Supplmaterialsall200821.Pdf

Total Page:16

File Type:pdf, Size:1020Kb

Supplmaterialsall200821.Pdf Supplementary materials, information Supplementary Table S1. List of GO terms used for the networks COVID-19, chloroquine and arrhythmia markers. Supplementary Table S2. List of the nodes of intersection of COVID-19 and chloroquine (264 nodes) and ACE2/TMPRSS2 and chloroquine (2 nodes). Supplementary Figure S1. Network generated with the targets of chloroquine (A) and biological processes represented by that network (B). The network was built with Cytoscape and UniProt database. Biological processes were retrieved with BiNGO tool. Supplementary Figure S2. Network generated with the targets of COVID-19 (A) and biological processes represented by that network (B). The network was built with Cytoscape and UniProt database. Biological processes were retrieved with BiNGO tool. Supplementary Figure S3. Network generated with the targets of ACE2 and TMPRSS2 (A) and biological processes represented by that network (B). The network was built with Cytoscape and UniProt database. Biological processes were retrieved with BiNGO tool. Supplementary Figure S4. Network generated with the targets of arrhytmia (A) and biological processes represented by that network (B). The network was built with Cytoscape and UniProt database. Biological processes were retrieved with BiNGO tool. Supplementary File S1. Cytoscape Session file (.cys) contains networks used in this study. These networks can be evaluated for nodes and edges of interest, e.g. to see identifiers. See the text for annotation of the networks. The file is uploaded at FigShare for free access; link is https://figshare.com/articles/online_resource/SupplementaryFileS1_Cytoscape_DataNetwork_cy s/12793580 . Supplementary Figure S1 B A 1336 nodes, 2526 edges 1224 biological processes Supplementary Figure S2 A B 828 nodes, 1545 edges 721 biological processes Supplementary Figure S3 A B 231 biological processes 15 nodes, 19 edges Supplementary Figure S4 B A 63 nodes, 80 edges 641 biological processes Supplementary Table S1. Lists of nodes used in this study for building networks. A) Targets of chloroquine GSTA2, TNF, TLR9, GST, HMGB1, GSTM1, CYP2C8, CYP3A4, CYP3A5, CYP2D6, CYP1A1 B) COVID-19 interacting proteins AP3B1, BRD4, BRD2, CWC27, ZC3H18, SLC44A2, PMPCB, YIF1A, ATP1B1, ACADM, ETFA, STOM, GGCX, ATP6V1A, PSMD8, REEP5, PMPCA, ANO6, PITRM1, SLC30A9, FASTKD5, SLC30A7, TUBGCP3, COQ8B, SAAL1, REEP6 , INTS4, SLC25A21, TUBGCP2, TARS2, RTN4, FAM8A1, AASS, AKAP8L, AAR2, BZW2, RRP9, PABPC1, CSNK2A2, CSNK2B, G3BP1, PABPC4, LARP1, FAM98A, SNIP1, UPF1, MOV10, G3BP2, DDX21, RBM28, RPL36, GOLGA7, ZDHHC5, POLA1, PRIM1, PRIM2, POLA2, COLGALT1, PKP2, AP2A2, GFER, ERGIC1, AP2M1, GRPEL1, TBCA, SBNO1, BCKDK, AKAP8, MYCBP2, SLU7, RIPK1, UBAP2L, TYSND1, PDZD11, PRRC2B, UBAP2, ZNF318, CRTC3, USP54, ZC3H7A, LARP4B, RBM41, TCF12, PPIL3, PLEKHA5, TBKBP1, CIT, HSBP1, PCNT, CEP43, PRKAR2A, PRKACA, PRKAR2B, RDX, CENPF, TLE1, TLE3, TLE5, GOLGA3, GOLGA2, GOLGB1, GRIPAP1, CEP350, PDE4DIP, CEP135, CEP68, CNTRL, ERC1, GCC2, CLIP4, NIN, CEP112, MIPOL1, USP13, GCC1, JAKMIP1, CDK5RAP2, AKAP9, GORASP1, FYCO1, C1orf50, CEP250, TBK1, HOOK1, NINL, GLA, IMPDH2, SIRT5, NUTF2, ARF6, RNF41, SLC27A2, EIF4E2, POR, RAP1GDS1, WASHC4, FKBP15, GIGYF2, IDE, TIMM10, ALG11, NUP210, TIMM29, DNAJC11, TIMM10B, TIMM9, HDAC2, GPX1, TRMT1, ATP5MG, ATP6AP1, SIGMAR1, ATP13A3, AGPS, CYB5B, ACSL3, CYB5R3, RALA, COMT, RAB5C, RAB7A, RAB8A, RAB2A, RAB10, RAB14, RHOA, RAB1A, GNB1, GNG5, LMAN2, MOGS, TOR1AIP1, MTARC1, QSOX2, HS2ST1, NDUFAF2, SCCPDH, SCARB1, NAT14, DCAKD, FAM162A, DNAJC19, SELENOS, PTGES2, RAB18, MPHOSPH10, SRP72, ATE1, NSD2, SRP19, SRP54, MRPS25, DDX10, LARP7, MEPCE, NGDN, EXOSC8, NARS2, NOL10, CCDC86, SEPSECS, EXOSC5, EXOSC3, AATF, HECTD1, MRPS2, MRPS5, EXOSC2, MRPS27, GTF2F2, FBN1, FBN2, NUP214, NUP62, DCAF7, EIF4H, NUP54, MIB1, SPART, NEK9, ZNF503, NUP88, NUP58, MAT2B, FBLN5, PPT1, CUL2, MAP7D1, THTPA, ZYG11B, TIMM8B, RBX1, ELOC, ELOB, HMOX1, TRIM59, ARL6IP6, VPS39, CLCC1, VPS11, SUN2, ALG5, STOML2, NUP98, RAE1, MTCH1, HEATR3, MDN1, PLOD2, TOR1A, STC2, PLAT, ITGB1, CISD3, COL6A1, PVR, DNMT1, LOX, PCSK6, INHBE, NPC2, MFGE8, OS9, NPTX1, POGLUT2, POGLUT3, ERO1B, PLD3, FOXRED2, CHPF, PUSL1, EMC1, GGH, ERLEC1, IL17RA, NGLY1, HS6ST2, SDF2, NEU1, GDF15, TM2D3, ERP44, EDEM3, SIL1, POFUT1, SMOC1, PLEKHF2, FBXL12, UGGT2, CHPF2, ADAMTS1, HYOU1, FKBP7, ADAM9, FKBP10, SLC9A3R1, CHMP2A, CSDE1, TOMM70, MARK3, MARK2, DPH5, DCTPP1, MARK1, PTBP2, BAG5, UBXN8, GPAA1, WFS1, ABCC1, F2RL1, SCAP, DPY19L1, TMEM97, SLC30A6, TAPT1, ERMP1, NLRX1, RETREG3, PIGO, FAR2, ECSIT, ALG8, TMEM39B, GHITM, ACAD9, NDFIP2, BCS1L, NDUFAF1, TMED5, NDUFB9, PIGS C) Markers of arrhythmia OPN, ANXA5, GDF15, MPO, LGALS3, TNNT2, TNNI3, ANFB, REN, IL6, CRP Supplementary Table S2 Intersection nodes of Chloroquine and COVID‐19 networks. The listed are 266 nodes that are common for the networks formed by chloroquine and COVID‐19. The rows from 3 to 266 show the nodes of COVID‐19 network, and the last 2 rows annotate ACE2/TMPRSS2 common nodes, ALB and YWHAZ. Common nodes of Chloroquine and Covid19 networks Accession Name Human number Label P09429 High mobility group box 1 HMGB1 P12004 Proliferating cell nuclear antigen PCNA Q9Y3U8 Ribosomal protein L36 RPL36 Q9Y2W1 Thyroid hormone receptor associated protein 3 THRAP3 Q9NYF8 BCL2 associated transcription factor 1 BCLAF1 Q9H307 Pinin, desmosome associated protein PNN Q8NEJ9 Neuroguidin NGDN Q86VM9 Zinc finger CCCH‐type containing 18 ZC3H18 Q6PKG0 La ribonucleoprotein 1, translational regulator LARP1 Q15287 RNA binding protein with serine rich domain 1 RNPS1 Q13573 SNW domain containing 1 SNW1 Q09161 Nuclear cap binding protein subunit 1 NCBP1 P62913 Ribosomal protein L11 RPL11 P62753 Ribosomal protein S6 kinase B1 RPS6 P62424 Ribosomal protein L7A RPL7A P38919 Eukaryotic translation initiation factor 4A3 EIF4A3 P23396 Ribosomal protein S3 RPS3 P19338 Nucleolin NCL Q07021 Complement C1q binding protein C1QBP P42858 Huntingtin HTT P12682 High mobility group box 1 HMGB1 Q9QUN7 Toll like receptor 2 Tlr2 P63158 High mobility group box 1 Hmgb1 O00206 Toll like receptor 4 TLR4 Q9QUK6 Toll like receptor 4 Tlr4 Q8TDQ0 Hepatitis A virus cellular receptor 2 HAVCR2 P43405 Spleen associated tyrosine kinase SYK Q9NP31 SH2 domain containing 2A SH2D2A P60484 Phosphatase and tensin homolog PTEN CHEBI:16755 CHEBI:16755 P22366 MYD88 innate immune signal transduction adaptor Myd88 O60260 Parkin RBR E3 ubiquitin protein ligase PRKN Q7Z434 Mitochondrial antiviral signaling protein MAVS O95786 DExD/H‐box helicase 58 DDX58 1 Q9BYX4 Interferon induced with helicase C domain 1 IFIH1 O15111 Component of inhibitor of nuclear factor kappa B kinase CHUK complex O14920 Inhibitor of nuclear factor kappa B kinase subunit beta IKBKB P35637 FUS RNA binding protein FUS Q08211 DExH‐box helicase 9 DHX9 