An R Package to Explore Circular RNA Impact on Gene Expression and Pathways

Total Page:16

File Type:pdf, Size:1020Kb

An R Package to Explore Circular RNA Impact on Gene Expression and Pathways G C A T T A C G G C A T genes Article CircIMPACT: An R Package to Explore Circular RNA Impact on Gene Expression and Pathways Alessia Buratin 1,2 , Enrico Gaffo 2 , Anna Dal Molin 2 and Stefania Bortoluzzi 2,3,* 1 Department of Biology, University of Padova, 35131 Padova, Italy; [email protected] 2 Department of Molecular Medicine, University of Padova, 35131 Padova, Italy; [email protected] (E.G.); [email protected] (A.D.M.) 3 Interdepartmental Research Center for Innovative Biotechnologies (CRIBI), University of Padova, 35131 Padova, Italy * Correspondence: [email protected] Abstract: Circular RNAs (circRNAs) are transcripts generated by back-splicing. CircRNAs might regulate cellular processes by different mechanisms, including interaction with miRNAs and RNA- binding proteins. CircRNAs are pleiotropic molecules whose dysregulation has been linked to human diseases and can drive cancer by impacting gene expression and signaling pathways. The detection of circRNAs aberrantly expressed in disease conditions calls for the investigation of their functions. Here, we propose CircIMPACT, a bioinformatics tool for the integrative analysis of circRNA and gene expression data to facilitate the identification and visualization of the genes whose expression varies according to circRNA expression changes. This tool can highlight regulatory axes potentially governed by circRNAs, which can be prioritized for further experimental study. The usefulness of CircIMPACT is exemplified by a case study analysis of bladder cancer RNA-seq data. The link between circHIPK3 and heparanase (HPSE) expression, due to the circHIPK3-miR558-HPSE Citation: Buratin, A.; Gaffo, E.; Dal regulatory axis previously determined by experimental studies on cell lines, was successfully detected. Molin, A.; Bortoluzzi, S. CircIMPACT: CircIMPACT is freely available at GitHub. An R Package to Explore Circular RNA Impact on Gene Expression and Keywords: circular RNA; gene expression; regulatory axes; pathways Pathways. Genes 2021, 12, 1044. https://doi.org/10.3390/ genes12071044 1. Introduction Academic Editor: Björn Voß Circular RNAs (circRNAs) are a class of abundant and stable RNAs that result from the ligation of a downstream splice donor to an upstream splice acceptor [1]. The progres- Received: 1 June 2021 sive discovery of circRNA functions, involvement in biological processes, and oncogenic Accepted: 2 July 2021 potential made them attractive molecules for both fundamental and cancer research [2]. Published: 6 July 2021 CircRNAs regulate cellular processes by acting with different mechanisms (Figure1 ), mostly involving sequence-specific binding with other nucleic acids or proteins. Of note, Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in one prominent mechanism whereby circRNAs are believed to function is by sponging published maps and institutional affil- miRNA, thus regulating the expression of miRNA-target genes, working as competitive iations. endogenous RNAs (ceRNAs) [3]. Aberrant DNA methylation and histone modifications can be controlled by circRNAs that regulate key epigenetic “writers” like DNMT1 [4] and EZH2 [5] methyltransferases. Regulatory functions on gene transcription were also described for circRNAs [6]. Other circRNAs modulate the activity of RNA-binding proteins (RBPs), a large class of molecules involved in a multitude of processes, including the Copyright: © 2021 by the authors. control of cell cycle progression [7] and splicing [8], among others. In addition, since most Licensee MDPI, Basel, Switzerland. This article is an open access article circRNAs originate from the circularization of coding gene exons, circRNA biogenesis distributed under the terms and can compete with linear RNA splicing [8]. Beyond exerting functions typical of long conditions of the Creative Commons non-coding RNAs, circRNAs can be translated into peptides [9,10]. Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). Genes 2021, 12, 1044. https://doi.org/10.3390/genes12071044 https://www.mdpi.com/journal/genes Genes 2021, 12, x FOR PEER REVIEW 2 of 13 Evidence on circRNA functions added another level of complexity in the network of diverse players in regulating cellular processes, impacting normal and pathogenic or malignant phenotypes. Transcriptomics data has been proven useful to unearth the effects of protein and RNA dysfunctions, and their contribution to the pathogenesis and global deregulation of gene expression in cancer. This type of analysis falls in the field of expression data reverse engineering, which has been extensively used to infer regulatory Genes 2021, 12, 1044 networks involving transcriptional regulators [11], miRNAs [12], and combinations2 of 13 thereof [13,14]. Starting