Novel Bioinformatics Approaches for Microrna Detection and Target Prediction

Total Page:16

File Type:pdf, Size:1020Kb

Novel Bioinformatics Approaches for Microrna Detection and Target Prediction Novel Bioinformatics Approaches for MicroRNA Detection and Target Prediction by Subramanian Shankar Ajay A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Bioinformatics) in The University of Michigan 2009 Doctoral committee: Professor Brian D. Athey, Co-Chair Research Investigator Inhan Lee, Co-Chair Professor Daniel M. Burns Jr. Assistant Professor Zhaohui Qin Professor David J. States, University of Texas Health Sciences Center at Houston To amma, appa and panni ii Acknowledgements I would like to show my immense gratitude to Prof. Brian Athey and Dr. Inhan Lee who took me under their wings when I first joined the Bioinformatics doctoral degree program. Their enthusiasm has been so infectious that I derived confidence from it every time I interacted with them. They have been a pillar of knowledge and support during the course of my graduate studies. Their ideas have helped shape this thesis to a large extent and I am grateful to them for the encouragement that they continued to provide along every step of the way. I would like to thank Prof. David States for his invaluable inputs and discussions. The influence his pedagogical role has had in the first few years cannot be emphasized enough. Many thanks are also due to my doctoral committee members, Dr. Zhaohui Qin and Prof. Daniel Burns, for all their help when I turned to them. I have had the pleasure of learning bioinformatics methods and concepts under their tutelage. I really appreciate the fresh perspectives that Dr. Jeffrey DeWet lent when I had a tough time sorting out scientific problems, especially with respect to experiments. The extremely resourceful Bioinformatics graduate program staff, Alicia, Yuri, Julia, Sandy and Janet have helped make my transition and stay in the program facile. Much of the work in this thesis would not have been possible without the support from laboratories of Dr. Arul Chinnaiyan from the Department of Pathology at the iii University of Michigan, Dr. Haiming Chen from the Department of Psychiatry at the University of Michigan and Dr. JongIn Yook at Yonsei University. I am thankful to members of Dr. Chinnaiyan’s group, Mohan, Bharathy and Anju who have taught me experimental techniques, from using a pipette to cell transfections. Outside the scientific community some people have had an immeasurable impact in my life. The unconditional love and support (and money) from my family has seen me through highs and lows. The friends I’ve made through college and graduate school are ones I’ll forever stand by - the spasmers from BITS to the ommalites in Ann Arbor, among whom Jaggi and Sweta deserve a special mention for everything they’ve helped me with. Work would not have been as much fun without k2 and uthra, and lunches would not have been as entertaining without the discussions on everything from politics to movies with my colleagues at Green Court. I thank them all. iv Table of Contents Dedication........................................................................................................................... ii Acknowledgements............................................................................................................iii List of Figures..................................................................................................................viii List of Tables ..................................................................................................................... ix List of Appendices ..............................................................................................................x Chapter 1............................................................................................................................. 1 Introduction......................................................................................................................... 1 1.1 Post-transcriptional gene regulation ...................................................................... 2 1.2 Introduction to microRNAs ................................................................................... 3 1.2.1 MicroRNA biogenesis................................................................................. 4 1.2.2 Mechanisms of miRNA-mediated repression ............................................. 6 1.3 Nearest-neighbour thermodynamics...................................................................... 7 1.4 Problem Statement............................................................................................... 10 1.4.1 Detection of miRNA expression ............................................................... 11 1.4.2 Computational miRNA target prediction in animals................................. 13 1.5 Contributions ....................................................................................................... 15 1.5.1 Target-specific microarray probe design................................................... 15 1.5.2 Discovery of endogenous 5′-UTR target sites........................................... 16 1.6 Thesis Outline...................................................................................................... 18 Chapter 2........................................................................................................................... 19 Microarray probe design for miRNAs .............................................................................. 19 2.1 Background.......................................................................................................... 