P10636‐8 Microtubule associated protein tau MAPT EBI‐14348029 EBI‐ 14348029 Q05127 Polymerase complex protein VP35 Q9HCE5 Methyltransferase like 14 METTL14 Q9R1S0 B9 domain containing 1 B9d1 P55085 F2R like trypsin receptor 1 F2RL1 Q9UBU9 Nuclear RNA export factor 1 NXF1 Q28141 DExH‐box helicase 9 DHX9 P61286 Poly(A) binding protein cytoplasmic 1 PABPC1 Q9QXM1 Junction mediating and regulatory protein, p53 cofactor JMY P07602 Prosaposin PSAP Q14164 Inhibitor of nuclear factor kappa B kinase subunit epsilon IKBKE P04487 Tegument protein US11 [Human alphaherpesvirus 1 US11 Q9H7S9 Zinc finger protein 703 ZNF703 F1BA49 B303_sSgp2 nonstructural protein [ SFTS virus HB29 ] F1BA49 O75569 Protein activator of interferon induced protein kinase PRKRA EIF2AK2 Q9UHD2 TANK binding kinase 1 TBK1 Q9NZ43 Unconventional SNARE in the ER 1 USE1 Q86U44 Methyltransferase like 3 METTL3 O00571 DEAD‐box helicase 3 X‐linked DDX3X O35658 Complement C1q binding protein C1qbp Q9NVI7 ATPase family AAA domain containing 3A ATAD3A Q5T9A4 ATPase family AAA domain containing 3B ATAD3B O14730 RIO kinase 3 RIOK3 O14672 ADAM metallopeptidase domain 10 ADAM10 P49768 Presenilin 1 PSEN1 P05067‐ Amyloid beta precursor protein APP PRO_0000000092 Q8N6Q3 CD177 CD177 P05067‐8 Amyloid beta precursor protein APP P49755 Transmembrane p24 trafficking protein 10 TMED10 Q8N766 ER membrane protein complex subunit 1 EMC1 Q04637 Eukaryotic translation initiation factor 4 gamma 1 EIF4G1 P54253 Ataxin 1 ATXN1 Q923E4 Sirtuin 1 Sirt1 P34902 Interleukin 2 receptor subunit gamma Il2rg 2 P07750 Interleukin 4 Il4 Q9NQC3 Reticulon 4 RTN4 Q16820 Meprin A subunit beta MEP1B O00213 Amyloid beta precursor protein binding family B member 1 APBB1 Q9Y6D5 ADP ribosylation factor guanine nucleotide exchange factor ARFGEF2 2 P19438 TNF receptor superfamily member 1A TNFRSF1A Q9ULZ3 PYD and CARD domain containing PYCARD Q13546 Receptor interacting serine/threonine kinase 1 RIPK1 P48729 Casein kinase 1 alpha 1 CSNK1A1 Q06A28 Ribonucleoside‐diphosphate reductase large subunit RIR1 Q60855 Receptor interacting serine/threonine kinase 1 Ripk1 Q9Y6K9 Inhibitor of nuclear factor kappa B kinase regulatory IKBKG subunit gamma O70343 PPARG coactivator 1 alpha Ppargc1a Q9UBK2 PPARG coactivator 1 alpha PPARGC1A Q9DBR0 A‐kinase anchoring protein 8 Akap8 P25799 Nuclear factor kappa B subunit 1 Nfkb1 O43823 A‐kinase anchoring protein 8 AKAP8 P42574 Caspase 3 CASP3 Q12933 TNF receptor associated factor 2 TRAF2 Q9UQ80 Proliferation‐associated 2G4 PA2G4 Q92769 Histone deacetylase 2 HDAC2 Q9Z2D8 Methyl‐CpG binding domain protein 3 Mbd3 Q6NYC1 Jumonji domain containing 6, arginine demethylase and JMJD6 lysine hydroxylase P04156 Prion protein PRNP Q06124 Protein tyrosine phosphatase non‐receptor type 11 PTPN11 Q01101 INSM transcriptional repressor 1 INSM1 O88895 Histone
Recommended publications
  • Astrin-SKAP Complex Reconstitution Reveals Its Kinetochore
    RESEARCH ARTICLE Astrin-SKAP complex reconstitution reveals its kinetochore interaction with microtubule-bound Ndc80 David M Kern1,2, Julie K Monda1,2†, Kuan-Chung Su1†, Elizabeth M Wilson-Kubalek3, Iain M Cheeseman1,2* 1Whitehead Institute for Biomedical Research, Cambridge, United States; 2Department of Biology, Massachusetts Institute of Technology, Cambridge, United States; 3Department of Cell Biology, The Scripps Research Institute, La Jolla, United States Abstract Chromosome segregation requires robust interactions