DOCSLIB.ORG

Hypoxia Inducible Factors Regulate Hypoxia-Mediated Splicing

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Hypoxia Inducible Factors Regulate Hypoxia-Mediated Splicing HYPOXIA INDUCIBLE FACTORS REGULATE HYPOXIA-MEDIATED SPLICING by JOHNNY A. SENA B.S., Eastern New Mexico University, 2005 M.S., Eastern New Mexico University, 2008 A thesis submitted to the Faculty of the Graduate School of the University of Colorado in partial fulfillment of the requirements for the degree of Doctor of Philosophy Molecular Biology Program 2014 ii This thesis for the Doctor of Philosophy degree by Johnny A. Sena has been approved for the Molecular Biology Program by Rui Zhao, Chair Cheng-Jun Hu, Advisor David Bentley Sean Colgan Richard Davis Cynthia Ju Trevor Williams Date _5/2/14__ iii Sena, Johnny A. (Ph.D., Molecular Biology) Hypoxia Inducible Factors Regulate Hypoxia-mediated Splicing Thesis directed by Assistant Professor Cheng-Jun Hu. ABSTRACT In response to oxygen deprivation or hypoxia within a cell, HIF1α and HIF2α hypoxia inducible transcription factors are stabilized and activate gene expression programs. Activation of HIF target genes promotes cell proliferation, apoptotic resistance, metabolic adaptation, and tissue angiogenesis in normal physiologic processes but these processes can be exploited by cancer cells to promote tumorigenesis. Recent genome-wide studies suggest that 90% of human genes are alternatively spliced, producing RNA isoforms that encode functionally distinct proteins. Thus, effective hypoxia response requires regulation of gene transcription as well as RNA splicing. Interestingly, several reports suggest that hypoxia can regulate alternative splicing; however the mechanism was not known. Although it is well established that HIFs regulate transcription during hypoxia, it was not known if HIFs could regulate alternative splicing. We hypothesized that HIFs were responsible for regulating hypoxia-mediated splicing. The following work confirmed that hypoxia regulates alternative splicing of HIF and non-HIF target genes. Moreover, we determined that HIFs, through the activation of HIF target genes, regulates transcription and alternative splicing of a subset of HIF targets. Subsequently, we found that HIFs induced the expression of CDC-like kinases which phosphorylated and activated SR protein iv splicing factors and that SC35 and SRp40 SR proteins regulated hypoxia- induced splicing of HIF target genes. Importantly, our findings provide a novel molecular mechanism through which HIFs regulate gene expression programs during hypoxia by regulating alternative splicing of HIF target genes. Importantly, we determined that CDC-like kinases regulate HIF-dependent tumorigenesis by regulating splicing of HIF targets. Excitingly, these findings identify a novel HIF signaling pathway that may be exploited to inhibit HIF activity in tumorigenesis. The form and content of this abstract are approved. I recommend its publication. Approved: Cheng-Jun Hu v To My Family for Always Believing in Me. vi CONTENTS CHAPTER I. INTRODUCTION…………………………………………………………. …….1 Hypoxia……………...……………………………………………………. ….....1 Hypoxia Inducible Transcription Factors.....…………………………… …….2 Discovery of HIF………………………………………………….. …….4 HIF1α……………………………………………………… ….....4 HIF2α……………………………………………………… …….4 Structure of HIFα..……………………………………………….. …….5 Oxygen Regulation of HIFα……………………………………... …….6 HIF Regulation by Kinase Signaling…………………………… …...11 HIF in Normal Physiology……………………………………………….. …...12 Embryonic Development………………………………………… …...13 Wound Healing…………………………………………………… …...14 Stem Cell Maintenance………………………………………….. …...15 HIF in Tumorigenesis……………………………………………………. …...16 Tumor Initiation…………………………………………………… …...17 VHL disease………………………………………………. …...17 Cancer stem cells………………………………………… …...18 Tumor Angiogenesis…………………………………………….. …...19 Epithelial-Mesenchymal Transition and Metastasis …………. …...20 Tumor Metabolism……………………………………………….. …...21 Cancer Therapy Resistance…………………………………….. …...22 vii Pre-mRNA Splicing………………………………..