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Inducible Gene Expression: Diverse Regulatory Mechanisms
REVIEWS MODES OF TRANSCRIPTIONAL REGULATION Inducible gene expression: diverse regulatory mechanisms Vikki M. Weake and Jerry L. Workman Abstract | The rapid activation of gene expression in response to stimuli occurs largely through the regulation of RNA polymerase II‑dependent transcription. In this Review, we discuss events that occur during the transcription cycle in eukaryotes that are important for the rapid and specific activation of gene expression in response to external stimuli. In addition to regulated recruitment of the transcription machinery to the promoter, it has now been shown that control steps can include chromatin remodelling and the release of paused polymerase. Recent work suggests that some components of signal transduction cascades also play an integral part in activating transcription at target genes. Chromatin Cells must be able to rapidly respond to changes in RNA polymerase II (Pol II)‑dependent transcription. A nucleoprotein structure their external environment — such as temperature or Although a traditional model of activator‑dependent formed of repeating nutrient availability — to exploit and survive in new recruitment of Pol II and the general transcription nucleosomal units in which conditions. Even cells in a multicellular organism need factors (GTFs) holds true for many inducible genes, 147 base pairs of DNA are wrapped around an octamer of to respond to developmental cues such as signalling recent studies suggest that Pol II is already present and 1–6 histone proteins consisting molecules to determine when to divide, migrate or poised for transcription at many inducible genes . of an H3–H4 tetramer flanked die. The production of new proteins in response to Therefore, it is becoming increasingly apparent that by two H2A–H2B dimers external stimuli results largely from rapid activation there is an additional level of regulation that occurs of gene transcription — this is known as inducible during the initial stages of transcription elongation Co-activator A protein that is recruited to gene expression. -
Molecular and Physiological Basis for Hair Loss in Near Naked Hairless and Oak Ridge Rhino-Like Mouse Models: Tracking the Role of the Hairless Gene
University of Tennessee, Knoxville TRACE: Tennessee Research and Creative Exchange Doctoral Dissertations Graduate School 5-2006 Molecular and Physiological Basis for Hair Loss in Near Naked Hairless and Oak Ridge Rhino-like Mouse Models: Tracking the Role of the Hairless Gene Yutao Liu University of Tennessee - Knoxville Follow this and additional works at: https://trace.tennessee.edu/utk_graddiss Part of the Life Sciences Commons Recommended Citation Liu, Yutao, "Molecular and Physiological Basis for Hair Loss in Near Naked Hairless and Oak Ridge Rhino- like Mouse Models: Tracking the Role of the Hairless Gene. " PhD diss., University of Tennessee, 2006. https://trace.tennessee.edu/utk_graddiss/1824 This Dissertation is brought to you for free and open access by the Graduate School at TRACE: Tennessee Research and Creative Exchange. It has been accepted for inclusion in Doctoral Dissertations by an authorized administrator of TRACE: Tennessee Research and Creative Exchange. For more information, please contact [email protected]. To the Graduate Council: I am submitting herewith a dissertation written by Yutao Liu entitled "Molecular and Physiological Basis for Hair Loss in Near Naked Hairless and Oak Ridge Rhino-like Mouse Models: Tracking the Role of the Hairless Gene." I have examined the final electronic copy of this dissertation for form and content and recommend that it be accepted in partial fulfillment of the requirements for the degree of Doctor of Philosophy, with a major in Life Sciences. Brynn H. Voy, Major Professor We have read this dissertation and recommend its acceptance: Naima Moustaid-Moussa, Yisong Wang, Rogert Hettich Accepted for the Council: Carolyn R. -