between the macromolecular kinetochore structure and dynamic microtubule polymers. A key outstanding question is how kinetochore-microtubule attachments are modulated to ensure that bi-oriented attachments are selectively stabilized and maintained. The Astrin-SKAP complex localizes preferentially to properly bi-oriented sister kinetochores, representing the final outer kinetochore component recruited prior to anaphase onset. Here, we reconstitute the 4-subunit Astrin-SKAP complex, including a novel MYCBP subunit. Our work demonstrates that the Astrin-SKAP complex contains separable kinetochore localization and microtubule binding domains. In addition, through cross-linking analysis in human cells and biochemical reconstitution, we show that the Astrin-SKAP complex binds synergistically to microtubules with the Ndc80 complex to form an integrated interface. We propose a model in which the Astrin-SKAP complex acts together with the Ndc80 complex to stabilize correctly formed kinetochore-microtubule interactions. *For correspondence: DOI: https://doi.org/10.7554/eLife.26866.001 [email protected] †These authors contributed equally to this work Introduction Competing interests: The The macromolecular kinetochore complex links chromosomes to dynamic microtubule polymers and authors declare that no harnesses the forces generated by microtubule growth and depolymerization to facilitate accurate competing interests exist.
    [Show full text]
  • Gpr161 Anchoring of PKA Consolidates GPCR and Camp Signaling
    Gpr161 anchoring of PKA consolidates GPCR and cAMP signaling Verena A. Bachmanna,1, Johanna E. Mayrhofera,1, Ronit Ilouzb, Philipp Tschaiknerc, Philipp Raffeinera, Ruth Röcka, Mathieu Courcellesd,e, Federico Apeltf, Tsan-Wen Lub,g, George S. Baillieh, Pierre Thibaultd,i, Pia Aanstadc, Ulrich Stelzlf,j, Susan S. Taylorb,g,2, and Eduard Stefana,2 aInstitute of Biochemistry and Center for Molecular Biosciences, University of Innsbruck, 6020 Innsbruck, Austria; bDepartment of Chemistry and Biochemistry, University of California, San Diego, CA 92093; cInstitute of Molecular Biology, University of Innsbruck, 6020 Innsbruck, Austria; dInstitute for Research in Immunology and Cancer, Université de Montréal, Montreal, QC, Canada H3C 3J7; eDépartement de Biochimie, Université de Montréal, Montreal, QC, Canada H3C 3J7; fOtto-Warburg Laboratory, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany; gDepartment of Pharmacology, University of California, San Diego, CA 92093; hInstitute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, G12 8QQ, United Kingdom; iDepartment of Chemistry, Université de Montréal, Montreal, QC, Canada H3C 3J7; and jInstitute of Pharmaceutical Sciences, Pharmaceutical Chemistry, University of Graz, 8010 Graz, Austria Contributed by Susan S. Taylor, May 24, 2016 (sent for review February 18, 2016; reviewed by John J. G. Tesmer and Mark von Zastrow) Scaffolding proteins organize the information flow from activated G accounts for nanomolar binding affinities to PKA R subunit dimers protein-coupled receptors (GPCRs) to intracellular effector cascades (12, 13). Moreover, additional components of the cAMP signaling both spatially and temporally. By this means, signaling scaffolds, such machinery, such as GPCRs, adenylyl cyclases, and phosphodiester- as A-kinase anchoring proteins (AKAPs), compartmentalize kinase ases, physically interact with AKAPs (1, 5, 11, 14).