…………………….. …...24 Splicing Reaction..………………………..…………..………..… …...25 Alternative Splicing.……………………………………………… …...26 Role of Alternative Splicing in Development……………..…………31 Role of Alternative Splicing in Cancer……………….………… …...32 Alternative Splicing in Apoptosis…………………….…. …...32 Alternative Splicing in Cancer Metabolism …………… …...33 Alternative Splicing in the Regulation of Proto-oncogenes…..…………………………..……... …...33 Alternative Splicing in Metastasis and Invasion……...………………………………..……..........33 Alternative Splicing in Angiogenesis…………………… …...34 Cis Elements Regulate Splicing…………………….………….. …...34 Trans-acting Factors Regulate Splicing………………..……… …...36 SR Protein Regulation…………………………………………... …...38 Coupling of Transcription and Splicing………………………… …...41 Cellular Stress Regulates Alternative Splicing………………... …...48 Regulation of Alternative Splicing by Heat Shock……………………………………………. …...48 Regulation of Alternative Splicing by Osmotic Stress………………………………………... …...49 Regulation of Alternative Splicing by Uv Irradiation………………………………………….. …...49 Regulation of Alternative Splicing by Hypoxia………………………………………………… …...49 viii II. HIFS ENHANCE THE TRANSCRIPTIONAL ACTIVATION AND SPLICING OF ADRENOMEDULLIN……………. …...53 Abstract……………………………………………………………………. …...53 Introduction……………………………………………………………….. …...54 Results…………………………………………………………………….. …...55 Hypoxia Preferentially Increases Fully-spliced ADM Transcript Levels in Various Cell-lines..………………… …...55 The Increased ADM FL/I1-3 Ratio is Due to RNA Splicing but Not Due to Differential RNA Stability ……………………..………………… …...59 ADM I1-3 Transcripts are Primarily Located in the Nucleus …………………………...…………….. …...60 HIF Activity is Required for Increased Splicing of ADM Pre-mRNA…………………………………….. …...63 HIF Activity is Sufficient for Increased Splicing of ADM Pre-mRNA …………….……………………… …...65 ADM Splicing Reporters Recapitulate Splicing Changes Observed for the Endogenous ADM Gene.……...………………………………… …...66 The Transactivation Domain of HIFα Protein is Not Required for Increased RNA Splicing of the ADM Splicing Reporter.…..……………… …...71 Activation of Endogenous HIF Target Genes is Not Absolutely Required for Increased Splicing of the ADM Splicing Reporter…………….. …...74 Discussion………………………………………………………………… …...76 Acknowledgments………………………………………………………... …...82 III. HYPOXIA REGULATES ALTERNATIVE SPLICING OF HIF AND NON-HIF TARGET GENES……………………............. …...83 Abstract……………………………………………………………. …………...83 ix Introduction……………………………………………………….. …………...84 Results………………………………………………………………………….85 Genome-wide Exon Array Analysis Determines that Hypoxia Alters RNA Splicing of HIF and Non-HIF Target Genes in Hep3B Cells…………………………………... …...85 Functional Clustering of Genes that Undergo Hypoxia-Mediated AS Reveals Novel Pathways Regulated By Hypoxia……………………….. …...90 RT-PCR and qRT-PCR Validation of Alternative Splicing for Select HIF Target Genes Identified in in Exon Array Analysis……………..……………………………. …...91 Differential Expression of HIF Target Genes During Hypoxia is Due to Alternative Splicing…………...……. …...96 HIF Activity, Not Hypoxia Per Se, is Necessary to Regulate AS of HIF Target Genes……………………………………………………...99 HIF Activity is Sufficient to Regulate AS of HIF Target Genes………………………………………… ….101 PDK1 Splicing Reporters Recapitulate Splicing Changes Observed for the Endogenous PDK1 Gene when Activated by HIF under Normoxia……………………………………………... ….104 Activation of Endogenous HIF Target Genes Contributes to the Increased FL/ΔE4 ratio of the PDK1 Splicing Reporter ……………………...107 Discussion…………………………………………………………………….110 Acknowledgments……..