1 Phylogenetic and Genomic Analyses of the Ribosomal Oxygenases Riox1 (No66) And
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Dual Proteome-Scale Networks Reveal Cell-Specific Remodeling of the Human Interactome
bioRxiv preprint doi: https://doi.org/10.1101/2020.01.19.905109; this version posted January 19, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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. Dual Proteome-scale Networks Reveal Cell-specific Remodeling of the Human Interactome Edward L. Huttlin1*, Raphael J. Bruckner1,3, Jose Navarrete-Perea1, Joe R. Cannon1,4, Kurt Baltier1,5, Fana Gebreab1, Melanie P. Gygi1, Alexandra Thornock1, Gabriela Zarraga1,6, Stanley Tam1,7, John Szpyt1, Alexandra Panov1, Hannah Parzen1,8, Sipei Fu1, Arvene Golbazi1, Eila Maenpaa1, Keegan Stricker1, Sanjukta Guha Thakurta1, Ramin Rad1, Joshua Pan2, David P. Nusinow1, Joao A. Paulo1, Devin K. Schweppe1, Laura Pontano Vaites1, J. Wade Harper1*, Steven P. Gygi1*# 1Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA. 2Broad Institute, Cambridge, MA, 02142, USA. 3Present address: ICCB-Longwood Screening Facility, Harvard Medical School, Boston, MA, 02115, USA. 4Present address: Merck, West Point, PA, 19486, USA. 5Present address: IQ Proteomics, Cambridge, MA, 02139, USA. 6Present address: Vor Biopharma, Cambridge, MA, 02142, USA. 7Present address: Rubius Therapeutics, Cambridge, MA, 02139, USA. 8Present address: RPS North America, South Kingstown, RI, 02879, USA. *Correspondence: [email protected] (E.L.H.), [email protected] (J.W.H.), [email protected] (S.P.G.) #Lead Contact: [email protected] bioRxiv preprint doi: https://doi.org/10.1101/2020.01.19.905109; this version posted January 19, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. -
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. -
(MINA) (NM 032778) Human Tagged ORF Clone Product Data
OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for RC212554L4 MINA53 (MINA) (NM_032778) Human Tagged ORF Clone Product data: Product Type: Expression Plasmids Product Name: MINA53 (MINA) (NM_032778) Human Tagged ORF Clone Tag: mGFP Symbol: RIOX2 Synonyms: JMJD10; MDIG; MINA; MINA53; NO52; ROX Vector: pLenti-C-mGFP-P2A-Puro (PS100093) E. coli Selection: Chloramphenicol (34 ug/mL) Cell Selection: Puromycin ORF Nucleotide The ORF insert of this clone is exactly the same as(RC212554). Sequence: Restriction Sites: SgfI-MluI Cloning Scheme: ACCN: NM_032778 ORF Size: 1392 bp This product is to be used for laboratory only. Not for diagnostic or therapeutic use. View online » ©2021 OriGene Technologies, Inc., 9620 Medical Center Drive, Ste 200, Rockville, MD 20850, US 1 / 2 MINA53 (MINA) (NM_032778) Human Tagged ORF Clone – RC212554L4 OTI Disclaimer: The molecular sequence of this clone aligns with the gene accession number as a point of reference only. However, individual transcript sequences of the same gene can differ through naturally occurring variations (e.g. polymorphisms), each with its own valid existence. This clone is substantially in agreement with the reference, but a complete review of all prevailing variants is recommended prior to use. More info OTI Annotation: This clone was engineered to express the complete ORF with an expression tag. Expression varies depending on the nature of the gene. RefSeq: NM_032778.3, NP_116167.3 RefSeq Size: 2221 bp RefSeq ORF: 1395 bp Locus ID: 84864 UniProt ID: Q8IUF8 Protein Families: Druggable Genome MW: 52.5 kDa Gene Summary: MINA is a c-Myc (MYC; MIM 190080) target gene that may play a role in cell proliferation or regulation of cell growth. -
Electronic Supplementary Material (ESI) for Metallomics
