Narayanan R. Ebola–Associated Genes in the Human Genome
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The Role of Nuclear Lamin B1 in Cell Proliferation and Senescence
Downloaded from genesdev.cshlp.org on September 29, 2021 - Published by Cold Spring Harbor Laboratory Press The role of nuclear lamin B1 in cell proliferation and senescence Takeshi Shimi,1 Veronika Butin-Israeli,1 Stephen A. Adam,1 Robert B. Hamanaka,2 Anne E. Goldman,1 Catherine A. Lucas,1 Dale K. Shumaker,1 Steven T. Kosak,1 Navdeep S. Chandel,2 and Robert D. Goldman1,3 1Department of Cell and Molecular Biology, 2Department of Medicine, Division of Pulmonary and Critical Care Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois 60611, USA Nuclear lamin B1 (LB1) is a major structural component of the nucleus that appears to be involved in the regulation of many nuclear functions. The results of this study demonstrate that LB1 expression in WI-38 cells decreases during cellular senescence. Premature senescence induced by oncogenic Ras also decreases LB1 expression through a retinoblastoma protein (pRb)-dependent mechanism. Silencing the expression of LB1 slows cell proliferation and induces premature senescence in WI-38 cells. The effects of LB1 silencing on proliferation require the activation of p53, but not pRb. However, the induction of premature senescence requires both p53 and pRb. The proliferation defects induced by silencing LB1 are accompanied by a p53-dependent reduction in mitochondrial reactive oxygen species (ROS), which can be rescued by growth under hypoxic conditions. In contrast to the effects of LB1 silencing, overexpression of LB1 increases the proliferation rate and delays the onset of senescence of WI-38 cells. This overexpression eventually leads to cell cycle arrest at the G1/S boundary. -
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. -
United States Patent (19) 11 Patent Number: 5,981,727 Baden Et Al
USOO5981727A United States Patent (19) 11 Patent Number: 5,981,727 Baden et al. (45) Date of Patent: Nov. 9, 1999 54 PLANT GROUP 2 PROMOTERS AND USES OTHER PUBLICATIONS THEREOF Oommen et al (1994) The Plant Cell 6: 1789–1803. 75 Inventors: Catherine S. Baden, Martinez, Pamela Lewin, (1985) In: Genes II, Wiley and Sons, NY, pp. Dunsmuir, Piedmont; Kathleen Y. Lee, 182-183. Oakland, all of Calif. Van Haaven et al (1991) Plant Mol Biol 17: 615-630. 73 Assignee: DNA Plant Technology Corporation, Pear et al (1989) Plant Mol Biol 13: 639-651. Oakland, Calif. Primary Examiner Elizabeth F. McElwain 21 Appl. No.: 08/761,549 Attorney, Agent, or Firm Townsend and Townsend and 22 Filed: Dec. 6, 1996 Crew Related U.S. Application Data 57 ABSTRACT This invention relates to compositions and methods useful in 63 Continuation of application No. 08/289,458, Aug. 12, 1994, the production of transgenic plants. In particular, the inven Pat. No. 5,608,144. tion relates to Group 2 (Gp2) plant promoter Sequences and 51 Int. Cl. ............................ C12N 15700;s CO7H 21/04 to expressionp cassettes containingg Gp2Op.4 planlplant ppromoter 52 U.S. Cl. ...................... 536/23.6; 536/24.1; 435/1723 Sequences. The invention also relates to vectors and trans 58 Field of Search ........................... 800/205; 435/69.1, genic plants containing Gp2 plant promoter Sequences that 435/172.3, 419, 536/24.1, 23.6 are operably linked to heterologous DNA sequences. In addition, the invention relates to methods of producing 56) References Cited transgenic plants by using vectors containing Gp2 promoter Sequences. -
The Landscape of Human Mutually Exclusive Splicing