…………………………………………………. ….113 x IV. HYPOXIC INDUCTION OF CDC-LIKE KINASES REGULATES TRANCRIPTION AND ALTERNATIVE SPLICING OF HIF TARGET GENES………………………………….. ….114 Abstract……………………………………………………………………. ….114 Introduction……………………………………………………………….. ….115 Results…………………………………………………………………….. ….116 HIFs Regulate Hypoxic Induction of CDC- Like Kinase 1, and 3 and Hypoxia Induces Phosphorylation of SR Proteins ……………………………...... ….116 TG003 Inhibits Hypoxia-induced Transcription and Splicing of HIF Targets………………….……….…………. ….119 SC35 and SRp40 Regulate AS of HIF Target Genes…………….……………………………….. ….121 SC35 Cooperates with HIF1α to Regulate AS of a PDK Minigene…………………….……………………... ….124 CLKs promote tumorigenesis of PRC3 Cells by Regulating AS of HIF Target Genes…………………. ….125 Discussion………………………………………………………………… ….128 Acknowledgments………………………………………………………... ….130 V. CONCLUSIONS AND PERSPECTIVES………………………………. ….132 Summary and Conclusions……………………………………………… ….132 Hypoxia, HIFs, and Pre-mRNA Splicing..…………………...… ….133 Hypoxic Induction of CLKs Regulates AS of HIF target Genes…………………..……………………… ….135 Perspectives and Future Directions……………………………………. ….137 Small Nucleolar RNAs……………..……………………………. ….138 RNA Helicases…………………………..……………………….. ….140 xi Other SR Proteins…………..…………..……………………….. ….141 SMAD3 and RBPMS…………………………………………….. ….142 NOL3………………………………………………………………. ….143 Splicing Targeted Therapies……………………………………. …145 VI. MATERIALS AND METHODS………………………………………….. ….148 Cell Culture……………………………………………………………….. ….148 Knockdown of Endogenous mRNAs Using Small Interfering RNAs (siRNAs)………………………………………. ….149 Plasmid Constructs and Viral Transduction…….…………………….. ….150 RNA Stability Assays.……………………………………………………. ….152 ADM and PDK1 Splicing Reporter Assays…..………………………... ….153 Protein Analysis………………………………………………………….. ….153 RNA Preparation and Reverse Transcription PCR and Quantitative PCR………………..……………. ….154 Exon Array Analysis of Alternative Splicing...…………………………. ….155 Functional Clustering of Hypoxia Inducible Genes and Alternatively Spliced Genes using DAVID Bioinformatics Resources……………………………………….
Load more

Recommended publications
  • Fast and Reliable Prediction of Noncoding Rnas
    Fast and reliable prediction of noncoding RNAs Stefan Washietl*, Ivo L. Hofacker*, and Peter F. Stadler*†‡ *Department of Theoretical Chemistry and Structural Biology, University of Vienna, Wa¨hringerstrasse 17, A-1090 Wien, Austria; and †Bioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, University of Leipzig, Ha¨rtelstrasse 16-18, D-04107 Leipzig, Germany Communicated by Hans Frauenfelder, Los Alamos National Laboratory, Los Alamos, NM, December 14, 2004 (received for review November 2, 2004) We report an efficient method for detecting functional RNAs. The served noncoding elements in mammalian (or, more generally, approach, which combines comparative sequence analysis and vertebrate) genomes, and it must be expected that a significant structure prediction, already has yielded excellent results for a fraction of them are functional RNAs. small number of aligned sequences and is suitable for large-scale Possible candidates, however, have been identified only spo- genomic screens. It consists of two basic components: (i) a measure radically so far (19, 21), simply because there are no reliable tools for RNA secondary structure conservation based on computing a to scan multiple sequence alignments for functional RNAs. The consensus secondary structure, and (ii) a measure for thermody- most widely used program QRNA (22), which has been success- namic stability, which, in the spirit of a z score, is normalized with fully used to identify ncRNAs in bacteria (23) and yeast (24), is respect to both sequence length and base composition but can be not suitable for screens of large genomes. QRNA is limited to calculated without sampling from shuffled sequences. Functional pairwise alignments, and its reliability is low, especially if the RNA secondary structures can be identified in multiple sequence evolutionary distance of the two sequences lies outside of the alignments with high sensitivity and high specificity.