    [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]
  • Identification and Characterization of RHOA-Interacting Proteins in Bovine Spermatozoa1
    BIOLOGY OF REPRODUCTION 78, 184–192 (2008) Published online before print 10 October 2007. DOI 10.1095/biolreprod.107.062943 Identification and Characterization of RHOA-Interacting Proteins in Bovine Spermatozoa1 Sarah E. Fiedler, Malini Bajpai, and Daniel W. Carr2 Department of Medicine, Oregon Health & Sciences University and Veterans Affairs Medical Center, Portland, Oregon 97239 ABSTRACT Guanine nucleotide exchange factors (GEFs) catalyze the GDP for GTP exchange [2]. Activation is negatively regulated by In somatic cells, RHOA mediates actin dynamics through a both guanine nucleotide dissociation inhibitors (RHO GDIs) GNA13-mediated signaling cascade involving RHO kinase and GTPase-activating proteins (GAPs) [1, 2]. Endogenous (ROCK), LIM kinase (LIMK), and cofilin. RHOA can be RHO can be inactivated via C3 exoenzyme ADP-ribosylation, negatively regulated by protein kinase A (PRKA), and it and studies have demonstrated RHO involvement in actin-based interacts with members of the A-kinase anchoring (AKAP) cytoskeletal response to extracellular signals, including lyso- family via intermediary proteins. In spermatozoa, actin poly- merization precedes the acrosome reaction, which is necessary phosphatidic acid (LPA) [2–4]. LPA is known to signal through for normal fertility. The present study was undertaken to G-protein-coupled receptors (GPCRs) [4, 5]; specifically, LPA- determine whether the GNA13-mediated RHOA signaling activated GNA13 (formerly Ga13) promotes RHO activation pathway may be involved in acrosome reaction in bovine through GEFs [4, 6]. Activated RHO-GTP then signals RHO caudal sperm, and whether AKAPs may be involved in its kinase (ROCK), resulting in the phosphorylation and activation targeting and regulation. GNA13, RHOA, ROCK2, LIMK2, and of LIM-kinase (LIMK), which in turn phosphorylates and cofilin were all detected by Western blot in bovine caudal inactivates cofilin, an actin depolymerizer, the end result being sperm.
    [Show full text]
  • Supplemental Information Proximity Interactions Among Centrosome
    Current Biology, Volume 24 Supplemental Information Proximity Interactions among Centrosome Components Identify Regulators of Centriole Duplication Elif Nur Firat-Karalar, Navin Rauniyar, John R. Yates III, and Tim Stearns Figure S1 A Myc Streptavidin -tubulin Merge Myc Streptavidin -tubulin Merge BirA*-PLK4 BirA*-CEP63 BirA*- CEP192 BirA*- CEP152 - BirA*-CCDC67 BirA* CEP152 CPAP BirA*- B C Streptavidin PCM1 Merge Myc-BirA* -CEP63 PCM1 -tubulin Merge BirA*- CEP63 DMSO - BirA* CEP63 nocodazole BirA*- CCDC67 Figure S2 A GFP – + – + GFP-CEP152 + – + – Myc-CDK5RAP2 + + + + (225 kDa) Myc-CDK5RAP2 (216 kDa) GFP-CEP152 (27 kDa) GFP Input (5%) IP: GFP B GFP-CEP152 truncation proteins Inputs (5%) IP: GFP kDa 1-7481-10441-1290218-1654749-16541045-16541-7481-10441-1290218-1654749-16541045-1654 250- Myc-CDK5RAP2 150- 150- 100- 75- GFP-CEP152 Figure S3 A B CEP63 – – + – – + GFP CCDC14 KIAA0753 Centrosome + – – + – – GFP-CCDC14 CEP152 binding binding binding targeting – + – – + – GFP-KIAA0753 GFP-KIAA0753 (140 kDa) 1-496 N M C 150- 100- GFP-CCDC14 (115 kDa) 1-424 N M – 136-496 M C – 50- CEP63 (63 kDa) 1-135 N – 37- GFP (27 kDa) 136-424 M – kDa 425-496 C – – Inputs (2%) IP: GFP C GFP-CEP63 truncation proteins D GFP-CEP63 truncation proteins Inputs (5%) IP: GFP Inputs (5%) IP: GFP kDa kDa 1-135136-424425-4961-424136-496FL Ctl 1-135136-424425-4961-424136-496FL Ctl 1-135136-424425-4961-424136-496FL Ctl 1-135136-424425-4961-424136-496FL Ctl Myc- 150- Myc- 100- CCDC14 KIAA0753 100- 100- 75- 75- GFP- GFP- 50- CEP63 50- CEP63 37- 37- Figure S4 A siCtl
