Complexes . ..
Load more

Recommended publications
  • Genome Informatics 4–8 September 2002, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
    Comparative and Functional Genomics Comp Funct Genom 2003; 4: 509–514. Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/cfg.300 Feature Meeting Highlights: Genome Informatics 4–8 September 2002, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK Jo Wixon1* and Jennifer Ashurst2 1MRC UK HGMP-RC, Hinxton, Cambridge CB10 1SB, UK 2The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK *Correspondence to: Abstract Jo Wixon, MRC UK HGMP-RC, Hinxton, Cambridge CB10 We bring you the highlights of the second Joint Cold Spring Harbor Laboratory 1SB, UK. and Wellcome Trust ‘Genome Informatics’ Conference, organized by Ewan Birney, E-mail: [email protected] Suzanna Lewis and Lincoln Stein. There were sessions on in silico data discovery, comparative genomics, annotation pipelines, functional genomics and integrative biology. The conference included a keynote address by Sydney Brenner, who was awarded the 2002 Nobel Prize in Physiology or Medicine (jointly with John Sulston and H. Robert Horvitz) a month later. Copyright 2003 John Wiley & Sons, Ltd. In silico data discovery background set was genes which had a log ratio of ∼0 in liver. Their approach found 17 of 17 known In the first of two sessions on this topic, Naoya promoters with a specificity of 17/28. None of the Hata (Cold Spring Harbor Laboratory, USA) sites they identified was located downstream of a spoke about motif searching for tissue specific TSS and all showed an excess in the foreground promoters. The first step in the process is to sample compared to the background sample.
    [Show full text]
  • The Capacity of Long-Term in Vitro Proliferation of Acute Myeloid
    The Capacity of Long-Term in Vitro Proliferation of Acute Myeloid Leukemia Cells Supported Only by Exogenous Cytokines Is Associated with a Patient Subset with Adverse Outcome Annette K. Brenner, Elise Aasebø, Maria Hernandez-Valladares, Frode Selheim, Frode Berven, Ida-Sofie Grønningsæter, Sushma Bartaula-Brevik and Øystein Bruserud Supplementary Material S2 of S31 Table S1. Detailed information about the 68 AML patients included in the study. # of blasts Viability Proliferation Cytokine Viable cells Change in ID Gender Age Etiology FAB Cytogenetics Mutations CD34 Colonies (109/L) (%) 48 h (cpm) secretion (106) 5 weeks phenotype 1 M 42 de novo 241 M2 normal Flt3 pos 31.0 3848 low 0.24 7 yes 2 M 82 MF 12.4 M2 t(9;22) wt pos 81.6 74,686 low 1.43 969 yes 3 F 49 CML/relapse 149 M2 complex n.d. pos 26.2 3472 low 0.08 n.d. no 4 M 33 de novo 62.0 M2 normal wt pos 67.5 6206 low 0.08 6.5 no 5 M 71 relapse 91.0 M4 normal NPM1 pos 63.5 21,331 low 0.17 n.d. yes 6 M 83 de novo 109 M1 n.d. wt pos 19.1 8764 low 1.65 693 no 7 F 77 MDS 26.4 M1 normal wt pos 89.4 53,799 high 3.43 2746 no 8 M 46 de novo 26.9 M1 normal NPM1 n.d. n.d. 3472 low 1.56 n.d. no 9 M 68 MF 50.8 M4 normal D835 pos 69.4 1640 low 0.08 n.d.