    [Show full text]
  • Comparing Tools for Non-Coding RNA Multiple Sequence Alignment Based On
    Downloaded from rnajournal.cshlp.org on September 26, 2021 - Published by Cold Spring Harbor Laboratory Press ES Wright 1 1 TITLE 2 RNAconTest: Comparing tools for non-coding RNA multiple sequence alignment based on 3 structural consistency 4 Running title: RNAconTest: benchmarking comparative RNA programs 5 Author: Erik S. Wright1,* 6 1 Department of Biomedical Informatics, University of Pittsburgh (Pittsburgh, PA) 7 * Corresponding author: Erik S. Wright ([email protected]) 8 Keywords: Multiple sequence alignment, Secondary structure prediction, Benchmark, non- 9 coding RNA, Consensus secondary structure 10 Downloaded from rnajournal.cshlp.org on September 26, 2021 - Published by Cold Spring Harbor Laboratory Press ES Wright 2 11 ABSTRACT 12 The importance of non-coding RNA sequences has become increasingly clear over the past 13 decade. New RNA families are often detected and analyzed using comparative methods based on 14 multiple sequence alignments. Accordingly, a number of programs have been developed for 15 aligning and deriving secondary structures from sets of RNA sequences. Yet, the best tools for 16 these tasks remain unclear because existing benchmarks contain too few sequences belonging to 17 only a small number of RNA families. RNAconTest (RNA consistency test) is a new 18 benchmarking approach relying on the observation that secondary structure is often conserved 19 across highly divergent RNA sequences from the same family. RNAconTest scores multiple 20 sequence alignments based on the level of consistency among known secondary structures 21 belonging to reference sequences in their output alignment. Similarly, consensus secondary 22 structure predictions are scored according to their agreement with one or more known structures 23 in a family.
    [Show full text]
  • U4 Small Nuclear RNA Dissociates from a Yeast Spliceosome And
    MOLECULAR AND CELLULAR BIOLOGY, Nov. 1991, p. 5571-5577 Vol. 11, No. 11 0270-7306/91/115571-07$02.00/0 Copyright C) 1991, American Society for Microbiology U4 Small Nuclear RNA Dissociates from a Yeast Spliceosome and Does Not Participate in the Subsequent Splicing Reaction SHYUE-LEE YEAN AND REN-JANG LIN* Department of Microbiology, University of Texas at Austin, Austin, Texas 78712-1095 Received 16 April 1991/Accepted 19 August 1991 U4 and U6 small nuclear RNAs reside in a single ribonucleoprotein particle, and both are required for pre-mRNA splicing. The U4/U6 and U5 small nuclear ribonucleoproteins join Ul and U2 on the pre-mRNA during spliceosome assembly. Binding of U4 is then destabilized prior to or concomitant with the 5' cleavage-ligation. In order to test the role of U4 RNA, we isolated a functional spliceosome by using extracts prepared from yeast cells carrying a temperature-sensitive allele ofprp2 (rna2). The isolated prp2A spliceosome contains U2, U5, U6, and possibly also I11 and can be activated to splice the bound pre-mRNA. U4 RNA does not associate with the isolated spliceosomes and is shown not to be involved in the subsequent cleavage-ligation reactions. These results are consistent with the hypothesis that the role of U4 in pre-mRNA splicing is to deliver U6 to the spliceosome. Splicing of introns from nuclear pre-mRNAs occurs by mRNA in a spliceosome (19, 22). This prp2A spliceosome is two cleavage-ligation (transesterification) reactions. The first functional, since it can be activated to splice if supplemented reaction is a cleavage at the 5' splice site and the formation with splicing factors and ATP.