    [Show full text]
  • A Genome-Wide Association Study Identifies New Susceptibility Loci for Esophageal Adenocarcinoma and Barrett's Esophagus
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by White Rose Research Online This is an author produced version of A genome-wide association study identifies new susceptibility loci for esophageal adenocarcinoma and Barrett's esophagus.. White Rose Research Online URL for this paper: http://eprints.whiterose.ac.uk/105073/ Article: Levine, D.M., Ek, W.E., Zhang, R. et al. (31 more authors) (2013) A genome-wide association study identifies new susceptibility loci for esophageal adenocarcinoma and Barrett's esophagus. Nature Genetics, 45 (12). pp. 1487-1493. ISSN 1061-4036 https://doi.org/10.1038/ng.2796 promoting access to White Rose research papers [email protected] http://eprints.whiterose.ac.uk/ HHS Public Access Author manuscript Author Manuscript Author ManuscriptNat Genet Author Manuscript. Author manuscript; Author Manuscript available in PMC 2014 June 01. Published in final edited form as: Nat Genet. 2013 December ; 45(12): 1487–1493. doi:10.1038/ng.2796. A Genome-Wide Association Study Identifies New Susceptibility Loci for Esophageal Adenocarcinoma and Barrett’ s Esophagus David M. Levine1, Weronica E. Ek2, Rui Zhang1, Xinxue Liu3, Lynn Onstad4, Cassandra Sather5, Pierre Lao-Sirieix3, Marilie D. Gammon6, Douglas A. Corley7, Nicholas J. Shaheen8, Nigel C. Bird9, Laura J. Hardie10, Liam J. Murray11, Brian J. Reid4,12, Wong-Ho Chow13, Harvey A. Risch14, Olof Nyrén15, Weimin Ye15, Geoffrey Liu16, Yvonne Romero17,18, Leslie Bernstein19, Anna H. Wu20, Alan G. Casson21, Stephen Chanock22, Patricia Harrington23,24,25, Isabel Caldas25, Irene Debiram-Beecham3, Carlos Caldas25,26, Nicholas K. Hayward27, Paul Pharoah23,24,25, Rebecca Fitzgerald3, Stuart MacGregor2, David C.
    [Show full text]
  • Supplemental Information
    Supplemental information Dissection of the genomic structure of the miR-183/96/182 gene. Previously, we showed that the miR-183/96/182 cluster is an intergenic miRNA cluster, located in a ~60-kb interval between the genes encoding nuclear respiratory factor-1 (Nrf1) and ubiquitin-conjugating enzyme E2H (Ube2h) on mouse chr6qA3.3 (1). To start to uncover the genomic structure of the miR- 183/96/182 gene, we first studied genomic features around miR-183/96/182 in the UCSC genome browser (http://genome.UCSC.edu/), and identified two CpG islands 3.4-6.5 kb 5’ of pre-miR-183, the most 5’ miRNA of the cluster (Fig. 1A; Fig. S1 and Seq. S1). A cDNA clone, AK044220, located at 3.2-4.6 kb 5’ to pre-miR-183, encompasses the second CpG island (Fig. 1A; Fig. S1). We hypothesized that this cDNA clone was derived from 5’ exon(s) of the primary transcript of the miR-183/96/182 gene, as CpG islands are often associated with promoters (2). Supporting this hypothesis, multiple expressed sequences detected by gene-trap clones, including clone D016D06 (3, 4), were co-localized with the cDNA clone AK044220 (Fig. 1A; Fig. S1). Clone D016D06, deposited by the German GeneTrap Consortium (GGTC) (http://tikus.gsf.de) (3, 4), was derived from insertion of a retroviral construct, rFlpROSAβgeo in 129S2 ES cells (Fig. 1A and C). The rFlpROSAβgeo construct carries a promoterless reporter gene, the β−geo cassette - an in-frame fusion of the β-galactosidase and neomycin resistance (Neor) gene (5), with a splicing acceptor (SA) immediately upstream, and a polyA signal downstream of the β−geo cassette (Fig.