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. -
Supplemental Materials ZNF281 Enhances Cardiac Reprogramming
Supplemental Materials ZNF281 enhances cardiac reprogramming by modulating cardiac and inflammatory gene expression Huanyu Zhou, Maria Gabriela Morales, Hisayuki Hashimoto, Matthew E. Dickson, Kunhua Song, Wenduo Ye, Min S. Kim, Hanspeter Niederstrasser, Zhaoning Wang, Beibei Chen, Bruce A. Posner, Rhonda Bassel-Duby and Eric N. Olson Supplemental Table 1; related to Figure 1. Supplemental Table 2; related to Figure 1. Supplemental Table 3; related to the “quantitative mRNA measurement” in Materials and Methods section. Supplemental Table 4; related to the “ChIP-seq, gene ontology and pathway analysis” and “RNA-seq” and gene ontology analysis” in Materials and Methods section. Supplemental Figure S1; related to Figure 1. Supplemental Figure S2; related to Figure 2. Supplemental Figure S3; related to Figure 3. Supplemental Figure S4; related to Figure 4. Supplemental Figure S5; related to Figure 6. Supplemental Table S1. Genes included in human retroviral ORF cDNA library. Gene Gene Gene Gene Gene Gene Gene Gene Symbol Symbol Symbol Symbol Symbol Symbol Symbol Symbol AATF BMP8A CEBPE CTNNB1 ESR2 GDF3 HOXA5 IL17D ADIPOQ BRPF1 CEBPG CUX1 ESRRA GDF6 HOXA6 IL17F ADNP BRPF3 CERS1 CX3CL1 ETS1 GIN1 HOXA7 IL18 AEBP1 BUD31 CERS2 CXCL10 ETS2 GLIS3 HOXB1 IL19 AFF4 C17ORF77 CERS4 CXCL11 ETV3 GMEB1 HOXB13 IL1A AHR C1QTNF4 CFL2 CXCL12 ETV7 GPBP1 HOXB5 IL1B AIMP1 C21ORF66 CHIA CXCL13 FAM3B GPER HOXB6 IL1F3 ALS2CR8 CBFA2T2 CIR1 CXCL14 FAM3D GPI HOXB7 IL1F5 ALX1 CBFA2T3 CITED1 CXCL16 FASLG GREM1 HOXB9 IL1F6 ARGFX CBFB CITED2 CXCL3 FBLN1 GREM2 HOXC4 IL1F7 -
A Genome-Wide Screen for Genes Affecting Spontaneous Direct-Repeat Recombination In
bioRxiv preprint doi: https://doi.org/10.1101/2020.02.11.943795; this version posted February 11, 2020. 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 A genome-wide screen for genes affecting spontaneous direct-repeat recombination in 2 Saccharomyces cerevisiae 3 4 5 Daniele Novarina*, Ridhdhi Desai†, Jessica A. Vaisica†, Jiongwen Ou†, Mohammed Bellaoui†,1, 6 Grant W. Brown†,2 and Michael Chang*,3 7 8 *European Research Institute for the Biology of Ageing, University of Groningen, University 9 Medical Center Groningen, 9713 AV Groningen, the Netherlands 10 †Department of Biochemistry and Donnelly Centre, University of Toronto, Toronto, ON M5S 11 3E1, Canada 12 13 1Current address: Genetics Unit, Faculty of Medicine and Pharmacy, University Mohammed 14 Premier, Oujda, Morocco 15 16 2Co-corresponding author: Department of Biochemistry and Donnelly Centre, University of 17 Toronto, 160 College Street, Toronto, ON M5S 3E1 Canada. E-mail: [email protected] 18 3Co-corresponding author: European Research Institute for the Biology of Ageing, University of 19 Groningen, University Medical Center Groningen, Antonius Deusinglaan 1, 9713 AV Groningen, 20 the Netherlands. E-mail: [email protected] 21 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.02.11.943795; this version posted February 11, 2020. 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. -
Bioinformatics Analyses of Genomic Imprinting
Bioinformatics Analyses of Genomic Imprinting Dissertation zur Erlangung des Grades des Doktors der Naturwissenschaften der Naturwissenschaftlich-Technischen Fakultät III Chemie, Pharmazie, Bio- und Werkstoffwissenschaften der Universität des Saarlandes von Barbara Hutter Saarbrücken 2009 Tag des Kolloquiums: 08.12.2009 Dekan: Prof. Dr.-Ing. Stefan Diebels Berichterstatter: Prof. Dr. Volkhard Helms Priv.