    [Show full text]
  • Forward Genetics
    MOLECULAR AND CELLULAR BIOLOGY, Sept. 1992, p. 3939-3947 Vol. 12, No. 9 0270-7306/92/093939-09$02.00/0 Copyright X 1992, American Society for Microbiology PRP38 Encodes a Yeast Protein Required for Pre-mRNA Splicing and Maintenance of Stable U6 Small Nuclear RNA Levels STEVEN BLANTON, APARNA SRINIVASAN, AND BRIAN C. RYMOND* T. H. Morgan School ofBiological Sciences, University ofKentucky, Lexington, Kentucky 40506-0225 Downloaded from Received 7 April 1992/Returned for modification 14 May 1992/Accepted 17 June 1992 An essential pre-mRNA splicing factor, the product of the PRP38 gene, has been genetically identified in a screen of temperature-sensitive mutants of Saccharomyces cerevisiae. Shifting temperature-sensitive prp38 cultures from 23 to 37°C prevents the first cleavage-ligation event in the excision of introns from mRNA precursors. In vitro splicing inactivation and complementation studies suggest that the PRP38-encoded factor functions, at least in part, after stable splicing complex formation. The PRP38 locus contains a 726-bp open reading frame coding for an acidic 28-kDa polypeptide (PRP38). While PRP38 lacks obvious structural similarity to previously defined splicing factors, heat inactivation of PRP38, PRP19, or any of the known U6 http://mcb.asm.org/ (or U4/U6) small nuclear ribonucleoprotein-associating proteins (i.e., PRP3, PRP4, PRP6, and PRP24) leads to a common, unexpected consequence: intracellular U6 small nuclear RNA (snRNA) levels decrease as splicing activity is lost. Curiously, U4 snRNA, normally extensively base paired with U6 snRNA, persists in the virtual absence of U6 snRNA. The excision of intervening sequences from eukaryotic ates from the spliceosome (11, 37).
    [Show full text]
  • Domains of Yeast U4 Spliceosomal RNA Required for PRP4 Protein Binding, Snrnp-Snrnp Interactions, and Pre- Mrna Splicing in Vivo
    Downloaded from genesdev.cshlp.org on September 27, 2021 - Published by Cold Spring Harbor Laboratory Press Domains of yeast U4 spliceosomal RNA required for PRP4 protein binding, snRNP-snRNP interactions, and pre- mRNA splicing in vivo R6my Bordonn4, Josette Banroques,~, 2 John Abelson, 1 and Christine Guthrie s Department of Biochemistry and Biophysics, University of California at San Francisco, San Francisco, California 94143 USA; ~Division of Biology, California Institute of Technology, Pasadena, California 91125 USA U4 small nuclear RNA (snRNA) contains two intramolecular stem-loop structures, located near each end of the molecule. The 5' stem-loop is highly conserved in structure and separates two regions of U4 snRNA that base- pair with U6 snRNA in the U4/U6 small nuclear ribonucleoprotein particle (snRNP). The 3' stem-loop is highly divergent in structure among species and lies immediately upstream of the binding site for Sm proteins. To investigate the function of these two domains, mutants were constructed that delete the yeast U4 snRNA 5' stem-loop and that replace the yeast 3' stem-loop with that from trypanosome U4 snRNA. Both mutants fail to complement a null allele of the yeast U4 gene. The defects of the mutants have been examined in heterozygous strains by native gel electrophoresis, glycerol gradient centrifugation, and immunoprecipitation. The chimeric yeast-trypanosome RNA does not associate efficiently with U6 snRNA, suggesting that the 3' stem-loop of yeast U4 snRNA might be a binding site for a putative protein that facilitates assembly of the U4/U6 complex. In contrast, the 5' hairpin deletion mutant associates efficiently with U6 snRNA.