from the hypothesis that circRNAs affect gene expression, then gene expression profiles could be used to infer circRNA biological functions (Figure 1). Figure 1. CircRNAs regulate cell behavior with different mechanisms. The integrated analysis of Figure 1. CircRNAs regulate cell behavior with different mechanisms. The integrated analysis circRNA and linear gene expression profiles can predict circRNA functionsby identifying the of circRNA and linear gene expression profiles can predict circRNA functionsby identifying the biological processes and pathways impacted by circRNA expression variation. biological processes and pathways impacted by circRNA expression variation. EvidenceCircRNAs on can circRNA be detected functions and addedquantifi anothered using level RNA-seq of complexity [15] and in theappropriate network ofsoftware diverse tools players [16,17]. in regulating Typically, cellular studies processes, aiming at impactingidentifying normal circRNA and roles pathogenic in disease or malignantand cancer phenotypes. face two consecutive Transcriptomics challenges. data has The been first proven is to usefulefficiently to unearth prioritize the the ef- fectscircRNAs of protein that discriminate and RNA dysfunctions, between normal and an theird malignant contribution cells or to that the pathogenesishave the potential and globalto define deregulation new and possibly of gene relevant expression disease in cancer. subtypes. This Subsequently, type of analysis the falls involvement in the field of ofcircRNAs expression in dataspecific reverse pathological engineering, mechan whichisms has beenor biological extensively processes used toinfer should regula- be toryidentified. networks These involving challenges transcriptional can be tackled regulators by circRNA [11 ],screening, miRNAs for [12 ],instance, and combinations by massive thereofcircRNA [13 silencing,14]. Starting or overexpression from the hypothesis studies, thatand circRNAswith experimental affect gene investigation expression, of then the genemechanisms expression involved, profiles once could the be usedcircRNAs to infer whose circRNA expression biological impacts functions significant (Figure1). cell featuresCircRNAs have been can identified. be detected and quantified using RNA-seq [15] and appropriate soft- wareComputational tools [16,17]. Typically, predictions studies were aiming extensivel at identifyingy used to circRNAidentify circRNA roles in disease correlation and cancerwith diseases face two [18] consecutive and infer challenges. circRNA functi The firstons. isMost to efficiently of the efforts prioritize were the put circRNAs toward thatpredicting discriminate the miRNA-sponging between normal andactivity malignant of circRNAs cells or and that inferring have the potentialcircRNA-miRNA- to define newgene andregulatory possibly relevantaxes. Among disease subtypes.circRNA-dedi Subsequently,cated databases, the involvement CircInteractome of circRNAs [19], in specificCircAtlas pathological [20], and CSCD mechanisms [21] provide or biological information processes about shouldmiRNAs be potentially identified. sponged These chal- by lengescircRNAs. can beHowever, tackled bynone circRNA of them screening, allows the for analysis instance, of bynew massive expression circRNA data. silencing or overexpressionThe ceRNA studies, function and was with the experimental first described investigation for circRNAs of the [1,22] mechanisms and has important involved, onceimplications the circRNAs in cancer. whose We expression and other groups impacts used significant custom cell integrative features haveanalysis been of identified. circRNA, miRNA,Computational and gene expression predictions data, were with extensively systems used biology to identify methods, circRNA to infer correlation circRNA withregulatory diseases networks [18] and [23–26]. infer circRNABesides, the functions. Cerina tool Most for of predicting the efforts biological were put functions toward predictingof circRNAs the based miRNA-sponging on the ceRNA activity model of was circRNAs recently and made inferring available circRNA-miRNA-gene [27]. However, the regulatoryceRNA function axes. Among may not circRNA-dedicated apply to all circRNAs databases, [28,29]: CircInteractome systematic analyses [19], CircAtlas of circRNA [20], andsequences CSCD showed [21] provide that only information a minority about present miRNAs multiple potentially binding sites sponged for specific by circRNAs. miRNAs However,[30], and, in none general, of them circRNAs allows theare analysisnot bound of newto miRNA-loaded expression data. Argonaute proteins [31]. The ceRNA function was the first described for circRNAs [1,22] and has important implications in cancer. We and other groups
Recommended publications
  • 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]
  • Aneuploidy: Using Genetic Instability to Preserve a Haploid Genome?