-Doz. Dr. Martina Paulsen Vorsitz: Prof. Dr. Jörn Walter Akad. Mitarbeiter: Dr. Tihamér Geyer Table of contents Summary________________________________________________________________ I Zusammenfassung ________________________________________________________ I Acknowledgements _______________________________________________________II Abbreviations ___________________________________________________________ III Chapter 1 – Introduction __________________________________________________ 1 1.1 Important terms and concepts related to genomic imprinting __________________________ 2 1.2 CpG islands as regulatory elements ______________________________________________ 3 1.3 Differentially methylated regions and imprinting clusters_____________________________ 6 1.4 Reading the imprint __________________________________________________________ 8 1.5 Chromatin marks at imprinted regions___________________________________________ 10 1.6 Roles of repetitive elements ___________________________________________________ 12 1.7 Functional implications of imprinted genes _______________________________________ 14 1.8 Evolution and parental conflict ________________________________________________ -
Onc2010217.Pdf
Oncogene (2010) 29, 4671–4681 & 2010 Macmillan Publishers Limited All rights reserved 0950-9232/10 www.nature.com/onc ORIGINAL ARTICLE DEK oncoprotein regulates transcriptional modifiers and sustains tumor initiation activity in high-grade neuroendocrine carcinoma of the lung T Shibata1,2, A Kokubu1, M Miyamoto1, F Hosoda1, M Gotoh2, K Tsuta3, H Asamura4, Y Matsuno5, T Kondo6, I Imoto7,8, J Inazawa7,8 and S Hirohashi1,2 1Cancer Genomics Project, National Cancer Center Research Institute, Chuo-ku, Tokyo, Japan; 2Pathology Division, National Cancer Center Research Institute, Chuo-ku, Tokyo, Japan; 3Clinical Laboratory Division, National Cancer Center Hospital, Chuo-ku, Tokyo, Japan; 4Division of Thoracic Surgery, National Cancer Center Hospital, Chuo-ku, Tokyo, Japan; 5Department of Surgical Pathology, Hokkaido University Hospital, Sapporo, Hokkaido, Japan; 6Proteome Bioinfomatics Project, National Cancer Center Research Institute, Chuo-ku, Tokyo, Japan; 7Department of Molecular Cytogenetics, Medical Research Institute and Graduate School of Biomedical Science, Tokyo Medical and Dental University, Tokyo, Japan and 8Center of Excellence Program for Frontier Research on Molecular Destruction and Reconstitution of Tooth and Bone, Tokyo Medical and Dental University, Tokyo, Japan Lung cancer shows diverse histological subtypes. Large- Introduction cell neuroendocrine cell carcinoma and small-cell lung carcinoma show similar histological features and clinical Lung cancer is one of the most prevalent cancers behaviors, and can be classified as high-grade neuro- worldwide, and shows diverse histological subtypes, endocrine carcinoma (HGNEC) of the lung. Here we including adenocarcinoma, squamous cell carcinoma, elucidated the molecular classification of pulmonary large-cell carcinoma, large-cell neuroendocrine carcino- endocrine tumors by copy-number profiling. We compared ma (LCNEC) and small-cell lung carcinoma (SCLC; alterations of copy number with the clinical outcome of Travis and Brambilla, 2004). -
SUPPLEMENTARY MATERIAL Bone Morphogenetic Protein 4 Promotes
www.intjdevbiol.com doi: 10.1387/ijdb.160040mk SUPPLEMENTARY MATERIAL corresponding to: Bone morphogenetic protein 4 promotes craniofacial neural crest induction from human pluripotent stem cells SUMIYO MIMURA, MIKA SUGA, KAORI OKADA, MASAKI KINEHARA, HIROKI NIKAWA and MIHO K. FURUE* *Address correspondence to: Miho Kusuda Furue. Laboratory of Stem Cell Cultures, National Institutes of Biomedical Innovation, Health and Nutrition, 7-6-8, Saito-Asagi, Ibaraki, Osaka 567-0085, Japan. Tel: 81-72-641-9819. Fax: 81-72-641-9812. E-mail: [email protected] Full text for this paper is available at: http://dx.doi.org/10.1387/ijdb.160040mk TABLE S1 PRIMER LIST FOR QRT-PCR Gene forward reverse AP2α AATTTCTCAACCGACAACATT ATCTGTTTTGTAGCCAGGAGC CDX2 CTGGAGCTGGAGAAGGAGTTTC ATTTTAACCTGCCTCTCAGAGAGC DLX1 AGTTTGCAGTTGCAGGCTTT