    [Show full text]
  • Hypertrophic Cardiomyopathy- Associated Mutations in Genes That Encode Calcium-Handling Proteins
    Current Molecular Medicine 2012, 12, 507-518 507 Beyond the Cardiac Myofilament: Hypertrophic Cardiomyopathy- Associated Mutations in Genes that Encode Calcium-Handling Proteins A.P. Landstrom and M.J. Ackerman* Departments of Medicine, Pediatrics, and Molecular Pharmacology & Experimental Therapeutics, Divisions of Cardiovascular Diseases and Pediatric Cardiology, and the Windland Smith Rice Sudden Death Genomics Laboratory, Mayo Clinic, Rochester, Minnesota, USA Abstract: Traditionally regarded as a genetic disease of the cardiac sarcomere, hypertrophic cardiomyopathy (HCM) is the most common inherited cardiovascular disease and a significant cause of sudden cardiac death. While the most common etiologies of this phenotypically diverse disease lie in a handful of genes encoding critical contractile myofilament proteins, approximately 50% of patients diagnosed with HCM worldwide do not host sarcomeric gene mutations. Recently, mutations in genes encoding calcium-sensitive and calcium- handling proteins have been implicated in the pathogenesis of HCM. Among these are mutations in TNNC1- encoded cardiac troponin C, PLN-encoded phospholamban, and JPH2-encoded junctophilin 2 which have each been associated with HCM in multiple studies. In addition, mutations in RYR2-encoded ryanodine receptor 2, CASQ2-encoded calsequestrin 2, CALR3-encoded calreticulin 3, and SRI-encoded sorcin have been associated with HCM, although more studies are required to validate initial findings. While a relatively uncommon cause of HCM, mutations in genes that encode calcium-handling proteins represent an emerging genetic subset of HCM. Furthermore, these naturally occurring disease-associated mutations have provided useful molecular tools for uncovering novel mechanisms of disease pathogenesis, increasing our understanding of basic cardiac physiology, and dissecting important structure-function relationships within these proteins.
    [Show full text]
  • In This Table Protein Name, Uniprot Code, Gene Name P-Value
    Supplementary Table S1: In this table protein name, uniprot code, gene name p-value and Fold change (FC) for each comparison are shown, for 299 of the 301 significantly regulated proteins found in both comparisons (p-value<0.01, fold change (FC) >+/-0.37) ALS versus control and FTLD-U versus control. Two uncharacterized proteins have been excluded from this list Protein name Uniprot Gene name p value FC FTLD-U p value FC ALS FTLD-U ALS Cytochrome b-c1 complex P14927 UQCRB 1.534E-03 -1.591E+00 6.005E-04 -1.639E+00 subunit 7 NADH dehydrogenase O95182 NDUFA7 4.127E-04 -9.471E-01 3.467E-05 -1.643E+00 [ubiquinone] 1 alpha subcomplex subunit 7 NADH dehydrogenase O43678 NDUFA2 3.230E-04 -9.145E-01 2.113E-04 -1.450E+00 [ubiquinone] 1 alpha subcomplex subunit 2 NADH dehydrogenase O43920 NDUFS5 1.769E-04 -8.829E-01 3.235E-05 -1.007E+00 [ubiquinone] iron-sulfur protein 5 ARF GTPase-activating A0A0C4DGN6 GIT1 1.306E-03 -8.810E-01 1.115E-03 -7.228E-01 protein GIT1 Methylglutaconyl-CoA Q13825 AUH 6.097E-04 -7.666E-01 5.619E-06 -1.178E+00 hydratase, mitochondrial ADP/ATP translocase 1 P12235 SLC25A4 6.068E-03 -6.095E-01 3.595E-04 -1.011E+00 MIC J3QTA6 CHCHD6 1.090E-04 -5.913E-01 2.124E-03 -5.948E-01 MIC J3QTA6 CHCHD6 1.090E-04 -5.913E-01 2.124E-03 -5.948E-01 Protein kinase C and casein Q9BY11 PACSIN1 3.837E-03 -5.863E-01 3.680E-06 -1.824E+00 kinase substrate in neurons protein 1 Tubulin polymerization- O94811 TPPP 6.466E-03 -5.755E-01 6.943E-06 -1.169E+00 promoting protein MIC C9JRZ6 CHCHD3 2.912E-02 -6.187E-01 2.195E-03 -9.781E-01 Mitochondrial 2-
    [Show full text]
  • DOE Systems Biology Knowledgebase Implementation Plan