Electronic Supplementary Material (ESI) for Metallomics. This journal is © The Royal Society of Chemistry 2018 Uniprot Entry name Gene names Protein names Predicted Pattern Number of Iron role EC number Subcellular Membrane Involvement in disease Gene ontology (biological process) Id iron ions location associated 1 P46952 3HAO_HUMAN HAAO 3-hydroxyanthranilate 3,4- H47-E53-H91 1 Fe cation Catalytic 1.13.11.6 Cytoplasm No NAD biosynthetic process [GO:0009435]; neuron cellular homeostasis dioxygenase (EC 1.13.11.6) (3- [GO:0070050]; quinolinate biosynthetic process [GO:0019805]; response to hydroxyanthranilate oxygenase) cadmium ion [GO:0046686]; response to zinc ion [GO:0010043]; tryptophan (3-HAO) (3-hydroxyanthranilic catabolic process [GO:0006569] acid dioxygenase) (HAD) 2 O00767 ACOD_HUMAN SCD Acyl-CoA desaturase (EC H120-H125-H157-H161; 2 Fe cations Catalytic 1.14.19.1 Endoplasmic Yes long-chain fatty-acyl-CoA biosynthetic process [GO:0035338]; unsaturated fatty 1.14.19.1) (Delta(9)-desaturase) H160-H269-H298-H302 reticulum acid biosynthetic process [GO:0006636] (Delta-9 desaturase) (Fatty acid desaturase) (Stearoyl-CoA desaturase) (hSCD1) 3 Q6ZNF0 ACP7_HUMAN ACP7 PAPL PAPL1 Acid phosphatase type 7 (EC D141-D170-Y173-H335 1 Fe cation Catalytic 3.1.3.2 Extracellular No 3.1.3.2) (Purple acid space phosphatase long form) 4 Q96SZ5 AEDO_HUMAN ADO C10orf22 2-aminoethanethiol dioxygenase H112-H114-H193 1 Fe cation Catalytic 1.13.11.19 Unknown No oxidation-reduction process [GO:0055114]; sulfur amino acid catabolic process (EC 1.13.11.19) (Cysteamine -
The Viral Oncoproteins Tax and HBZ Reprogram the Cellular Mrna Splicing Landscape
bioRxiv preprint doi: https://doi.org/10.1101/2021.01.18.427104; this version posted January 18, 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. The viral oncoproteins Tax and HBZ reprogram the cellular mRNA splicing landscape Charlotte Vandermeulen1,2,3, Tina O’Grady3, Bartimee Galvan3, Majid Cherkaoui1, Alice Desbuleux1,2,4,5, Georges Coppin1,2,4,5, Julien Olivet1,2,4,5, Lamya Ben Ameur6, Keisuke Kataoka7, Seishi Ogawa7, Marc Thiry8, Franck Mortreux6, Michael A. Calderwood2,4,5, David E. Hill2,4,5, Johan Van Weyenbergh9, Benoit Charloteaux2,4,5,10, Marc Vidal2,4*, Franck Dequiedt3*, and Jean-Claude Twizere1,2,11* 1Laboratory of Viral Interactomes, GIGA Institute, University of Liege, Liege, Belgium.2Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA.3Laboratory of Gene Expression and Cancer, GIGA Institute, University of Liege, Liege, Belgium.4Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA. 5Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA.6Laboratory of Biology and Modeling of the Cell, CNRS UMR 5239, INSERM U1210, University of Lyon, Lyon, France.7Department of Pathology and Tumor Biology, Kyoto University, Japan.8Unit of Cell and Tissue Biology, GIGA Institute, University of Liege, Liege, Belgium.9Laboratory of Clinical and Epidemiological Virology, Rega Institute for Medical Research, Department of Microbiology, Immunology and Transplantation, Catholic University of Leuven, Leuven, Belgium.10Department of Human Genetics, CHU of Liege, University of Liege, Liege, Belgium.11Lead Contact. *Correspondence: [email protected]; [email protected]; [email protected] bioRxiv preprint doi: https://doi.org/10.1101/2021.01.18.427104; this version posted January 18, 2021. -
Supplementary Material Computational Prediction of SARS
Supplementary_Material Computational prediction of SARS-CoV-2 encoded miRNAs and their putative host targets Sheet_1 List of potential stem-loop structures in SARS-CoV-2 genome as predicted by VMir. Rank Name Start Apex Size Score Window Count (Absolute) Direct Orientation 1 MD13 2801 2864 125 243.8 61 2 MD62 11234 11286 101 211.4 49 4 MD136 27666 27721 104 205.6 119 5 MD108 21131 21184 110 204.7 210 9 MD132 26743 26801 119 188.9 252 19 MD56 9797 9858 128 179.1 59 26 MD139 28196 28233 72 170.4 133 28 MD16 2934 2974 76 169.9 71 43 MD103 20002 20042 80 159.3 403 46 MD6 1489 1531 86 156.7 171 51 MD17 2981 3047 131 152.8 38 87 MD4 651 692 75 140.3 46 95 MD7 1810 1872 121 137.4 58 116 MD140 28217 28252 72 133.8 62 122 MD55 9712 9758 96 132.5 49 135 MD70 