CCCTGCTTCATCAGCTTCTT FOXD3 CAGCGGTTCGGCGGGAGG TGAGTGAGAGGTTGTGGCGGATG GAPDH CAAAGTTGTCATGGATGACC CCATGGAGAAGGCTGGGG MSX1 GGATCAGACTTCGGAGAGTGAACT GCCTTCCCTTTAACCCTCACA NANOG TGAACCTCAGCTACAAACAG TGGTGGTAGGAAGAGTAAAG OCT4 GACAGGGGGAGGGGAGGAGCTAGG CTTCCCTCCAACCAGTTGCCCCAAA PAX3 TTGCAATGGCCTCTCAC AGGGGAGAGCGCGTAATC PAX6 GTCCATCTTTGCTTGGGAAA TAGCCAGGTTGCGAAGAACT p75 TCATCCCTGTCTATTGCTCCA TGTTCTGCTTGCAGCTGTTC SOX9 AATGGAGCAGCGAAATCAAC CAGAGAGATTTAGCACACTGATC SOX10 GACCAGTACCCGCACCTG CGCTTGTCACTTTCGTTCAG Suppl. Fig. S1. Comparison of the gene expression profiles of the ES cells and the cells induced by NC and NC-B condition. Scatter plots compares the normalized expression of every gene on the array (refer to Table S3). The central line -
Genetic Analysis of the Hsm3 Protein Function in Yeast Saccharomyces Cerevisiae Nub4 Complex
G C A T T A C G G C A T genes Article Genetic Analysis of the Hsm3 Protein Function in Yeast Saccharomyces cerevisiae NuB4 Complex Tatiyana A. Evstyukhina 1,2, Elena A. Alekseeva 1,2,* , Dmitriy V. Fedorov 1, Vyacheslav T. Peshekhonov 1,2 and Vladimir G. Korolev 1,2 1 Laboratory of Eukaryotic Genetics, Department of Molecular and Radiation Biophysics, Petersburg Nuclear Physics Institute Named by B.P. Konstantinov of National Research Centre “Kurchatov Institute”, 188300 Gatchina, Russia; [email protected] (T.A.E.); [email protected] (D.V.F.); [email protected] (V.T.P.); [email protected] (V.G.K.) 2 Laboratory of Molecular Genetic and Recombination Technologies, Kurchatov Genome Center— Petersburg Nuclear Physics Institute, mkr. Orlova Roscha 1, Leningrad District, 188300 Gatchina, Russia * Correspondence: [email protected] Abstract: In the nuclear compartment of yeast, NuB4 core complex consists of three proteins, Hat1, Hat2, and Hif1, and interacts with a number of other factors. In particular, it was shown that NuB4 complex physically interacts with Hsm3p. Early we demonstrated that the gene HSM3 participates in the control of replicative and reparative spontaneous mutagenesis, and that hsm3D mutants increase the frequency of mutations induced by different mutagens. It was previously believed that the HSM3 gene controlled only some minor repair processes in the cell, but later it was suggested that it had a chaperone function with its participation in proteasome assembly. In this work, we analyzed the properties of three hsm3D, hif1D, and hat1D mutants. The results obtained showed that the Citation: Evstyukhina, T.A.; Hsm3 protein may be a functional subunit of NuB4 complex. -
Functional Link Between Mitochondria and Rnr3, the Minor Catalytic Subunit of Yeast Ribonucleotide Reductase
Research Article www.microbialcell.com Functional link between mitochondria and Rnr3, the minor catalytic subunit of yeast ribonucleotide reductase Isaac Corcoles-Saez1, Jean-Luc Ferat2, Michael Costanzo3, Charles M. Boone3 and Rita S. Cha1,* 1 School of Medical Sciences, North West Cancer Research Institute, Bangor University, Deniol Road, Bangor, LL57 2UW, United Kingdom. 2 Institute of Integrative Biology of the Cell (I2BC), Avenue de la Terrasse, Paris, France. 3 University of Toronto, Donnelly Centre, 160 College Street, Toronto, Ontario, M5S 3E1, Canada.. * Corresponding Author: Rita S. Cha, Tel: +44 (0)1248 38286; E-mail: [email protected] ABSTRACT Ribonucleotide reductase (RNR) is an essential holoenzyme re- doi: 10.15698/mic2019.06.680 quired for de novo synthesis of dNTPs. The Saccharomyces cerevisiae genome Received originally: 24.12.2019; encodes for two catalytic subunits, Rnr1 and Rnr3. While Rnr1 is required for in revised form: 09.05.2019, DNA replication and DNA damage repair, the function(s) of Rnr3 is unknown. Accepted 13.05.2019, Published 20.05.2019. Here, we show that carbon source, an essential nutrient, impacts Rnr1 and Rnr3 abundance: Non-fermentable carbon sources or limiting concentrations of glucose down regulate Rnr1 and induce Rnr3 expression. Oppositely, abun- Keywords: Rnr1, Rnr3, Mec1, carbon dant glucose induces Rnr1 expression and down regulates Rnr3. The carbon source, respiration, mitochondria, source dependent regulation of Rnr3 is mediated by Mec1, the budding yeast dNTP. ATM/ATR checkpoint response kinase. Unexpectedly, this regulation is inde- pendent of all currently known components of the Mec1 DNA damage re- Abbreviations: sponse network, including Rad53, Dun1, and Tel1, implicating a novel Mec1 DDR – DNA damage response, signalling axis. -