bioRxiv preprint doi: https://doi.org/10.1101/133215; this version posted May 2, 2017. 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-ND 4.0 International license. The landscape of human mutually exclusive splicing Klas Hatje1,2,#,*, Ramon O. Vidal2,*, Raza-Ur Rahman2, Dominic Simm1,3, Björn Hammesfahr1,$, Orr Shomroni2, Stefan Bonn2§ & Martin Kollmar1§ 1 Group of Systems Biology of Motor Proteins, Department of NMR-based Structural Biology, Max-Planck-Institute for Biophysical Chemistry, Göttingen, Germany 2 Group of Computational Systems Biology, German Center for Neurodegenerative Diseases, Göttingen, Germany 3 Theoretical Computer Science and Algorithmic Methods, Institute of Computer Science, Georg-August-University Göttingen, Germany § Corresponding authors # Current address: Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland $ Current address: Research and Development - Data Management (RD-DM), KWS SAAT SE, Einbeck, Germany * These authors contributed equally E-mail addresses: KH: [email protected], RV: [email protected], RR: [email protected], DS: [email protected], BH: [email protected], OS: [email protected], SB: [email protected], MK: [email protected] - 1 - bioRxiv preprint doi: https://doi.org/10.1101/133215; this version posted May 2, 2017. 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. -
Genome-Scale Single-Cell Mechanical Phenotyping Reveals Disease-Related Genes Involved in Mitotic Rounding
ARTICLE DOI: 10.1038/s41467-017-01147-6 OPEN Genome-scale single-cell mechanical phenotyping reveals disease-related genes involved in mitotic rounding Yusuke Toyoda 1,2, Cedric J. Cattin3, Martin P. Stewart 3,4,5, Ina Poser1, Mirko Theis6, Teymuras V. Kurzchalia1, Frank Buchholz1,6, Anthony A. Hyman1 & Daniel J. Müller 3 To divide, most animal cells drastically change shape and round up against extracellular confinement. Mitotic cells facilitate this process by generating intracellular pressure, which the contractile actomyosin cortex directs into shape. Here, we introduce a genome-scale microcantilever- and RNAi-based approach to phenotype the contribution of > 1000 genes to the rounding of single mitotic cells against confinement. Our screen analyzes the rounding force, pressure and volume of mitotic cells and localizes selected proteins. We identify 49 genes relevant for mitotic rounding, a large portion of which have not previously been linked to mitosis or cell mechanics. Among these, depleting the endoplasmic reticulum-localized protein FAM134A impairs mitotic progression by affecting metaphase plate alignment and pressure generation by delocalizing cortical myosin II. Furthermore, silencing the DJ-1 gene uncovers a link between mitochondria-associated Parkinson’s disease and mitotic pressure. We conclude that mechanical phenotyping is a powerful approach to study the mechanisms governing cell shape. 1 Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstrasse 108, 01307 Dresden, Germany. 2 Division of Cell Biology, Life Science Institute, Kurume University, Hyakunen-Kohen 1-1, Kurume, Fukuoka 839-0864, Japan. 3 Department of Biosystems Science and Engineering (D-BSSE), Eidgenössische Technische Hochschule (ETH) Zurich, Mattenstrasse 26, 4058 Basel, Switzerland. -
Annotation and Biological Information
Microarray annotation and biological information Benedikt Brors Dept. Intelligent Bioinformatics Systems German Cancer Research Center [email protected] Why do we need microarray clone annotation? Often, the result of microarray data analysis is a list of genes. • The list has to be summarized with respect to its biological • meaning. For this, information about the genes and the related proteins has to be gathered. If the list is small (let’s say, 1–30), this is easily done by reading • database information and/or the available literature. Sometimes, lists are longer (100s or even 1000s of genes). • Automatic parsing and extracting of information is needed. To get complete information, you will need the help of • an experienced computational biologist (aka ‘bioinformatician’). However, there is a lot that you can do on your own. Primary databases Some information about genes and the encoded