    [Show full text]
  • An Extensive Program of Periodic Alternative Splicing Linked to Cell
    RESEARCH ARTICLE An extensive program of periodic alternative splicing linked to cell cycle progression Daniel Dominguez1,2, Yi-Hsuan Tsai1,3, Robert Weatheritt4, Yang Wang1,2, Benjamin J Blencowe4*, Zefeng Wang1,5* 1Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, United States; 2Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, United States; 3Program in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, United States; 4Donnelly Centre and Department of Molecular Genetics, University of Toronto, Toronto, Canada; 5Key Lab of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Chinese Academy of Science, Shanghai, China Abstract Progression through the mitotic cell cycle requires periodic regulation of gene function at the levels of transcription, translation, protein-protein interactions, post-translational modification and degradation. However, the role of alternative splicing (AS) in the temporal control of cell cycle is not well understood. By sequencing the human transcriptome through two continuous cell cycles, we identify ~ 1300 genes with cell cycle-dependent AS changes. These genes are significantly enriched in functions linked to cell cycle control, yet they do not significantly overlap genes subject to periodic changes in steady-state transcript levels. Many of the periodically spliced genes are controlled by the SR protein kinase CLK1, whose level undergoes cell cycle- dependent fluctuations via an auto-inhibitory circuit. Disruption of CLK1 causes pleiotropic cell cycle defects and loss of proliferation, whereas CLK1 over-expression is associated with various *For correspondence: cancers. These results thus reveal a large program of CLK1-regulated periodic AS intimately [email protected] (BJB); associated with cell cycle control.
    [Show full text]
  • Molecular Genetics of Microcephaly Primary Hereditary: an Overview
    brain sciences Review Molecular Genetics of Microcephaly Primary Hereditary: An Overview Nikistratos Siskos † , Electra Stylianopoulou †, Georgios Skavdis and Maria E. Grigoriou * Department of Molecular Biology & Genetics, Democritus University of Thrace, 68100 Alexandroupolis, Greece; [email protected] (N.S.); [email protected] (E.S.); [email protected] (G.S.) * Correspondence: [email protected] † Equal contribution. Abstract: MicroCephaly Primary Hereditary (MCPH) is a rare congenital neurodevelopmental disorder characterized by a significant reduction of the occipitofrontal head circumference and mild to moderate mental disability. Patients have small brains, though with overall normal architecture; therefore, studying MCPH can reveal not only the pathological mechanisms leading to this condition, but also the mechanisms operating during normal development. MCPH is genetically heterogeneous, with 27 genes listed so far in the Online Mendelian Inheritance in Man (OMIM) database. In this review, we discuss the role of MCPH proteins and delineate the molecular mechanisms and common pathways in which they participate. Keywords: microcephaly; MCPH; MCPH1–MCPH27; molecular genetics; cell cycle 1. Introduction Citation: Siskos, N.; Stylianopoulou, Microcephaly, from the Greek word µικρoκεϕαλi´α (mikrokephalia), meaning small E.; Skavdis, G.; Grigoriou, M.E. head, is a term used to describe a cranium with reduction of the occipitofrontal head circum- Molecular Genetics of Microcephaly ference equal, or more that teo standard deviations
    [Show full text]
  • Scaffolding During the Cell Cycle by A-Kinase Anchoring Proteins
    Pflugers Arch - Eur J Physiol DOI 10.1007/s00424-015-1718-0 INVITED REVIEW Scaffolding during the cell cycle by A-kinase anchoring proteins B. Han1,2 & W. J. Poppinga1,2 & M. Schmidt1,2 Received: 12 May 2015 /Revised: 28 June 2015 /Accepted: 1 July 2015 # The Author(s) 2015. This article is published with open access at Springerlink.com Abstract Cell division relies on coordinated regulation of the specific AKAP subset in relation to diseases with focus on a cell cycle. A process including a well-defined series of strictly diverse subset of cancer. regulated molecular mechanisms involving cyclin-dependent kinases, retinoblastoma protein, and polo-like kinases. Dys- Keywords AKAPs . Scaffolding . Cell cycle . Proliferation . functions in cell cycle regulation are associated with disease Cancer such as cancer, diabetes, and neurodegeneration. Compart- mentalization of cellular signaling is a common strategy used to ensure the accuracy and efficiency of cellular responses. Introduction Compartmentalization of intracellular signaling is maintained by scaffolding proteins, such as A-kinase anchoring proteins The growth of organisms is driven by cell division which (AKAPs). AKAPs are characterized by their ability to anchor relies on coordinated regulation of phases in cell cycle [4]. the regulatory subunits of protein kinase A (PKA), and there- When the cell is quiescent, it remains in the G1 phase; how- by achieve guidance to different cellular locations via various ever, on initiation of cell division, it progresses into the S targeting domains. Next to PKA, AKAPs also associate with phase, during which DNA replication occurs, followed by a several other signaling elements including receptors, ion chan- separation of sister chromatids during the M phase, which in nels, protein kinases, phosphatases, small GTPases, and phos- turn is again separated in the pro-, meta-, ana-, and telophase, phodiesterases.