13171 13219 93 130.2 131 164 MD95 18782 18820 79 124.7 184 173 MD121 24086 24135 99 123.1 45 176 MD96 19046 19086 75 123.1 179 196 MD19 3197 3236 76 120.4 49 200 MD86 17048 17083 73 119.8 428 223 MD75 14534 14600 137 117 51 228 MD50 8824 8870 94 115.8 79 234 MD129 25598 25642 89 115.6 354 Reverse Orientation 6 MR61 19088 19132 88 197.8 271 10 MR72 23563 23636 148 188.8 286 11 MR11 3775 3844 136 185.1 116 12 MR94 29532 29582 94 184.6 271 15 MR43 14973 15028 109 183.9 226 27 MR14 4160 4206 89 170 241 34 MR35 11734 11792 111 164.2 37 52 MR5 1603 1652 89 152.7 118 53 MR57 18089 18132 101 152.7 139 94 MR8 2804 2864 122 137.4 38 107 MR58 18474 18508 72 134.9 237 117 MR16 4506 4540 72 133.8 311 120 MR34 10010 10048 82 132.7 245 133 MR7 2534 2578 90 130.4 75 146 MR79 24766 24808 75 127.9 59 150 MR65 21528 21576 99 127.4 83 180 MR60 19016 19049 70 122.5 72 187 MR51 16450 16482 75 121 363 190 MR80 25687 25734 96 120.6 75 198 MR64 21507 21544 70 120.3 35 206 MR41 14500 14542 84 119.2 94 218 MR84 26840 26894 108 117.6 94 Sheet_2 List of stable stem-loop structures based on MFE. -
HLA-Dependent Variation in SARS-Cov-2 CD8+ T Cell Cross- 2 Reactivity with Human Coronaviruses 3 4 Paul R
bioRxiv preprint doi: https://doi.org/10.1101/2021.07.17.452778; this version posted July 20, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 1 HLA-dependent variation in SARS-CoV-2 CD8+ T cell cross- 2 reactivity with human coronaviruses 3 4 Paul R. Buckley1,2, Chloe H. Lee1,2, Mariana Pereira Pinho1, Rosana Ottakandathil Babu1,2, 5 Jeongmin Woo1,2, Agne Antanaviciute1,2, Alison Simmons1, Graham Ogg1, Hashem 6 Koohy1,2,+ 7 8 1 MRC Human Immunology Unit, Medical Research Council (MRC) Human Immunology 9 Unit, MRC Weatherall Institute of Molecular Medicine (WIMM), John Radcliffe Hospital, 10 University of Oxford, Oxford, United Kingdom. 11 12 2 MRC WIMM Centre for Computational Biology, Medical Research Council (MRC) 13 Weatherall Institute of Molecular Medicine, John Radcliffe Hospital, University of Oxford, 14 Oxford, United Kingdom. 15 16 + Correspondence: [email protected] 17 18 Abstract 19 20 Pre-existing T cell immunity to SARS-CoV-2 in individuals without prior exposure to SARS- 21 CoV-2 has been reported in several studies. While emerging evidence hints toward prior 22 exposure to common-cold human coronaviruses (HCoV), the extent of- and conditions for- 23 cross-protective immunity between SARS-CoV-2 and HCoVs remain open. Here, by 24 leveraging a comprehensive pool of publicly available functionally evaluated SARS-CoV-2 25 peptides, we report 126 immunogenic SARS-CoV-2 peptides with high sequence similarity to 26 285 MHC-presented target peptides from at least one of four HCoV, thus providing a map 27 describing the landscape of SARS-CoV-2 shared and private immunogenic peptides with 28 functionally validated T cell responses. -
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by Submitted in partial satisfaction of the requirements for degree of in in the GRADUATE DIVISION of the UNIVERSITY OF CALIFORNIA, SAN FRANCISCO Approved: ______________________________________________________________________________ Chair ______________________________________________________________________________ ______________________________________________________________________________ ______________________________________________________________________________ ______________________________________________________________________________ Committee Members Copyright 2019 by Adolfo Cuesta ii Acknowledgements For me, completing a doctoral dissertation was a huge undertaking that was only possible with the support of many people along the way. First, I would like to thank my PhD advisor, Jack Taunton. He always gave me the space to pursue my own ideas and interests, while providing thoughtful guidance. Nearly every aspect of this project required a technique that was completely new to me. He