    DOE Systems Biology Knowledgebase Implementation Plan As part of the U.S. Department of Energy’s (DOE) Office of Science, the Office of Biological and Environmental Research (BER) supports fundamental research and technology development aimed at achieving predictive, systems-level understand- ing of complex biological and environmental systems to advance DOE missions in energy, climate, and environment. DOE Contact Susan Gregurick 301.903.7672, [email protected] Office of Biological and Environmental Research U.S. Department of Energy Office of Science www.science.doe.gov/Program_Offices/BER.htm Acknowledgements The DOE Office of Biological and Environmental Research appreciates the vision and leadership exhibited by Bob Cottingham and Brian Davison (both from Oak Ridge National Laboratory) over the past year to conceptualize and guide the effort to create the DOE Systems Biology Knowledgebase Implementation Plan. Furthermore, we are grateful for the valuable contributions from about 300 members of the scientific community to organize, participate in, and provide the intellectual output of 5 work- shops, which culminated with the implementation plan. The plan was rendered into its current form by the efforts of the Biological and Environmental Research Information System (Oak Ridge National Laboratory). The report is available via • www.genomicscience.energy.gov/compbio/ • www.science.doe.gov/ober/BER_workshops.html • www.systemsbiologyknowledgebase.org Suggested citation for entire report: U.S. DOE. 2010. DOE Systems Biology Knowledgebase Implementation Plan. U.S. Department of Energy Office of Science (www.genomicscience.energy.gov/compbio/). DOE Systems Biology Knowledgebase Implementation Plan September 30, 2010 Office of Biological and Environmental Research The document is available via genomicscience.energy.gov/compbio/.
    [Show full text]
  • Anti-SRI / Sorcin Antibody (ARG42959)
    Product datasheet [email protected] ARG42959 Package: 50 μg anti-SRI / Sorcin antibody Store at: -20°C Summary Product Description Rabbit Polyclonal antibody recognizes SRI / Sorcin Tested Reactivity Hu, Ms, Rat Tested Application FACS, IHC-P, WB Host Rabbit Clonality Polyclonal Isotype IgG Target Name SRI / Sorcin Antigen Species Human Immunogen Synthetic peptide corresponding to a sequence of Human SRI / Sorcin. (TVDPQELQKALTTMGFRLSPQAVNSIAKRY) Conjugation Un-conjugated Alternate Names SCN; 22 kDa protein; V19; CP-22; Sorcin; CP22 Application Instructions Application table Application Dilution FACS 1:150 - 1:500 IHC-P 1:200 - 1:1000 WB 1:500 - 1:2000 Application Note IHC-P: Antigen Retrieval: Heat mediation was performed in Citrate buffer (pH 6.0) for 20 min. * The dilutions indicate recommended starting dilutions and the optimal dilutions or concentrations should be determined by the scientist. Calculated Mw 22 kDa Observed Size ~ 22 kDa Properties Form Liquid Purification Affinity purification with immunogen. Buffer 0.2% Na2HPO4, 0.9% NaCl, 0.05% Sodium azide and 4% Trehalose. Preservative 0.05% Sodium azide Stabilizer 4% Trehalose Concentration 0.5 - 1 mg/ml www.arigobio.com 1/3 Storage instruction For continuous use, store undiluted antibody at 2-8°C for up to a week. For long-term storage, aliquot and store at -20°C or below. Storage in frost free freezers is not recommended. Avoid repeated freeze/thaw cycles. Suggest spin the vial prior to opening. The antibody solution should be gently mixed before use. Note For laboratory research only, not for drug, diagnostic or other use. Bioinformation Gene Symbol SRI Gene Full Name sorcin Background This gene encodes a calcium-binding protein with multiple E-F hand domains that relocates from the cytoplasm to the sarcoplasmic reticulum in response to elevated calcium levels.