    [Show full text]
  • Expression Profiling of Snornas in Normal Hematopoiesis and AML Wayne A
    Washington University School of Medicine Digital Commons@Becker Open Access Publications 2018 Expression profiling of snoRNAs in normal hematopoiesis and AML Wayne A. Warner Washington University School of Medicine in St. Louis David H. Spencer Washington University School of Medicine in St. Louis Maria Trissal Washington University School of Medicine in St. Louis Brian S. White Washington University School of Medicine in St. Louis Nichole Helton Washington University School of Medicine in St. Louis See next page for additional authors Follow this and additional works at: https://digitalcommons.wustl.edu/open_access_pubs Recommended Citation Warner, Wayne A.; Spencer, David H.; Trissal, Maria; White, Brian S.; Helton, Nichole; Ley, Timothy J.; and Link, Daniel C., ,"Expression profiling of snoRNAs in normal hematopoiesis and AML." Blood Advances.2,2. 151-163. (2018). https://digitalcommons.wustl.edu/open_access_pubs/7237 This Open Access Publication is brought to you for free and open access by Digital Commons@Becker. It has been accepted for inclusion in Open Access Publications by an authorized administrator of Digital Commons@Becker. For more information, please contact [email protected]. Authors Wayne A. Warner, David H. Spencer, Maria Trissal, Brian S. White, Nichole Helton, Timothy J. Ley, and Daniel C. Link This open access publication is available at Digital Commons@Becker: https://digitalcommons.wustl.edu/open_access_pubs/7237 REGULAR ARTICLE Expression profiling of snoRNAs in normal hematopoiesis and AML Wayne A. Warner,1,* David H. Spencer,1-3,* Maria Trissal,1 Brian S. White,1,2 Nichole Helton,1 Timothy J. Ley,1-3 and Daniel C. Link1,3 1Division of Oncology, 2McDonnell Genome Institute, School of Medicine, and 3Siteman Cancer Center, Washington University, St.
    [Show full text]
  • Comparing Tools for Noncoding RNA Multiple Sequence Alignment Based on Structural Consistency
    Downloaded from rnajournal.cshlp.org on September 29, 2021 - Published by Cold Spring Harbor Laboratory Press BIOINFORMATICS RNAconTest: comparing tools for noncoding RNA multiple sequence alignment based on structural consistency ERIK S. WRIGHT Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania 15219, USA ABSTRACT The importance of noncoding RNA sequences has become increasingly clear over the past decade. New RNA families are often detected and analyzed using comparative methods based on multiple sequence alignments. Accordingly, a number of programs have been developed for aligning and deriving secondary structures from sets of RNA sequences. Yet, the best tools for these tasks remain unclear because existing benchmarks contain too few sequences belonging to only a small number of RNA families. RNAconTest (RNA consistency test) is a new benchmarking approach relying on the obser- vation that secondary structure is often conserved across highly divergent RNA sequences from the same family. RNAconTest scores multiple sequence alignments based on the level of consistency among known secondary structures belonging to reference sequences in their output alignment. Similarly, consensus secondary structure predictions are scored according to their agreement with one or more known structures in a family. Comparing the performance of 10 popular alignment programs using RNAconTest revealed that DAFS, DECIPHER, LocARNA, and MAFFT created the most structurally consistent alignments. The best consensus secondary structure predictions were generated by DAFS and LocARNA (via RNAalifold). Many of the methods specific to noncoding RNAs exhibited poor scalability as the number or length of input sequences increased, and several programs displayed substantial declines in score as more sequences were aligned.
    [Show full text]
  • Inflammatory, Regulatory, and Autophagy Co-Expression Modules
    Durocher et al. Journal of Neuroinflammation (2019) 16:56 https://doi.org/10.1186/s12974-019-1433-4 RESEARCH Open Access Inflammatory, regulatory, and autophagy co-expression modules and hub genes underlie the peripheral immune response to human intracerebral hemorrhage Marc Durocher1, Bradley P. Ander1, Glen Jickling1, Farah Hamade1, Heather Hull1, Bodie Knepp1, Da Zhi Liu1, Xinhua Zhan1, Anh Tran1, Xiyuan Cheng1, Kwan Ng1, Alan Yee1, Frank R. Sharp1 and Boryana Stamova1,2* Abstract Background: Intracerebral hemorrhage (ICH) has a high morbidity and mortality. The peripheral immune system and cross-talk between peripheral blood and brain have been implicated in the ICH immune response. Thus, we delineated the gene networks associated with human ICH in the peripheral blood transcriptome. We also compared the differentially expressed genes in blood following ICH to a prior human study of perihematomal brain tissue. Methods: We performed peripheral blood whole-transcriptome analysis of ICH and matched vascular risk factor control subjects (n = 66). Gene co-expression network analysis identified groups of co-expressed genes (modules) associated with ICH and their most interconnected genes (hubs). Mixed-effects regression identified differentially expressed genes in ICH compared to controls. Results: Of seven ICH-associated modules, six were enriched with cell-specific genes: one neutrophil module, one neutrophil plus monocyte module, one T cell module, one Natural Killer cell module, and two erythroblast modules. The neutrophil/monocyte modules were enriched in inflammatory/immune pathways; the T cell module in T cell receptor signaling genes; and the Natural Killer cell module in genes regulating alternative splicing, epigenetic, and post-translational modifications.