19 2.2 Computational Methods....................................................................................... 21 2.2.1 Base change strategy ................................................................................. 21 2.2.1 ProDeG algorithm ..................................................................................... 21 2.3 Computational Results......................................................................................... 24 2.3.1 Variance of Tm by introducing mismatches............................................... 24 2.3.2 ProDeG probes for human miRNA cDNAs .............................................. 25 2.3.3 Characteristics of ProDeG probes for cDNA of human miRNAs............. 26 2.3.4 ProDeG probes for RNA samples of human miRNAs.............................. 26 v 2.4 Experimental validation – Methods..................................................................... 27 2.4.1 Microarray platform .................................................................................. 27 2.4.2 let-7 family spiked-in experiments............................................................ 27 2.4.3 Hybridization experiment using lymphoblastoid cell-line small RNA ..... 28 2.4.5 Quantitative RT-PCR ................................................................................ 30 2.5 Experimental validation – Results....................................................................... 31 2.5.1 Verification of ProDeG cDNA probe specificity using let-7 spike-in experiments......................................................................................................... 31 2.5.2 Expression signals of ProDeG let-7 probes from human lymphoblastoid cell lines.............................................................................................................. 32 2.6 Discussion............................................................................................................ 33 Chapter 3........................................................................................................................... 47 Discovery of endogenous 5′-UTR miRNA target sites..................................................... 47 3.1 Background.......................................................................................................... 47 3.2 Results.................................................................................................................. 49 3.2.1 Presence of miRNA interaction sites in human 5′-UTR ........................... 49 3.2.2 hsa-miR-34a targets AXIN2 through both UTRs....................................... 50 3.2.3 Modified cel-lin-4 targets both lin28 UTRs .............................................. 52 3.3 Methods ............................................................................................................... 53 3.3.1 Bioinformatics and statistical analysis ...................................................... 53 3.3.2 Experimental validation – AXIN2 and hsa-miR-34a................................. 54 3.3.3 Experimental validation – LIN28 and lin-4 siRNA .................................. 55 3.4 Discussion............................................................................................................ 57 Chapter 4........................................................................................................................... 65 Post-transcriptional regulation by miRNA binding of uAUGs......................................... 65 4.1 Background.......................................................................................................... 65 4.2 Methods ............................................................................................................... 67 4.2.1 uAUG and miRNA sequence data............................................................. 67 4.2.2 Sequence complementarity search ............................................................ 68 4.2.3 miRNA expression data............................................................................
Recommended publications
  • Wo 2010/075007 A2
    (12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization International Bureau (10) International Publication Number (43) International Publication Date 1 July 2010 (01.07.2010) WO 2010/075007 A2 (51) International Patent Classification: (81) Designated States (unless otherwise indicated, for every C12Q 1/68 (2006.01) G06F 19/00 (2006.01) kind of national protection available): AE, AG, AL, AM, C12N 15/12 (2006.01) AO, AT, AU, AZ, BA, BB, BG, BH, BR, BW, BY, BZ, CA, CH, CL, CN, CO, CR, CU, CZ, DE, DK, DM, DO, (21) International Application Number: DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, PCT/US2009/067757 HN, HR, HU, ID, IL, IN, IS, JP, KE, KG, KM, KN, KP, (22) International Filing Date: KR, KZ, LA, LC, LK, LR, LS, LT, LU, LY, MA, MD, 11 December 2009 ( 11.12.2009) ME, MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, OM, PE, PG, PH, PL, PT, RO, RS, RU, SC, SD, (25) Filing Language: English SE, SG, SK, SL, SM, ST, SV, SY, TJ, TM, TN, TR, TT, (26) Publication Language: English TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW. (30) Priority Data: (84) Designated States (unless otherwise indicated, for every 12/3 16,877 16 December 2008 (16.12.2008) US kind of regional protection available): ARIPO (BW, GH, GM, KE, LS, MW, MZ, NA, SD, SL, SZ, TZ, UG, ZM, (71) Applicant (for all designated States except US): DODDS, ZW), Eurasian (AM, AZ, BY, KG, KZ, MD, RU, TJ, W., Jean [US/US]; 938 Stanford Street, Santa Monica, TM), European (AT, BE, BG, CH, CY, CZ, DE, DK, EE, CA 90403 (US).