proteins • is available already from sequence databases, e.g. database accession number, nucleotide and protein sequences, database cross references, and a sequence name that may or may not give a hint to the function. To find a sequence in another database, use sequence comparison tools like BLAST. There are large repositories for sequence data, the most • prominent being EMBL, GenBank and DDBJ (these 3 are redundant). Because they are so large, nobody cares about the quality of the data. Everybody having internet access can deposit sequence information there. Errors introduced long time ago will stay there forever. GenBank information from NCBI Curated databases In contrast, some databases are curated. That means that • biologists will get the information first and compare them with literature before it goes into the database. -
Production of Recombinant Retroviruses Encoding Human Flt3 Ligand and IL-6 and Establishment of Genetically Modified OP9 Mouse Stromal Cells
Journal of Bacteriology and Virology 2007. Vol. 37, No. 1 p.31 – 38 Production of Recombinant Retroviruses Encoding Human Flt3 Ligand and IL-6 and Establishment of Genetically Modified OP9 Mouse Stromal Cells Ho-Bum Kang1,2, Young-Eun Kim1, Hyo-Jin Kang1, Ae-Ran Lee1, Dai-Eun Seok2 and Younghee Lee1* 1Department of Biochemistry, College of Natural Sciences, Chungbuk National University, Cheongju, Chungbuk, 361-763, Korea and 2Department of Pharmacy, College of Pharmacy, Chungnam National University, Yusong, Daejon, 305-764, Korea Received : December 2, 2006 Accepted : January 24, 2007 Flt3 Ligand (FL) and IL-6 are multifunctional cytokines implicated in normal hematopoiesis and ex vivo expansion of hematopoietic stem cells. Retroviral vectors are useful for stable expression of genes in many cells. Here, we aimed to produce retroviral vectors directing expression of human FL and IL-6 genes. Recombinant retroviral vectors containing human genes for FL and IL-6 were constructed using a retroviral vector pLXSN. Recombinant retroviruses were produced from GP2-293 cells with the aid of pseudo-envelope protein gene VSV-G, and efficiently transduced to a mouse stromal cell line OP9. Genetically modified OP9 cells clearly showed expression of human FL or IL-6 gene at the mRNA level determined by RT-PCR. Based on the results from ELISA, human FL and IL-6 were detected in the cell culture medium of OP9/FL and OP9/IL-6 cells, respectively. As the recombinant human FL and IL-6 proteins are successfully produced and secreted to the culture medium, this system can be useful in future application such as ex vivo expansion of hematopoietic stem cells and differentiation of embryonic stem cells. -
Nº Ref Uniprot Proteína Péptidos Identificados Por MS/MS 1 P01024
Document downloaded from http://www.elsevier.es, day 26/09/2021. This copy is for personal use. Any transmission of this document by any media or format is strictly prohibited. Nº Ref Uniprot Proteína Péptidos identificados 1 P01024 CO3_HUMAN Complement C3 OS=Homo sapiens GN=C3 PE=1 SV=2 por 162MS/MS 2 P02751 FINC_HUMAN Fibronectin OS=Homo sapiens GN=FN1 PE=1 SV=4 131 3 P01023 A2MG_HUMAN Alpha-2-macroglobulin OS=Homo sapiens GN=A2M PE=1 SV=3 128 4 P0C0L4 CO4A_HUMAN Complement C4-A OS=Homo sapiens GN=C4A PE=1 SV=1 95 5 P04275 VWF_HUMAN von Willebrand factor OS=Homo sapiens GN=VWF PE=1 SV=4 81 6 P02675 FIBB_HUMAN Fibrinogen beta chain OS=Homo sapiens GN=FGB PE=1 SV=2 78 7 P01031 CO5_HUMAN Complement C5 OS=Homo sapiens GN=C5 PE=1 SV=4 66 8 P02768 ALBU_HUMAN Serum albumin OS=Homo sapiens GN=ALB PE=1 SV=2 66 9 P00450 CERU_HUMAN Ceruloplasmin OS=Homo sapiens GN=CP PE=1 SV=1 64 10 P02671 FIBA_HUMAN Fibrinogen alpha chain OS=Homo sapiens GN=FGA PE=1 SV=2 58 11 P08603 CFAH_HUMAN Complement factor H OS=Homo sapiens GN=CFH PE=1 SV=4 56 12 P02787 TRFE_HUMAN Serotransferrin OS=Homo sapiens GN=TF PE=1 SV=3 54 13 P00747 PLMN_HUMAN Plasminogen OS=Homo sapiens GN=PLG PE=1 SV=2 48 14 P02679 FIBG_HUMAN Fibrinogen gamma chain OS=Homo sapiens GN=FGG PE=1 SV=3 47 15 P01871 IGHM_HUMAN Ig mu chain C region OS=Homo sapiens GN=IGHM PE=1 SV=3 41 16 P04003 C4BPA_HUMAN C4b-binding protein alpha chain OS=Homo sapiens GN=C4BPA PE=1 SV=2 37 17 Q9Y6R7 FCGBP_HUMAN IgGFc-binding protein OS=Homo sapiens GN=FCGBP PE=1 SV=3 30 18 O43866 CD5L_HUMAN CD5 antigen-like OS=Homo -