    Health Science Campus FINAL APPROVAL OF DISSERTATION Doctor of Philosophy in Biomedical Science (Cancer Biology) Aneuploidy: Using genetic instability to preserve a haploid genome? Submitted by: Ramona Ramdath In partial fulfillment of the requirements for the degree of Doctor of Philosophy in Biomedical Science Examination Committee Signature/Date Major Advisor: David Allison, M.D., Ph.D. Academic James Trempe, Ph.D. Advisory Committee: David Giovanucci, Ph.D. Randall Ruch, Ph.D. Ronald Mellgren, Ph.D. Senior Associate Dean College of Graduate Studies Michael S. Bisesi, Ph.D. Date of Defense: April 10, 2009 Aneuploidy: Using genetic instability to preserve a haploid genome? Ramona Ramdath University of Toledo, Health Science Campus 2009 Dedication I dedicate this dissertation to my grandfather who died of lung cancer two years ago, but who always instilled in us the value and importance of education. And to my mom and sister, both of whom have been pillars of support and stimulating conversations. To my sister, Rehanna, especially- I hope this inspires you to achieve all that you want to in life, academically and otherwise. ii Acknowledgements As we go through these academic journeys, there are so many along the way that make an impact not only on our work, but on our lives as well, and I would like to say a heartfelt thank you to all of those people: My Committee members- Dr. James Trempe, Dr. David Giovanucchi, Dr. Ronald Mellgren and Dr. Randall Ruch for their guidance, suggestions, support and confidence in me. My major advisor- Dr. David Allison, for his constructive criticism and positive reinforcement.
    [Show full text]
  • Supplementary Materials
    Supplementary materials Supplementary Table S1: MGNC compound library Ingredien Molecule Caco- Mol ID MW AlogP OB (%) BBB DL FASA- HL t Name Name 2 shengdi MOL012254 campesterol 400.8 7.63 37.58 1.34 0.98 0.7 0.21 20.2 shengdi MOL000519 coniferin 314.4 3.16 31.11 0.42 -0.2 0.3 0.27 74.6 beta- shengdi MOL000359 414.8 8.08 36.91 1.32 0.99 0.8 0.23 20.2 sitosterol pachymic shengdi MOL000289 528.9 6.54 33.63 0.1 -0.6 0.8 0 9.27 acid Poricoic acid shengdi MOL000291 484.7 5.64 30.52 -0.08 -0.9 0.8 0 8.67 B Chrysanthem shengdi MOL004492 585 8.24 38.72 0.51 -1 0.6 0.3 17.5 axanthin 20- shengdi MOL011455 Hexadecano 418.6 1.91 32.7 -0.24 -0.4 0.7 0.29 104 ylingenol huanglian MOL001454 berberine 336.4 3.45 36.86 1.24 0.57 0.8 0.19 6.57 huanglian MOL013352 Obacunone 454.6 2.68 43.29 0.01 -0.4 0.8 0.31 -13 huanglian MOL002894 berberrubine 322.4 3.2 35.74 1.07 0.17 0.7 0.24 6.46 huanglian MOL002897 epiberberine 336.4 3.45 43.09 1.17 0.4 0.8 0.19 6.1 huanglian MOL002903 (R)-Canadine 339.4 3.4 55.37 1.04 0.57 0.8 0.2 6.41 huanglian MOL002904 Berlambine 351.4 2.49 36.68 0.97 0.17 0.8 0.28 7.33 Corchorosid huanglian MOL002907 404.6 1.34 105 -0.91 -1.3 0.8 0.29 6.68 e A_qt Magnogrand huanglian MOL000622 266.4 1.18 63.71 0.02 -0.2 0.2 0.3 3.17 iolide huanglian MOL000762 Palmidin A 510.5 4.52 35.36 -0.38 -1.5 0.7 0.39 33.2 huanglian MOL000785 palmatine 352.4 3.65 64.6 1.33 0.37 0.7 0.13 2.25 huanglian MOL000098 quercetin 302.3 1.5 46.43 0.05 -0.8 0.3 0.38 14.4 huanglian MOL001458 coptisine 320.3 3.25 30.67 1.21 0.32 0.9 0.26 9.33 huanglian MOL002668 Worenine
    [Show full text]
  • Viewed and Published Immediately Upon Acceptance Cited in Pubmed and Archived on Pubmed Central Yours — You Keep the Copyright