    [Show full text]
  • Cooperative Gene Regulation by Microrna Pairs and Their
    Published online 29 May 2014 Nucleic Acids Research, 2014, Vol. 42, No. 12 7539–7552 doi: 10.1093/nar/gku465 Cooperative gene regulation by microRNA pairs and their identification using a computational workflow Ulf Schmitz1,*, Xin Lai2, Felix Winter1, Olaf Wolkenhauer1,3, Julio Vera2 and Shailendra K. Gupta1,4 Downloaded from 1Department of Systems Biology and Bioinformatics, University of Rostock, Rostock, Germany, 2Laboratory of Systems Tumor Immunology, Department of Dermatology, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nuremberg, Germany, 3Stellenbosch Institute for Advanced Study (STIAS), Wallenberg Research Centre at Stellenbosch University, Stellenbosch, South Africa and 4Department of Bioinformatics, CSIR-Indian Institute of Toxicology Research, 226001 Lucknow, Uttar Pradesh, India http://nar.oxfordjournals.org/ Received December 22, 2013; Revised April 18, 2014; Accepted May 10, 2014 ABSTRACT fine-tuned through a cellular context-dependent regulation by multiple miRNAs, where miRNAs can either induce MicroRNAs (miRNAs) are an integral part of gene reg- translational repression or target mRNA degradation (4). ulation at the post-transcriptional level. Recently, it Thereby, the miRNA-target regulation machinery can real- at Universitaet Erlangen-Nuernberg, Wirtschafts- und Sozialwissenschaftliche Z on August 3, 2016 has been shown that pairs of miRNAs can repress the ize elaborate gene control functions, including noise buffer- translation of a target mRNA in a cooperative man- ing or homeostasis, and can ultimately mediate distinct tar- ner, which leads to an enhanced effectiveness and get expression patterns appropriate to the demand of differ- specificity in target repression. However, it remains ent biological processes (3,5,6). However, deregulated miR- unclear which miRNA pairs can synergize and which NAs have also been associated with the pathogenesis and genes are target of cooperative miRNA regulation.
    [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]
  • Exploring Prostate Cancer Genome Reveals Simultaneous Losses of PTEN, FAS and PAPSS2 in Patients with PSA Recurrence After Radical Prostatectomy
    Int. J. Mol. Sci. 2015, 16, 3856-3869; doi:10.3390/ijms16023856 OPEN ACCESS International Journal of Molecular Sciences ISSN 1422-0067 www.mdpi.com/journal/ijms Article Exploring Prostate Cancer Genome Reveals Simultaneous Losses of PTEN, FAS and PAPSS2 in Patients with PSA Recurrence after Radical Prostatectomy Chinyere Ibeawuchi 1, Hartmut Schmidt 2, Reinhard Voss 3, Ulf Titze 4, Mahmoud Abbas 5, Joerg Neumann 6, Elke Eltze 7, Agnes Marije Hoogland 8, Guido Jenster 9, Burkhard Brandt 10 and Axel Semjonow 1,* 1 Prostate Center, Department of Urology, University Hospital Muenster, Albert-Schweitzer-Campus 1, Gebaeude 1A, Muenster D-48149, Germany; E-Mail: [email protected] 2 Center for Laboratory Medicine, University Hospital Muenster, Albert-Schweitzer-Campus 1, Gebaeude 1A, Muenster D-48149, Germany; E-Mail: [email protected] 3 Interdisciplinary Center for Clinical Research, University of Muenster, Albert-Schweitzer-Campus 1, Gebaeude D3, Domagkstrasse 3, Muenster D-48149, Germany; E-Mail: [email protected] 4 Pathology, Lippe Hospital Detmold, Röntgenstrasse 18, Detmold D-32756, Germany; E-Mail: [email protected] 5 Institute of Pathology, Mathias-Spital-Rheine, Frankenburg Street 31, Rheine D-48431, Germany; E-Mail: [email protected] 6 Institute of Pathology, Klinikum Osnabrueck, Am Finkenhuegel 1, Osnabrueck D-49076, Germany; E-Mail: [email protected] 7 Institute of Pathology, Saarbrücken-Rastpfuhl, Rheinstrasse 2, Saarbrücken D-66113, Germany; E-Mail: [email protected] 8 Department
    [Show full text]
  • INPP5A Monoclonal Antibody (M05), Clone 3D8