    [Show full text]
  • Genetic Determinants of Sporadic Breast Cancer in Sri Lankan Women Nirmala Dushyanthi Sirisena1*, Adebowale Adeyemo2, Anchala I
    Sirisena et al. BMC Cancer (2018) 18:180 https://doi.org/10.1186/s12885-018-4112-4 RESEARCH ARTICLE Open Access Genetic determinants of sporadic breast cancer in Sri Lankan women Nirmala Dushyanthi Sirisena1*, Adebowale Adeyemo2, Anchala I. Kuruppu1, Nilaksha Neththikumara1, Nilakshi Samaranayake3 and Vajira H. W. Dissanayake1 Abstract Background: While a range of common genetic variants have been identified to be associated with risk of sporadic breast cancer in several Western studies, little is known about their role in South Asian populations. Our objective was to examine the association between common genetic variants in breast cancer related genes and risk of breast cancer in a cohort of Sri Lankan women. Methods: A case-control study of 350 postmenopausal women with breast cancer and 350 healthy postmenopausal women was conducted. Genotyping using the iPLEX GOLD assay was done for 56 haplotype-tagging single nucleotide polymorphisms (SNPs) in 36 breast cancer related genes. Testing for association was done using an additive genetic model. Odds ratios and 95% confidence intervals were calculated using adjusted logistic regression models. Results: Four SNPs [rs3218550 (XRCC2), rs6917 (PHB), rs1801516 (ATM),andrs13689(CDH1)] were significantly associated with risk of breast cancer. The rs3218550 T allele and rs6917 A allele increased breast cancer risk by 1.5-fold and 1.4-fold, respectively. The CTC haplotype defined by the SNPs rs3218552|rs3218550|rs3218536 on chromosome 7 (P = 0.0088) and the CA haplotype defined by the SNPs rs1049620|rs6917 on chromosome 17 (P = 0.0067) were significantly associated with increased risk of breast cancer. The rs1801516 A allele and the rs13689 C allele decreased breast cancer risk by 0.6-fold and 0.7-fold, respectively.
    [Show full text]
  • Annexins: Putative Linkers in Dynamic Membrane–Cytoskeleton
    Protoplasma (2007) 230: 203–215 DOI 10.1007/s00709-006-0234-7 PROTOPLASMA Printed in Austria Annexins: putative linkers in dynamic membrane–cytoskeleton interactions in plant cells D. Konopka-Postupolska Laboratory of Plant Pathogenesis, Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Warsaw Received January 10, 2006; accepted March 14, 2006; published online April 24, 2007 © Springer-Verlag 2007 Summary. The plasma membrane, the most external cellular structure, proteins with similar characteristics in plant cells (Boustead is at the forefront between the plant cell and its environment. Hence, it is et al. 1989, Blackbourn et al. 1991). In vertebrates the annex- naturally adapted to function in detection of external signals, their trans- duction throughout the cell, and finally, in cell reactions. Membrane ins were grouped into 13 families. In contrast, plant annexins lipids and the cytoskeleton, once regarded as simple and static structures, seem to represent a relatively simpler, smaller, and less have recently been recognized as significant players in signal transduc- diverse family of proteins. Nevertheless, in all analysed tion. Proteins involved in signal detection and transduction are organised in specific domains at the plasma membrane. Their aggregation allows to plant species, at least two distinct proteins with molecular bring together and orient the downstream and upstream members of sig- masses between 33 and 36 kDa have been discovered nalling pathways. The cortical cytoskeleton provides a structural frame- (Smallwood et al. 1990, Shin et al. 1995, Proust et al. 1996, work for rapid signal transduction from the cell periphery into the Thonat et al. 1997). However, a search through the nucleus.