    [Show full text]
  • Genomic Discovery of an Evolutionarily Programmed Modality for Small-Molecule Targeting of an Intractable Protein Surface
    Genomic discovery of an evolutionarily programmed modality for small-molecule targeting of an intractable protein surface Uddhav K. Shigdela,1,2, Seung-Joo Leea,1,3, Mathew E. Sowaa,1,4, Brian R. Bowmana,1,5, Keith Robisona,6, Minyun Zhoua,7, Khian Hong Puaa,8, Dylan T. Stilesa,6, Joshua A. V. Blodgetta,9, Daniel W. Udwarya,10, Andrew T. Rajczewskia,11, Alan S. Manna,12, Siavash Mostafavia,13, Tara Hardyb, Sukrat Aryab,14, Zhigang Wenga,15, Michelle Stewarta,16, Kyle Kenyona,6, Jay P. Morgensterna,6, Ende Pana,17, Daniel C. Graya,6, Roy M. Pollocka,4, Andrew M. Fryb, Richard D. Klausnerc,18, Sharon A. Townsona,19, and Gregory L. Verdinea,d,e,f,2,18,20 Contributed by Richard D. Klausner, April 21, 2020 (sent for review April 8, 2020; reviewed by Chuan He and Ben Shen) The vast majority of intracellular protein targets are refractory toward small-molecule therapeutic engagement, and additional Author contributions: U.K.S., S.-J.L., M.E.S., B.R.B., K.R., Z.W., M.S., D.C.G., R.M.P., A.M.F., R.D.K., S.A.T., and G.L.V. designed research; U.K.S., S.-J.L., M.E.S., K.R., M.Z., K.H.P., D.T.S., therapeutic modalities are needed to overcome this deficiency. J.A.V.B., D.W.U., A.T.R., A.S.M., S.M., T.H., S.A., K.K., J.P.M., E.P., R.D.K., and G.L.V. performed Here, the identification and characterization of a natural product, research; M.E.S., D.T.S., and A.M.F.
    [Show full text]
  • Polo-Like Kinase 1 Regulates Nlp, a Centrosome Protein Involved in Microtubule Nucleation
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Developmental Cell, Vol. 5, 113–125, July, 2003, Copyright 2003 by Cell Press Polo-like Kinase 1 Regulates Nlp, a Centrosome Protein Involved in Microtubule Nucleation Martina Casenghi,1,2 Patrick Meraldi,1,2,3 Rieder, 1999; Palazzo et al., 2000). Although centrosome Ulrike Weinhart,1 Peter I. Duncan,1,4 maturation is important for mitotic spindle formation, the Roman Ko¨ rner,1 and Erich A. Nigg1,* underlying mechanisms remain largely unknown. Two 1Department of Cell Biology protein kinases, Polo-like kinase 1 (Plk1; Lane and Nigg, Max Planck Institute of Biochemistry 1996; Sunkel and Glover, 1988) and Aurora-A (Berdnik Am Klopferspitz 18a and Knoblich, 2002; Hannak et al., 2001), as well as D-82152 Martinsried protein phosphatase 4 (Helps et al., 1998; Sumiyoshi Germany et al., 2002), have been implicated in the regulation of centrosome maturation, but the substrates of these en- zymes await identification. Also acting at the G2/M tran- sition, the protein kinase Nek2 and a member of the Summary phosphatase 1 family contribute to regulate centrosome separation, in part through phosphorylation of the centri- In animal cells, most microtubules are nucleated at ole-associated protein C-Nap1 (Fry et al., 1998b; Helps centrosomes. At the onset of mitosis, centrosomes et al., 2000; Mayor et al., 2000). undergo a structural reorganization, termed matura- The discovery of ␥-tubulin and ␥-tubulin-containing tion, which leads to increased microtubule nucleation multiprotein complexes has greatly advanced our un- activity.
    [Show full text]