    INPP5A monoclonal antibody (M05), clone 3D8 Catalog # : H00003632-M05 規格 : [ 100 ug ] List All Specification Application Image Product Mouse monoclonal antibody raised against a partial recombinant Western Blot (Recombinant protein) Description: INPP5A. Immunoprecipitation Immunogen: INPP5A (NP_005530, 288 a.a. ~ 387 a.a) partial recombinant protein with GST tag. MW of the GST tag alone is 26 KDa. Sequence: YFNQEVFRDNNGTALLEFDKELSVFKDRLYELDISFPPSYPYSEDARQG EQYMNTRCPAWCDRILMSPSAKELVLRVSVCCPSPGHRGMWSAGSGL AQPW enlarge Host: Mouse Sandwich ELISA (Recombinant Reactivity: Human protein) Isotype: IgG2a Kappa Quality Control Antibody Reactive Against Recombinant Protein. Testing: enlarge ELISA Western Blot detection against Immunogen (36.74 KDa) . Storage Buffer: In 1x PBS, pH 7.4 Storage Store at -20°C or lower. Aliquot to avoid repeated freezing and thawing. Instruction: MSDS: Download Datasheet: Download Applications Western Blot (Recombinant protein) Protocol Download Immunoprecipitation Page 1 of 3 2016/5/21 Immunoprecipitation of INPP5A transfected lysate using anti-INPP5A monoclonal antibody and Protein A Magnetic Bead (U0007), and immunoblotted with INPP5A MaxPab rabbit polyclonal antibody. Protocol Download Sandwich ELISA (Recombinant protein) Detection limit for recombinant GST tagged INPP5A is 0.1 ng/ml as a capture antibody. Protocol Download ELISA Gene Information Entrez GeneID: 3632 GeneBank NM_005539 Accession#: Protein NP_005530 Accession#: Gene Name: INPP5A Gene Alias: 5PTASE,DKFZp434A1721,MGC116947,MGC116949 Gene inositol polyphosphate-5-phosphatase, 40kDa Description: Omim ID: 600106 Gene Ontology: Hyperlink Gene Summary: The protein encoded by this gene is a membrane-associated type I inositol 1,4,5-trisphosphate (InsP3) 5-phosphatase. InsP3 5- phosphatases hydrolyze Ins(1,4,5)P3, which mobilizes intracellular calcium and acts as a second messenger mediating cell responses to various stimulation.
    [Show full text]
  • Endoglin Protein Interactome Profiling Identifies TRIM21 and Galectin-3 As
    cells Article Endoglin Protein Interactome Profiling Identifies TRIM21 and Galectin-3 as New Binding Partners 1, 1, 2, Eunate Gallardo-Vara y, Lidia Ruiz-Llorente y, Juan Casado-Vela y , 3 4 5 6, , María J. Ruiz-Rodríguez , Natalia López-Andrés , Asit K. Pattnaik , Miguel Quintanilla z * 1, , and Carmelo Bernabeu z * 1 Centro de Investigaciones Biológicas, Consejo Superior de Investigaciones Científicas (CSIC), and Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), 28040 Madrid, Spain; [email protected] (E.G.-V.); [email protected] (L.R.-L.) 2 Bioengineering and Aerospace Engineering Department, Universidad Carlos III and Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas (CIBERNED), Leganés, 28911 Madrid, Spain; [email protected] 3 Centro Nacional de Investigaciones Cardiovasculares (CNIC), 28029 Madrid, Spain; [email protected] 4 Cardiovascular Translational Research, Navarrabiomed, Complejo Hospitalario de Navarra (CHN), Universidad Pública de Navarra (UPNA), IdiSNA, 31008 Pamplona, Spain; [email protected] 5 School of Veterinary Medicine and Biomedical Sciences, and Nebraska Center for Virology, University of Nebraska-Lincoln, Lincoln, NE 68583, USA; [email protected] 6 Instituto de Investigaciones Biomédicas “Alberto Sols”, Consejo Superior de Investigaciones Científicas (CSIC), and Departamento de Bioquímica, Universidad Autónoma de Madrid (UAM), 28029 Madrid, Spain * Correspondence: [email protected] (M.Q.); [email protected] (C.B.) These authors contributed equally to this work. y Equal senior contribution. z Received: 7 August 2019; Accepted: 7 September 2019; Published: 13 September 2019 Abstract: Endoglin is a 180-kDa glycoprotein receptor primarily expressed by the vascular endothelium and involved in cardiovascular disease and cancer.