Identification of Growth Trait Related Genes in a Yorkshire Purebred Pig Population by Genome-Wide Association Studies
Open Access Asian-Australas J Anim Sci Vol. 30, No. 4:462-469 April 2017 https://doi.org/10.5713/ajas.16.0548 pISSN 1011-2367 eISSN 1976-5517 Identification of growth trait related genes in a Yorkshire purebred pig population by genome-wide association studies Qingli Meng1,a, Kejun Wang2,a, Xiaolei Liu3, Haishen Zhou1, Li Xu1, Zhaojun Wang1,*, and Meiying Fang2,* * Corresponding Authors: Zhaojun Wang Objective: The aim of this study is to identify genomic regions or genes controlling growth Tel: +86-010-82475589, Fax: +86-010-82475589, E-mail: [email protected] traits in pigs. Meiying Fang Methods: Using a panel of 54,148 single nucleotide polymorphisms (SNPs), we performed a Tel: +86-010-62734943, Fax: +86-010-62734943, genome-wide Association (GWA) study in 562 pure Yorshire pigs with four growth traits: average E-mail: [email protected] daily gain from 30 kg to 100 kg or 115 kg, and days to 100 kg or 115 kg. Fixed and random model 1 Beijing Breeding Swine Center, Beijing 100194, China Circulating Probability Unification method was used to identify the associations between 2 Department of Animal Genetics and Breeding, 54,148 SNPs and these four traits. SNP annotations were performed through the Sus scrofa data National Engineering Laboratory for Animal Breeding, MOA Laboratory of Animal Genetics and Breeding, set from Ensembl. Bioinformatics analysis, including gene ontology analysis, pathway analysis College of Animal Science and Technology, China and network analysis, was used to identify the candidate genes. Agricultural University, -
Mutations of the UMOD Gene Are Responsible for Medullary Cystic Kidney Disease 2 and Familial Juvenile Hyperuricaemic Nephropath
882 J Med Genet: first published as 10.1136/jmg.39.12.882 on 1 December 2002. Downloaded from ORIGINAL ARTICLE Mutations of the UMOD gene are responsible for medullary cystic kidney disease 2 and familial juvenile hyperuricaemic nephropathy T C Hart, M C Gorry, P S Hart, A S Woodard, Z Shihabi, J Sandhu, B Shirts, L Xu, H Zhu, M M Barmada, A J Bleyer ............................................................................................................................. J Med Genet 2002;39:882–892 Introduction: Medullary cystic kidney disease 2 (MCKD2) and familial juvenile hyperuricaemic neph- ropathy (FJHN) are both autosomal dominant renal diseases characterised by juvenile onset of hyper- uricaemia, gout, and progressive renal failure. Clinical features of both conditions vary in presence and severity. Often definitive diagnosis is possible only after significant pathology has occurred. Genetic linkage studies have localised genes for both conditions to overlapping regions of See end of article for chromosome 16p11-p13. These clinical and genetic findings suggest that these conditions may be authors’ affiliations ....................... allelic. Aim: To identify the gene and associated mutation(s) responsible for FJHN and MCKD2. Correspondence to: Methods: Two large, multigenerational families segregating FJHN were studied by genetic linkage Dr T C Hart, Center for Craniofacial and Dental and haplotype analyses to sublocalise the chromosome 16p FJHN gene locus. To permit refinement of Genetics, University of the candidate interval and localisation of candidate genes, an integrated physical and genetic map of Pittsburgh, School of Dental the candidate region was developed. DNA sequencing of candidate genes was performed to detect Medicine, 614 Salk Hall, mutations in subjects affected with FJHN (three unrelated families) and MCKD2 (one family). -