trusted that I was up to the challenge, supported me throughout, helped me find outside resources when necessary. I remain impressed with his voracious appetite for the literature, and ability to recall some of the most subtle, yet most important details in a paper. Most of all, I am thankful that Jack has always been so generous with his time, both in person, and remotely. I’ve enjoyed our many conversations and hope that they will continue. I’d also like to thank my thesis committee, Kevan Shokat and David Agard for their valuable support, insight, and encouragement throughout this project. My lab mates in the Taunton lab made this such a pleasant experience, even on the days when things weren’t working well. I worked very closely with Tangpo Yang on the mass spectrometry aspects of this project. Xiaobo Wan taught me almost everything I know about protein crystallography. Thank you as well to Geoff Smith, Jordan Carelli, Pat Sharp, Yazmin Carassco, Keely Oltion, Nicole Wenzell, Haoyuan Wang, Steve Sethofer, and Shyam Krishnan, Shawn Ouyang and Qian Zhao. -
Estudio De Regiones Genómicas Asociadas a La Varianza Ambiental Del Tamaño De Camada En Conejos
MÁSTER EN MEJORA GENÉTICA ANIMAL Y BIOTECNOLOGÍA DE LA REPRODUCCIÓN ESTUDIO DE REGIONES GENÓMICAS ASOCIADAS A LA VARIANZA AMBIENTAL DEL TAMAÑO DE CAMADA EN CONEJOS Proyecto Final de Máster Cristina Casto Rebollo Universitat Politècnica de València Julio 2018 Directora: Dra. Noelia Ibáñez Escriche 1 ÍNDICE GENERAL ABSTRACT ............................................................................................................................... 7 RESUMEN ................................................................................................................................. 8 RESUM .................................................................................................................................... 10 1. REVISIÓN BIBLIOGRÁFICA ........................................................................................... 12 2. OBJETIVOS ......................................................................................................................... 23 ARTÍCULO 1: ESTUDIO DE REGIONES GENÓMICAS ASOCIADAS A LA VARIANZA AMBIENTAL EN EL TAMAÑO DE CAMADA EN CONEJOS .......................................... 24 1. INTRODUCCIÓN ............................................................................................................... 24 2. MATERIALES Y MÉTODOS ............................................................................................ 25 2.1. Material fenotípico y genotípico. .................................................................................. 25 2.2. Procesado de datos. ...................................................................................................... -
Unraveling the Sperm Transcriptome by Next Generation Sequencing and the Global Epigenetic Landscape in Infertile Men Fadi Choucair
Unraveling the sperm transcriptome by next generation sequencing and the global epigenetic landscape in infertile men Fadi Choucair To cite this version: Fadi Choucair. Unraveling the sperm transcriptome by next generation sequencing and the global epigenetic landscape in infertile men. Molecular biology. Université Côte d’Azur; Université libanaise, 2018. English. NNT : 2018AZUR4058. tel-01958881 HAL Id: tel-01958881 https://tel.archives-ouvertes.fr/tel-01958881 Submitted on 18 Dec 2018 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. THÈSE DE DOCTORAT Exploration du transcriptome spermatique par le séquençage nouvelle génération et le portrait épigénétique de l’infertilité masculine Unraveling the sperm transcriptome by next generation sequencing and the global epigenetic landscape in infertile men Fadi CHOUCAIR INSERM U1065, C3M Présentée en vue de l’obtention Devant le jury, composé de : du grade de docteur en interactions Mme RACHEL LEVY, PR, UMRS 938, UPMC M. FABIEN MONGELARD, MC, CRCL, ENS Lyon moléculaires et cellulaires Mme NINA SAADALLAH-ZEIDAN, -