    [Show full text]
  • Genetic and Genomic Analysis of Hyperlipidemia, Obesity and Diabetes Using (C57BL/6J × TALLYHO/Jngj) F2 Mice
    University of Tennessee, Knoxville TRACE: Tennessee Research and Creative Exchange Nutrition Publications and Other Works Nutrition 12-19-2010 Genetic and genomic analysis of hyperlipidemia, obesity and diabetes using (C57BL/6J × TALLYHO/JngJ) F2 mice Taryn P. Stewart Marshall University Hyoung Y. Kim University of Tennessee - Knoxville, [email protected] Arnold M. Saxton University of Tennessee - Knoxville, [email protected] Jung H. Kim Marshall University Follow this and additional works at: https://trace.tennessee.edu/utk_nutrpubs Part of the Animal Sciences Commons, and the Nutrition Commons Recommended Citation BMC Genomics 2010, 11:713 doi:10.1186/1471-2164-11-713 This Article is brought to you for free and open access by the Nutrition at TRACE: Tennessee Research and Creative Exchange. It has been accepted for inclusion in Nutrition Publications and Other Works by an authorized administrator of TRACE: Tennessee Research and Creative Exchange. For more information, please contact [email protected]. Stewart et al. BMC Genomics 2010, 11:713 http://www.biomedcentral.com/1471-2164/11/713 RESEARCH ARTICLE Open Access Genetic and genomic analysis of hyperlipidemia, obesity and diabetes using (C57BL/6J × TALLYHO/JngJ) F2 mice Taryn P Stewart1, Hyoung Yon Kim2, Arnold M Saxton3, Jung Han Kim1* Abstract Background: Type 2 diabetes (T2D) is the most common form of diabetes in humans and is closely associated with dyslipidemia and obesity that magnifies the mortality and morbidity related to T2D. The genetic contribution to human T2D and related metabolic disorders is evident, and mostly follows polygenic inheritance. The TALLYHO/ JngJ (TH) mice are a polygenic model for T2D characterized by obesity, hyperinsulinemia, impaired glucose uptake and tolerance, hyperlipidemia, and hyperglycemia.
    [Show full text]
  • HNRPH1 (HNRNPH1) (NM 005520) 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 RC201834 HNRPH1 (HNRNPH1) (NM_005520) Human Tagged ORF Clone Product data: Product Type: Expression Plasmids Product Name: HNRPH1 (HNRNPH1) (NM_005520) Human Tagged ORF Clone Tag: Myc-DDK Symbol: HNRNPH1 Synonyms: hnRNPH; HNRPH; HNRPH1 Vector: pCMV6-Entry (PS100001) E. coli Selection: Kanamycin (25 ug/mL) Cell Selection: Neomycin 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 / 6 HNRPH1 (HNRNPH1) (NM_005520) Human Tagged ORF Clone – RC201834 ORF Nucleotide >RC201834 ORF sequence Sequence: Red=Cloning site Blue=ORF Green=Tags(s) TTTTGTAATACGACTCACTATAGGGCGGCCGGGAATTCGTCGACTGGATCCGGTACCGAGGAGATCTGCC GCCGCGATCGCC ATGATGTTGGGCACGGAAGGTGGAGAGGGATTCGTGGTGAAGGTCCGGGGCTTGCCCTGGTCTTGCTCGG CCGATGAAGTGCAGAGGTTTTTTTCTGACTGCAAAATTCAAAATGGGGCTCAAGGTATTCGTTTCATCTA CACCAGAGAAGGCAGACCAAGTGGCGAGGCTTTTGTTGAACTTGAATCAGAAGATGAAGTCAAATTGGCC CTGAAAAAAGACAGAGAAACTATGGGACACAGATATGTTGAAGTATTCAAGTCAAACAACGTTGAAATGG ATTGGGTGTTGAAGCATACTGGTCCAAATAGTCCTGACACGGCCAATGATGGCTTTGTACGGCTTAGAGG ACTTCCCTTTGGATGTAGCAAGGAAGAAATTGTTCAGTTCTTCTCAGGGTTGGAAATCGTGCCAAATGGG ATAACATTGCCGGTGGACTTCCAGGGGAGGAGTACGGGGGAGGCCTTCGTGCAGTTTGCTTCACAGGAAA TAGCTGAAAAGGCTCTAAAGAAACACAAGGAAAGAATAGGGCACAGGTATATTGAAATCTTTAAGAGCAG TAGAGCTGAAGTTAGAACTCATTATGATCCACCACGAAAGCTTATGGCCATGCAGCGGCCAGGTCCTTAT
    [Show full text]
  • Androgen Receptor Binding Sites Identified by a GREF GATA Model