    BMC Genomics BioMed Central Research article Open Access Differential gene expression in ADAM10 and mutant ADAM10 transgenic mice Claudia Prinzen1, Dietrich Trümbach2, Wolfgang Wurst2, Kristina Endres1, Rolf Postina1 and Falk Fahrenholz*1 Address: 1Johannes Gutenberg-University, Institute of Biochemistry, Mainz, Johann-Joachim-Becherweg 30, 55128 Mainz, Germany and 2Helmholtz Zentrum München – German Research Center for Environmental Health, Institute for Developmental Genetics, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany Email: Claudia Prinzen - [email protected]; Dietrich Trümbach - [email protected]; Wolfgang Wurst - [email protected]; Kristina Endres - [email protected]; Rolf Postina - [email protected]; Falk Fahrenholz* - [email protected] * Corresponding author Published: 5 February 2009 Received: 19 June 2008 Accepted: 5 February 2009 BMC Genomics 2009, 10:66 doi:10.1186/1471-2164-10-66 This article is available from: http://www.biomedcentral.com/1471-2164/10/66 © 2009 Prinzen et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Background: In a transgenic mouse model of Alzheimer disease (AD), cleavage of the amyloid precursor protein (APP) by the α-secretase ADAM10 prevented amyloid plaque formation, and alleviated cognitive deficits. Furthermore, ADAM10 overexpression increased the cortical synaptogenesis. These results suggest that upregulation of ADAM10 in the brain has beneficial effects on AD pathology. Results: To assess the influence of ADAM10 on the gene expression profile in the brain, we performed a microarray analysis using RNA isolated from brains of five months old mice overexpressing either the α-secretase ADAM10, or a dominant-negative mutant (dn) of this enzyme.
    [Show full text]
  • Supp Table 6.Pdf
    Supplementary Table 6. Processes associated to the 2037 SCL candidate target genes ID Symbol Entrez Gene Name Process NM_178114 AMIGO2 adhesion molecule with Ig-like domain 2 adhesion NM_033474 ARVCF armadillo repeat gene deletes in velocardiofacial syndrome adhesion NM_027060 BTBD9 BTB (POZ) domain containing 9 adhesion NM_001039149 CD226 CD226 molecule adhesion NM_010581 CD47 CD47 molecule adhesion NM_023370 CDH23 cadherin-like 23 adhesion NM_207298 CERCAM cerebral endothelial cell adhesion molecule adhesion NM_021719 CLDN15 claudin 15 adhesion NM_009902 CLDN3 claudin 3 adhesion NM_008779 CNTN3 contactin 3 (plasmacytoma associated) adhesion NM_015734 COL5A1 collagen, type V, alpha 1 adhesion NM_007803 CTTN cortactin adhesion NM_009142 CX3CL1 chemokine (C-X3-C motif) ligand 1 adhesion NM_031174 DSCAM Down syndrome cell adhesion molecule adhesion NM_145158 EMILIN2 elastin microfibril interfacer 2 adhesion NM_001081286 FAT1 FAT tumor suppressor homolog 1 (Drosophila) adhesion NM_001080814 FAT3 FAT tumor suppressor homolog 3 (Drosophila) adhesion NM_153795 FERMT3 fermitin family homolog 3 (Drosophila) adhesion NM_010494 ICAM2 intercellular adhesion molecule 2 adhesion NM_023892 ICAM4 (includes EG:3386) intercellular adhesion molecule 4 (Landsteiner-Wiener blood group)adhesion NM_001001979 MEGF10 multiple EGF-like-domains 10 adhesion NM_172522 MEGF11 multiple EGF-like-domains 11 adhesion NM_010739 MUC13 mucin 13, cell surface associated adhesion NM_013610 NINJ1 ninjurin 1 adhesion NM_016718 NINJ2 ninjurin 2 adhesion NM_172932 NLGN3 neuroligin
    [Show full text]