    [Show full text]
  • The Biocyc Collection of Microbial Genomes and Metabolic Pathways Peter D
    Briefings in Bioinformatics, 2017, 1–9 doi: 10.1093/bib/bbx085 Paper Downloaded from https://academic.oup.com/bib/advance-article-abstract/doi/10.1093/bib/bbx085/4084231 by guest on 02 May 2019 The BioCyc collection of microbial genomes and metabolic pathways Peter D. Karp, Richard Billington, Ron Caspi, Carol A. Fulcher, Mario Latendresse, Anamika Kothari, Ingrid M. Keseler, Markus Krummenacker, Peter E. Midford, Quang Ong, Wai Kit Ong, Suzanne M. Paley and Pallavi Subhraveti Corresponding author: Peter D. Karp, Bioinformatics Research Group, SRI International, 333 Ravenswood Ave, AE206, Menlo Park, CA 94025, USA. E-mail: [email protected] Abstract BioCyc.org is a microbial genome Web portal that combines thousands of genomes with additional information inferred by computer programs, imported from other databases and curated from the biomedical literature by biologist curators. BioCyc also provides an extensive range of query tools, visualization services and analysis software. Recent advances in BioCyc in- clude an expansion in the content of BioCyc in terms of both the number of genomes and the types of information available for each genome; an expansion in the amount of curated content within BioCyc; and new developments in the BioCyc soft- ware tools including redesigned gene/protein pages and metabolite pages; new search tools; a new sequence-alignment tool; a new tool for visualizing groups of related metabolic pathways; and a facility called SmartTables, which enables biolo- gists to perform analyses that previously would have required a programmer’s assistance. Key words: genome databases; microbial genome databases; metabolic pathway databases Peter Karp is the Director of the SRI Bioinformatics Research Group (BRG).
    [Show full text]
  • Refined Mapping of the Human Serotonin Transporter (SLC6A4) Gene Within 17Q11 Adjacent to the CPD and NF1 Genes
    European Journal of Human Genetics (2000) 8, 75–78 © 2000 Macmillan Publishers Ltd All rights reserved 1018–4813/00 $15.00 y www.nature.com/ejhg SHORT REPORT Refined mapping of the human serotonin transporter (SLC6A4) gene within 17q11 adjacent to the CPD and NF1 genes Sanbing Shen1, Sharon Battersby1, Molly Weaver2, Elma Clark1, Karen Stephens2,3 and Anthony J Harmar1 1MRC Brain Metabolism Unit, University Department of Neuroscience, Edinburgh, Scotland; Departments of 2Medicine and 3Laboratory Medicine, University of Washington, Seattle, WA 98195, USA The SLC6A4 gene encodes the serotonin transporter, the target of an important class of antidepressant drugs (serotonin selective reuptake inhibitors). Polymorphisms in the SLC6A4 gene have been reported to be associated with susceptibility to depression and other psychiatric disorders. We have constructed a 1 Mb YAC and PAC contig which harbours both the SLC6A4 and the carboxypeptidase D (CPD) genes. The order of loci within the contig was cen–D17S975–D17S1549–24R–D17S1294–SLC6A4–28L–(CPD, D17S2009, D17S2004)–D17S2120–ter. Both genes were deleted in one of 17 neurofibromatosis type 1 (NF1) patients carrying submicroscopic NF1 contiguous gene deletions. European Journal of Human Genetics (2000) 8, 75–78. Keywords: serotonin transporter; CPD; NF1; YAC contig Introduction and YAC libraries from ICRF (35D8, 132C6 and 49A9) and The actions of the neurotransmitter serotonin (5-HT) are CEPH (704F1, 782E2 and 765D1). Yeast DNA was prepared by terminated by reuptake via a Na+ -dependent serotonin combined methods of Schedl et al2 and Bellis et al.3 Pulsed- transporter (SERT) encoded by the SLC6A4 gene. The SERT is field gel electrophoresis was performed in 0.5 ϫ TBE buffer at the target for an important class of antidepressant drugs (the 6 V/cm for 24 h at 14°C with 60 s switch time and gels were serotonin selective reuptake inhibitors) and also of certain blotted overnight onto Appligene Positive Membrane.