    [Show full text]
  • Bioinformatics Approaches to Analysing RNA Mediated Regulation of Gene Expression
    Bioinformatics approaches to analysing RNA mediated regulation of gene expression Dissertation zur Erlangung des akademischen Grades "doctor rerum naturalium" (Dr. rer. nat.) eingereicht im Institut für Biochemie und Biologie an der Mathematisch-Naturwissenschaftlichen Fakultät der Universität Potsdam LIAM CHILDS Arbeitsgruppe Bioinformatik Max-Plank-Institut für Molekulare Pflanzenphysiologie Potsdam, den 13.07.2009 This work is licensed under a Creative Commons License: Attribution - Noncommercial - Share Alike 3.0 Germany To view a copy of this license visit http://creativecommons.org/licenses/by-nc-sa/3.0/de/deed.en Published online at the Institutional Repository of the University of Potsdam: URL http://opus.kobv.de/ubp/volltexte/2010/4128/ URN urn:nbn:de:kobv:517-opus-41284 http://nbn-resolving.org/urn:nbn:de:kobv:517-opus-41284 Acknowledgements Dirk Walther is certainly one of the best supervisors I’ve ever had. He gave me the freedom to pursue my own ideas and goals whilst providing all the necessary help and support when needed. I have a sneaking suspicion that, if I didn’t play the drums, I may not have been chosen to fill this PhD position. Nevertheless, studying under Dirk and playing in a kick-arse rock/pop/punk/funk/blues/jazz band together has made the past three years, although so very far from home, a very happy and fulfilling experience. To work at such an institute, in the company of great scientific minds, has helped my scientific thinking through a colossal improvement. I still have far to go, but I start my post-doctoral efforts from a very solid basis.
    [Show full text]
  • Direct Probing of RNA Structure and RNA-Protein Interactions in Purified Hela Cell&Apos;S and Yeast Spliceosomal U4/U6.U5
    doi:10.1006/jmbi.2002.5451availableonlineathttp://www.idealibrary.comon J. Mol. Biol. (2002) 317, 631±649 Direct Probing of RNA Structure and RNA-Protein Interactions in Purified HeLa Cell's and Yeast Spliceosomal U4/U6.U5 Tri-snRNP Particles AnnieMougin1,AlexanderGottschalk2,PatriziaFabrizio2 ReinhardLuÈhrmann2andChristianeBranlant1* 1UMR 7567 CNRS-UHP The U4/U6.U5 tri-snRNP is a key component of spliceosomes. By using Nancy I, Maturation des ARN chemical reagents and RNases, we performed the ®rst extensive exper- et Enzymologie MoleÂculaire imental analysis of the structure and accessibility of U4 and U6 snRNAs Universite H. Poincare in tri-snRNPs. These were puri®ed from HeLa cell nuclear extract and B.P. 239, 54506 Vandoeuvre- Saccharomyces cerevisiae cellular extract. U5 accessibility was also investi- les Nancy CeÂdex, France gated. For both species, data demonstrate the formation of the U4/U6 Y- shaped structure. In the human tri-snRNP and U4/U6 snRNP, U6 forms 2Department of Cellular the long range interaction, that was previously proposed to be respon- Biochemistry, Max-Planck- sible for dissociation of the deproteinized U4/U6 duplex. In both yeast Institute of Biophysical and human tri-snRNPs, U5 is more protected than U4 and U6, Chemistry, D-37077, GoÈttingen suggesting that the U5 snRNP-speci®c protein complex and other com- Germany ponents of the tri-snRNP wrapped the 50 stem-loop of U5. Loop I of U5 is partially accessible, and chemical modi®cations of loop I were identical in yeast and human tri-snRNPs. This re¯ects a strong conservation of the interactions of proteins with the functional loop I.