Genome-Wide Assessment of DNA Methylation in Mouse Oocytes Reveals Effects Associated with in Vitro Growth, Superovulation
Saenz-de-Juano et al. Clinical Epigenetics (2019) 11:197 https://doi.org/10.1186/s13148-019-0794-y RESEARCH Open Access Genome-wide assessment of DNA methylation in mouse oocytes reveals effects associated with in vitro growth, superovulation, and sexual maturity Maria Desemparats Saenz-de-Juano1,2, Elena Ivanova3, Katy Billooye1, Anamaria-Cristina Herta1, Johan Smitz1, Gavin Kelsey3,4 and Ellen Anckaert1* Abstract Background: In vitro follicle culture (IFC), as applied in the mouse system, allows the growth and maturation of a large number of immature preantral follicles to become mature and competent oocytes. In the human oncofertility clinic, there is increasing interest in developing this technique as an alternative to ovarian cortical tissue transplantation and to preserve the fertility of prepubertal cancer patients. However, the effect of IFC and hormonal stimulation on DNA methylation in the oocyte is not fully known, and there is legitimate concern over epigenetic abnormalities that could be induced by procedures applied during assisted reproductive technology (ART). Results: In this study, we present the first genome-wide analysis of DNA methylation in MII oocytes obtained after natural ovulation, after IFC and after superovulation. We also performed a comparison between prepubertal and adult hormonally stimulated oocytes. Globally, the distinctive methylation landscape of oocytes, comprising alternating hyper- and hypomethylated domains, is preserved irrespective of the procedure. The conservation of methylation extends to the germline differential methylated regions (DMRs) of imprinted genes, necessary for their monoallelic expression in the embryo. However, we do detect specific, consistent, and coherent differences in DNA methylation in IFC oocytes, and between oocytes obtained after superovulation from prepubertal compared with sexually mature females. -
Development of Novel Analysis and Data Integration Systems to Understand Human Gene Regulation
Development of novel analysis and data integration systems to understand human gene regulation Dissertation zur Erlangung des Doktorgrades Dr. rer. nat. der Fakult¨atf¨urMathematik und Informatik der Georg-August-Universit¨atG¨ottingen im PhD Programme in Computer Science (PCS) der Georg-August University School of Science (GAUSS) vorgelegt von Raza-Ur Rahman aus Pakistan G¨ottingen,April 2018 Prof. Dr. Stefan Bonn, Zentrum f¨urMolekulare Neurobiologie (ZMNH), Betreuungsausschuss: Institut f¨urMedizinische Systembiologie, Hamburg Prof. Dr. Tim Beißbarth, Institut f¨urMedizinische Statistik, Universit¨atsmedizin, Georg-August Universit¨at,G¨ottingen Prof. Dr. Burkhard Morgenstern, Institut f¨urMikrobiologie und Genetik Abtl. Bioinformatik, Georg-August Universit¨at,G¨ottingen Pr¨ufungskommission: Prof. Dr. Stefan Bonn, Zentrum f¨urMolekulare Neurobiologie (ZMNH), Referent: Institut f¨urMedizinische Systembiologie, Hamburg Prof. Dr. Tim Beißbarth, Institut f¨urMedizinische Statistik, Universit¨atsmedizin, Korreferent: Georg-August Universit¨at,G¨ottingen Prof. Dr. Burkhard Morgenstern, Weitere Mitglieder Institut f¨urMikrobiologie und Genetik Abtl. Bioinformatik, der Pr¨ufungskommission: Georg-August Universit¨at,G¨ottingen Prof. Dr. Carsten Damm, Institut f¨urInformatik, Georg-August Universit¨at,G¨ottingen Prof. Dr. Florentin W¨org¨otter, Physikalisches Institut Biophysik, Georg-August-Universit¨at,G¨ottingen Prof. Dr. Stephan Waack, Institut f¨urInformatik, Georg-August Universit¨at,G¨ottingen Tag der m¨undlichen Pr¨ufung: der 30. M¨arz2018