    [Show full text]
  • S41564-021-00949-1.Pdf
    ARTICLES https://doi.org/10.1038/s41564-021-00949-1 CcrZ is a pneumococcal spatiotemporal cell cycle regulator that interacts with FtsZ and controls DNA replication by modulating the activity of DnaA Clement Gallay 1,5, Stefano Sanselicio1,5, Mary E. Anderson2, Young Min Soh1, Xue Liu1, Gro A. Stamsås3, Simone Pelliciari 4, Renske van Raaphorst1, Julien Dénéréaz 1, Morten Kjos 3, Heath Murray 4, Stephan Gruber 1, Alan D. Grossman 2 and Jan-Willem Veening 1 ✉ Most bacteria replicate and segregate their DNA concomitantly while growing, before cell division takes place. How bacteria synchronize these different cell cycle events to ensure faithful chromosome inheritance by daughter cells is poorly understood. Here, we identify Cell Cycle Regulator protein interacting with FtsZ (CcrZ) as a conserved and essential protein in pneumococci and related Firmicutes such as Bacillus subtilis and Staphylococcus aureus. CcrZ couples cell division with DNA replication by controlling the activity of the master initiator of DNA replication, DnaA. The absence of CcrZ causes mis-timed and reduced initiation of DNA replication, which subsequently results in aberrant cell division. We show that CcrZ from Streptococcus pneu- moniae interacts directly with the cytoskeleton protein FtsZ, which places CcrZ in the middle of the newborn cell where the DnaA-bound origin is positioned. This work uncovers a mechanism for control of the bacterial cell cycle in which CcrZ controls DnaA activity to ensure that the chromosome is replicated at the right time during the cell cycle. n many bacterial species, DNA replication and cell division MapZ was shown to guide Z-ring formation, analogous to the Min occur concomitantly1–3.
    [Show full text]
  • The Sri Lankan Personal Genome Project: an Overview
    Leading Article The Sri Lankan Personal Genome Project: an overview Prof. Vajira H. W. Dissanayake MBBS, PhD Professor, Department of Anatomy; Medical Geneticist, Human Genetics Unit, Faculty of Medicine, University of Colombo, Sri Lanka E-Mail address: [email protected] Pubudu S. Samarakoon BSc, MSc Tutor, Biomedical Informatics Course, Postgraduate Institute of Medicine, University of Colombo, Sri Lanka. Current address: Research Fellow, Department of Medical Genetics, University of Oslo, Norway. E-Mail address: [email protected] Dr. Vinod Scaria MBBS Scientist, CSIR Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India E-Mail address: [email protected] Ashok Patowary BSc, MSc Scientist, CSIR Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India E-Mail address: [email protected] Dr. Sridhar Sivasubbu PhD Scientist, CSIR Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India E-Mail address: [email protected] Dr. Rajesh S. Gokhale PhD Director, CSIR Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India E-mail address: [email protected] Sri Lanka Journal of Bio-Medical Informatics 2011;2(1):4-8 DOI: http://dx.doi.org/10.4038/sljbmi.v2i1.3711 Abstract The first Sri Lankan Personal Genome was sequenced heralding the entry of Sri Lanka into the new era of whole genome sequencing. This paper explains the background and the rationale for the project, gives a brief overview of what was found in the Sri Lankan Personal Genome, and discusses the future directions of the project. Keywords - Sri Lankan Personal Genome Project; Sri Lanka; Genome; Sinhalese; Whole Genome Sequencing Background With the completion of the Human Genome Project (HGP)(1,2) and a decade of human genomics, we are at an interesting juncture in the history of mankind.
    [Show full text]