    doi:10.1016/j.jmb.2005.09.009 J. Mol. Biol. (2005) 353, 763–771 COMMUNICATION Androgen Receptor Binding Sites Identified by a GREF_GATA Model Katsuaki Masuda1, Thomas Werner2, Shilpi Maheshwari1 Matthias Frisch2, Soyon Oh1, Gyorgy Petrovics1, Klaus May2 Vasantha Srikantan1, Shiv Srivastava1 and Albert Dobi1* 1Center for Prostate Disease Changes in transcriptional regulation can be permissive for tumor Research, Department of progression by allowing for selective growth advantage of tumor cells. Surgery, Uniformed Services Tumor suppressors can effectively inhibit this process. The PMEPA1 gene, a University, Rockville, MD potent inhibitor of prostate cancer cell growth is an androgen-regulated 20852, USA gene. We addressed the question of whether or not androgen receptor can directly bind to specific PMEPA1 promoter upstream sequences. To test this 2Genomatix Software GmbH hypothesis we extended in silico prediction of androgen receptor binding D-80339 Munich, Germany sites by a modeling approach and verified the actual binding by in vivo chromatin immunoprecipitation assay. Promoter upstream sequences of highly androgen-inducible genes were examined from microarray data of prostate cancer cells for transcription factor binding sites (TFBSs). Results were analyzed to formulate a model for the description of specific androgen receptor binding site context in these sequences. In silico analysis and subsequent experimental verification of the selected sequences suggested that a model that combined a GREF and a GATA TFBS was sufficient for predicting a class of functional androgen receptor binding sites. The GREF matrix family represents androgen receptor, glucocorticoid receptor and progesterone receptor binding sites and the GATA matrix family represents GATA binding protein 1–6 binding sites.
    [Show full text]
  • Snapshot: the Splicing Regulatory Machinery Mathieu Gabut, Sidharth Chaudhry, and Benjamin J
    192 Cell SnapShot: The Splicing Regulatory Machinery Mathieu Gabut, Sidharth Chaudhry, and Benjamin J. Blencowe 133 Banting and Best Department of Medical Research, University of Toronto, Toronto, ON M5S 3E1, Canada Expression in mouse , April4, 2008©2008Elsevier Inc. Low High Name Other Names Protein Domains Binding Sites Target Genes/Mouse Phenotypes/Disease Associations Amy Ceb Hip Hyp OB Eye SC BM Bo Ht SM Epd Kd Liv Lu Pan Pla Pro Sto Spl Thy Thd Te Ut Ov E6.5 E8.5 E10.5 SRp20 Sfrs3, X16 RRM, RS GCUCCUCUUC SRp20, CT/CGRP; −/− early embryonic lethal E3.5 9G8 Sfrs7 RRM, RS, C2HC Znf (GAC)n Tau, GnRH, 9G8 ASF/SF2 Sfrs1 RRM, RS RGAAGAAC HipK3, CaMKIIδ, HIV RNAs; −/− embryonic lethal, cond. KO cardiomyopathy SC35 Sfrs2 RRM, RS UGCUGUU AChE; −/− embryonic lethal, cond. KO deficient T-cell maturation, cardiomyopathy; LS SRp30c Sfrs9 RRM, RS CUGGAUU Glucocorticoid receptor SRp38 Fusip1, Nssr RRM, RS ACAAAGACAA CREB, type II and type XI collagens SRp40 Sfrs5, HRS RRM, RS AGGAGAAGGGA HipK3, PKCβ-II, Fibronectin SRp55 Sfrs6 RRM, RS GGCAGCACCUG cTnT, CD44 DOI 10.1016/j.cell.2008.03.010 SRp75 Sfrs4 RRM, RS GAAGGA FN1, E1A, CD45; overexpression enhances chondrogenic differentiation Tra2α Tra2a RRM, RS GAAARGARR GnRH; overexpression promotes RA-induced neural differentiation SR and SR-Related Proteins Tra2β Sfrs10 RRM, RS (GAA)n HipK3, SMN, Tau SRm160 Srrm1 RS, PWI AUGAAGAGGA CD44 SWAP Sfrs8 RS, SWAP ND SWAP, CD45, Tau; possible asthma susceptibility gene hnRNP A1 Hnrnpa1 RRM, RGG UAGGGA/U HipK3, SMN2, c-H-ras; rheumatoid arthritis, systemic lupus