  • Whole Genome Sequencing of Finnish Type 1 Diabetic Siblings Discordant for Kidney Disease Reveals DNA Variants Associated with Diabetic Nephropathy
    Supplementary Data Whole genome sequencing of Finnish type 1 diabetic siblings discordant for kidney disease reveals DNA variants associated with diabetic nephropathy Jing Guo, Owen J.L. Rackham, Bing He, Anne-May Österholm, Niina Sandholm, Erkka Valo, Valma Harjutsalo, Carol Forsblom, Iiro Toppila, Maikki Parkkonen, Qibin Li, Wenjuan Zhu, Nathan Harmston, Sonia Chothani, Miina K. Öhman, Eudora Eng, Yang Sun, Enrico Petretto, Per-Henrik Groop, Karl Tryggvason Supplementary Material: Whole Genome Sequencing on Finnish Diabetic Nephropathy Sibling cohort Table of contents Supplementary Methods ............................................................ 3 Supplementary Results .............................................................. 9 Supplementary Tables ............................................................. 11 Supplementary Table 1. Comparison of DNA sequencing quality using the Illumina and Complete Genomics platforms. ......................................................................11 Supplementary Table 2. Annotation of SNVs and indels identified in 161 genomes in the Discovery cohort by RefSeq. ......................................................................12 Supplementary Table 3. Frameshift-causing small insertions and deletions (indels) found in DN cases-only or controls-only individuals of the Finnish T1D DSP discovery cohort ...................................................................................................13 Supplementary Table 4. Recurrently mutated regions (RMR) significantly overrepresented
    [Show full text]
  • Genome-Wide Identification and Analysis of Mirnas Complementary to Upstream Sequences of Mrna Transcription Start Sites
    In: Gene Silencing: Theory, Techniques and Applications ISBN: 978-1-61728-276-8 Editor: Anthony J. Catalano © 2010 Nova Science Publishers, Inc. The exclusive license for this PDF is limited to personal printing only. No part of this digital document may be reproduced, stored in a retrieval system or transmitted commercially in any form or by any means. The publisher has taken reasonable care in the preparation of this digital document, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained herein. This digital document is sold with the clear understanding that the publisher is not engaged in rendering legal, medical or any other professional services. Chapter XIII Genome-wide Identification and Analysis of miRNAs Complementary to Upstream Sequences of mRNA Transcription Start Sites Kenta Narikawa1, Kenji Nishi2, Yuki Naito2, Minami Mazda2 and Kumiko Ui-Tei1,2,* 1Department of Computational Biology, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa-shi, Chiba-ken 277-8561, Japan 2Department of Biophysics and Biochemistry, Graduate School of Science, University of Tokyo, 2-11-16 Yayoi, Bunkyo-ku, Tokyo 113-0032, Japan Abstract Small regulatory RNAs including short interfering RNAs (siRNAs) and microRNAs (miRNAs) are crucial regulators of gene expression at the posttranscriptional level. Recently, additional roles for small RNAs in gene activation and suppression at the transcriptional level were reported; these RNAs were shown to have sequences that closely or completely match to their respective promoter regions.