Coding RNA Genes
Review A guide to naming human non-coding RNA genes Ruth L Seal1,2,* , Ling-Ling Chen3, Sam Griffiths-Jones4, Todd M Lowe5, Michael B Mathews6, Dawn O’Reilly7, Andrew J Pierce8, Peter F Stadler9,10,11,12,13, Igor Ulitsky14 , Sandra L Wolin15 & Elspeth A Bruford1,2 Abstract working on non-coding RNA (ncRNA) nomenclature in the mid- 1980s with the approval of initial gene symbols for mitochondrial Research on non-coding RNA (ncRNA) is a rapidly expanding field. transfer RNA (tRNA) genes. Since then, we have worked closely Providing an official gene symbol and name to ncRNA genes brings with experts in the ncRNA field to develop symbols for many dif- order to otherwise potential chaos as it allows unambiguous ferent kinds of ncRNA genes. communication about each gene. The HUGO Gene Nomenclature The number of genes that the HGNC has named per ncRNA class Committee (HGNC, www.genenames.org) is the only group with is shown in Fig 1, and ranges in number from over 4,500 long the authority to approve symbols for human genes. The HGNC ncRNA (lncRNA) genes and over 1,900 microRNA genes, to just four works with specialist advisors for different classes of ncRNA to genes in the vault and Y RNA classes. Every gene symbol has a ensure that ncRNA nomenclature is accurate and informative, Symbol Report on our website, www.genenames.org, which where possible. Here, we review each major class of ncRNA that is displays the gene symbol, gene name, chromosomal location and currently annotated in the human genome and describe how each also includes links to key resources such as Ensembl (Zerbino et al, class is assigned a standardised nomenclature. -
Dependent Protein Kinase to Cyclic CMP Agarose
Binding of Regulatory Subunits of Cyclic AMP- Dependent Protein Kinase to Cyclic CMP Agarose Andreas Hammerschmidt1., Bijon Chatterji2., Johannes Zeiser2, Anke Schro¨ der2, Hans- Gottfried Genieser3, Andreas Pich2, Volkhard Kaever1, Frank Schwede3, Sabine Wolter1", Roland Seifert1*" 1 Institute of Pharmacology, Hannover Medical School, Hannover, Germany, 2 Institute of Toxicology, Hannover Medical School, Hannover, Germany, 3 Biolog Life Science Institute, Bremen, Germany Abstract The bacterial adenylyl cyclase toxins CyaA from Bordetella pertussis and edema factor from Bacillus anthracis as well as soluble guanylyl cyclase a1b1 synthesize the cyclic pyrimidine nucleotide cCMP. These data raise the question to which effector proteins cCMP binds. Recently, we reported that cCMP activates the regulatory subunits RIa and RIIa of cAMP- dependent protein kinase. In this study, we used two cCMP agarose matrices as novel tools in combination with immunoblotting and mass spectrometry to identify cCMP-binding proteins. In agreement with our functional data, RIa and RIIa were identified as cCMP-binding proteins. These data corroborate the notion that cAMP-dependent protein kinase may serve as a cCMP target. Citation: Hammerschmidt A, Chatterji B, Zeiser J, Schro¨der A, Genieser H-G, et al. (2012) Binding of Regulatory Subunits of Cyclic AMP-Dependent Protein Kinase to Cyclic CMP Agarose. PLoS ONE 7(7): e39848. doi:10.1371/journal.pone.0039848 Editor: Andreas Hofmann, Griffith University, Australia Received May 11, 2012; Accepted May 31, 2012; Published July 9, 2012 Copyright: ß 2012 Hammerschmidt et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.