    [Show full text]
  • Fast and Reliable Prediction of Noncoding Rnas
    Fast and reliable prediction of noncoding RNAs Stefan Washietl1, Ivo L. Hofacker1 & Peter F. Stadler1;2;∗ 1Department of Theoretical Chemistry and Structural Biology, University of Vienna, Wahringerstraße¨ 17, A-1090 Wien, Austria 2Bioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, University of Leipzig, Kreuzstraße 7b, D-04103 Leipzig, Germany ∗Corresponding author. [email protected] Abstract We report an efficient method to detect functional RNAs. The ap- proach, which combines comparative sequence analysis and structure pre- diction, yields excellent results already for a small number of aligned se- quences and is suitable for large scale-genomic screens. It consists of two basic components: (1) a novel measure for RNA secondary structure conservation based on computing a consensus secondary structure, and (2) a measure for thermodynamic stability, which — in the spirit of a z- score — is normalized w.r.t. both sequence length and base composition but can be calculated without sampling from shuffled sequences. Func- tional RNA secondary structures can be identified in multiple sequence alignments with high sensitivity and high specificity. We demonstrate that this approach is not only much more accurate than previous methods but also significantly faster. The method is implemented in the program RNAz, which can be downloaded from http://www.tbi.univie.ac.at/ ˜wash/RNAz/. As a first application we screened all alignments of length N ≥ 50 in the CORG database, which compiles conserved non-coding elements in upstream regions of orthologous genes from human, mouse, rat fugu and zebrafish. We recovered all of the known non-coding RNAs and cis-acting elements with high significance and found compelling evidence for many other conserved RNA secondary structures not described so far.
    [Show full text]
  • Cloning PRP38 by Complementation
    PRP38 encodes a yeast protein required for pre-mRNA splicing and maintenance of stable U6 small nuclear RNA levels. S Blanton, A Srinivasan and B C Rymond Mol. Cell. Biol. 1992, 12(9):3939. DOI: 10.1128/MCB.12.9.3939. Downloaded from Updated information and services can be found at: http://mcb.asm.org/content/12/9/3939 These include: http://mcb.asm.org/ CONTENT ALERTS Receive: RSS Feeds, eTOCs, free email alerts (when new articles cite this article), more» on October 8, 2014 by UNIV OF KENTUCKY Information about commercial reprint orders: http://journals.asm.org/site/misc/reprints.xhtml To subscribe to to another ASM Journal go to: http://journals.asm.org/site/subscriptions/ MOLECULAR AND CELLULAR BIOLOGY, Sept. 1992, p. 3939-3947 Vol. 12, No. 9 0270-7306/92/093939-09$02.00/0 Copyright X 1992, American Society for Microbiology PRP38 Encodes a Yeast Protein Required for Pre-mRNA Splicing and Maintenance of Stable U6 Small Nuclear RNA Levels STEVEN BLANTON, APARNA SRINIVASAN, AND BRIAN C. RYMOND* T. H. Morgan School ofBiological Sciences, University ofKentucky, Lexington, Kentucky 40506-0225 Received 7 April 1992/Returned for modification 14 May 1992/Accepted 17 June 1992 Downloaded from An essential pre-mRNA splicing factor, the product of the PRP38 gene, has been genetically identified in a screen of temperature-sensitive mutants of Saccharomyces cerevisiae. Shifting temperature-sensitive prp38 cultures from 23 to 37°C prevents the first cleavage-ligation event in the excision of introns from mRNA precursors. In vitro splicing inactivation and complementation studies suggest that the PRP38-encoded factor functions, at least in part, after stable splicing complex formation.
    [Show full text]