Exosomal Long Non-Coding Rnas in Lung Diseases
International Journal of Molecular Sciences Review Exosomal Long Non-Coding RNAs in Lung Diseases Christophe Poulet 1,2,3,* , Makon-Sébastien Njock 1,2,3,4 , Catherine Moermans 3,4 , Edouard Louis 2,3,5 , Renaud Louis 2,3,4, Michel Malaise 1,2,3 and Julien Guiot 2,3,4,* 1 Department of Rheumatology, University Hospital of Liège (CHULiege), 4000 Liège, Belgium; [email protected] (M.-S.N.); [email protected] (M.M.) 2 Fibropôle Research Group, University Hospital of Liège (CHULiege), 4000 Liège, Belgium; [email protected] (E.L.); [email protected] (R.L.); 3 GIGA-I3 Research Group, GIGA Institute, University of Liège (ULiege) and University Hospital of Liège (CHULiege), 4000 Liège, Belgium; [email protected] 4 Department of Respiratory Diseases, University Hospital of Liège (CHULiege), 4000 Liège, Belgium 5 Department of Gastroenterology, University Hospital of Liège (CHULiege), 4000 Liège, Belgium * Correspondence: [email protected] (C.P.); [email protected] (J.G.); Tel.: +32-4-366-37-78 (C.P.) Received: 1 May 2020; Accepted: 15 May 2020; Published: 19 May 2020 Abstract: Within the non-coding genome landscape, long non-coding RNAs (lncRNAs) and their secretion within exosomes are a window that could further explain the regulation, the sustaining, and the spread of lung diseases. We present here a compilation of the current knowledge on lncRNAs commonly found in Chronic Obstructive Pulmonary Disease (COPD), asthma, Idiopathic Pulmonary Fibrosis (IPF), or lung cancers. We built interaction networks describing the mechanisms of action for COPD, asthma, and IPF, as well as private networks for H19, MALAT1, MEG3, FENDRR, CDKN2B-AS1, TUG1, HOTAIR, and GAS5 lncRNAs in lung cancers. -
Drosophila As a Tool to Understand the Genetics of Human Alcoholism
International Journal of Molecular Sciences Review Flying Together: Drosophila as a Tool to Understand the Genetics of Human Alcoholism Daniel R. Lathen 1 , Collin B. Merrill 2 and Adrian Rothenfluh 1,2,3,4,* 1 Department of Psychiatry and Neuroscience Ph.D. Program, University of Utah, Salt Lake City, UT 84108, USA; [email protected] 2 Molecular Medicine Program, University of Utah, Salt Lake City, UT 84112, USA; [email protected] 3 Department of Neurobiology and Anatomy, University of Utah, Salt Lake City, UT 84132, USA 4 Department of Human Genetics, University of Utah, Salt Lake City, UT 84112, USA * Correspondence: adrian.rothenfl[email protected] Received: 11 August 2020; Accepted: 8 September 2020; Published: 11 September 2020 Abstract: Alcohol use disorder (AUD) exacts an immense toll on individuals, families, and society. Genetic factors determine up to 60% of an individual’s risk of developing problematic alcohol habits. Effective AUD prevention and treatment requires knowledge of the genes that predispose people to alcoholism, play a role in alcohol responses, and/or contribute to the development of addiction. As a highly tractable and translatable genetic and behavioral model organism, Drosophila melanogaster has proven valuable to uncover important genes and mechanistic pathways that have obvious orthologs in humans and that help explain the complexities of addiction. Vinegar flies exhibit remarkably strong face and mechanistic validity as a model for AUDs, permitting many advancements in the quest to understand human genetic involvement in this disease. These advancements occur via approaches that essentially fall into one of two categories: (1) discovering candidate genes via human genome-wide association studies (GWAS), transcriptomics on post-mortem tissue from AUD patients, or relevant physiological connections, then using reverse genetics in flies to validate candidate genes’ roles and investigate their molecular function in the context of alcohol.