    [Show full text]
  • Targeting PH Domain Proteins for Cancer Therapy
    The Texas Medical Center Library DigitalCommons@TMC The University of Texas MD Anderson Cancer Center UTHealth Graduate School of The University of Texas MD Anderson Cancer Biomedical Sciences Dissertations and Theses Center UTHealth Graduate School of (Open Access) Biomedical Sciences 12-2018 Targeting PH domain proteins for cancer therapy Zhi Tan Follow this and additional works at: https://digitalcommons.library.tmc.edu/utgsbs_dissertations Part of the Bioinformatics Commons, Medicinal Chemistry and Pharmaceutics Commons, Neoplasms Commons, and the Pharmacology Commons Recommended Citation Tan, Zhi, "Targeting PH domain proteins for cancer therapy" (2018). The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences Dissertations and Theses (Open Access). 910. https://digitalcommons.library.tmc.edu/utgsbs_dissertations/910 This Dissertation (PhD) is brought to you for free and open access by the The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences at DigitalCommons@TMC. It has been accepted for inclusion in The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences Dissertations and Theses (Open Access) by an authorized administrator of DigitalCommons@TMC. For more information, please contact [email protected]. TARGETING PH DOMAIN PROTEINS FOR CANCER THERAPY by Zhi Tan Approval page APPROVED: _____________________________________________ Advisory Professor, Shuxing Zhang, Ph.D. _____________________________________________
    [Show full text]
  • A Multi-Stage Genome-Wide Association Study of Uterine Fibroids in African Americans
    UCLA UCLA Previously Published Works Title A multi-stage genome-wide association study of uterine fibroids in African Americans. Permalink https://escholarship.org/uc/item/0mc5r0xh Journal Human genetics, 136(10) ISSN 0340-6717 Authors Hellwege, Jacklyn N Jeff, Janina M Wise, Lauren A et al. Publication Date 2017-10-01 DOI 10.1007/s00439-017-1836-1 Peer reviewed eScholarship.org Powered by the California Digital Library University of California Hum Genet (2017) 136:1363–1373 DOI 10.1007/s00439-017-1836-1 ORIGINAL INVESTIGATION A multi‑stage genome‑wide association study of uterine fbroids in African Americans Jacklyn N. Hellwege1,2,3 · Janina M. Jef4 · Lauren A. Wise5,6 · C. Scott Gallagher7 · Melissa Wellons8,9 · Katherine E. Hartmann3,9 · Sarah F. Jones1,3 · Eric S. Torstenson1,2 · Scott Dickinson10 · Edward A. Ruiz‑Narváez6 · Nadin Rohland7 · Alexander Allen7 · David Reich7,11,12 · Arti Tandon7 · Bogdan Pasaniuc13,14 · Nicholas Mancuso13 · Hae Kyung Im10 · David A. Hinds15 · Julie R. Palmer6 · Lynn Rosenberg6 · Joshua C. Denny16,17 · Dan M. Roden2,16,17,18 · Elizabeth A. Stewart19 · Cynthia C. Morton12,20,21,22 · Eimear E. Kenny4 · Todd L. Edwards1,2,3 · Digna R. Velez Edwards2,3,9 Received: 12 April 2017 / Accepted: 16 August 2017 / Published online: 23 August 2017 © Springer-Verlag GmbH Germany 2017 Abstract Uterine fbroids are benign tumors of the uterus imaging, genotyped and imputed to 1000 Genomes. Stage 2 afecting up to 77% of women by menopause. They are the used self-reported fbroid and GWAS data from 23andMe, leading indication for hysterectomy, and account for $34 bil- Inc.
    [Show full text]