    [Show full text]
  • Germline PTPRT Mutation Potentially Involved in Cancer Predisposition
    Germline PTPRT mutation potentially involved in cancer predisposition Lorena Martin1, Victor Lorca2, Pedro P´erez-Segura2, Patricia Llovet1, Vanesa Garc´ıa-Barber´an3, Maria Luisa Gonzalez-Morales2, Sami Belhad4, Gabriel Capell´a5, Laura Valle4, Miguel de la Hoya2, Pilar Garre6, and Trinidad Caldes2 1Hospital Clinico San Carlos. IdISCC 2Hospital Clinico San Carlos. IdISSC 3Hospital Cl´ınicoSan Carlos, IdISCC, CIBERONC 4IDIBELL 5ICO-IDIBELL 6Hospital clinico San Carlos. IdISSC September 17, 2020 Abstract Familial Colorectal Cancer Type X (FCCTX) is a term used to describe a group of families with an increased predisposition to colorectal and other related cancers, but an unknown genetic basis. Whole-exome sequencing in two cancer-affected and one healthy members of a FCCTX family revealed a truncating germline mutation in PTPRT [c.4090dup, p.(Asp1364GlyfsTer24)]. PTPRT encodes a receptor phosphatase and is a tumor suppressor gene found to be frequently mutated at somatic level in many cancers, having been proven that these mutations act as drivers that promote tumor development. This germline variant shows a compatible cosegregation with cancer in the family and results in the loss of a significant fraction of the second phosphatase domain of the protein, which is essential for PTPRT's activity. In addition, the tumors of the carriers exhibit epigenetic inactivation of the wild-type allele and an altered expression of PTPRT downstream target genes, consistent with a causal role of this germline mutation in the cancer predisposition of the family. Although PTPRT's role cancer initiation and progression has been well studied, this is the first time that a germline PTPRT mutation is linked with cancer susceptibility and hereditary cancer, which highlights the relevance of the present study.
    [Show full text]
  • To Download the PDF File
    NOTE TO USERS This reproduction is the best copy available. UMI* ACTIVE LEARNING FOR THE PREDICTION OF ASPARAGINE AND ASPARTATE HYDROXYLATION SITES ON HUMAN PROTEINS By Festus Omonigho Iyuke, B.Sc, M.Sc. ACTIVE LEARNING FOR THE PREDICTION OF ASPARAGINE AND ASPARTATE HYDROXYLATION SITES ON HUMAN PROTEINS A thesis submitted to the Faculty of Graduate Studies and Research in partial fulfillment of the requirements for the degree of Masters of Applied Science in Biomedical Engineering Ottawa-Carleton Institute for Biomedical Engineering Department of Systems and Computer Engineering Carleton University Ottawa, Ontario, Canada September 2011 Copyright © Festus Iyuke, September 2011 Library and Archives Bibliotheque et 1*1 Canada Archives Canada Published Heritage Direction du Branch Patrimoine de I'edition 395 Wellington Street 395, rue Wellington OttawaONK1A0N4 OttawaONK1A0N4 Canada Canada Your file Votre reference ISBN: 978-0-494-83033-8 Our file Notre reference ISBN: 978-0-494-83033-8 NOTICE: AVIS: The author has granted a non­ L'auteur a accorde une licence non exclusive exclusive license allowing Library and permettant a la Bibliotheque et Archives Archives Canada to reproduce, Canada de reproduire, publier, archiver, publish, archive, preserve, conserve, sauvegarder, conserver, transmettre au public communicate to the public by par telecommunication ou par I'lnternet, preter, telecommunication or on the Internet, distribuer et vendre des theses partout dans le loan, distribute and sell theses monde, a des fins commerciales ou autres, sur worldwide, for commercial or non­ support microforme, papier, electronique et/ou commercial purposes, in microform, autres formats. paper, electronic and/or any other formats. The author retains copyright L'auteur conserve la propriete du droit d'auteur ownership and moral rights in this et des droits moraux qui protege cette these.
    [Show full text]
  • Is Chemically Dispersed Oil More Toxic to Atlantic Cod
    Olsvik et al. BMC Genomics 2012, 13:702 http://www.biomedcentral.com/1471-2164/13/702 RESEARCH ARTICLE Open Access Is chemically dispersed oil more toxic to Atlantic cod (Gadus morhua) larvae than mechanically dispersed oil? A transcriptional evaluation Pål A Olsvik1*, Kai K Lie1, Trond Nordtug2 and Bjørn Henrik Hansen2 Abstract Background: The use of dispersants can be an effective way to deal with acute oil spills to limit environmental damage, however very little is known about whether chemically dispersed oil have the same toxic effect on marine organisms as mechanically dispersed oil. We exposed Atlantic cod larvae to chemically and mechanically dispersed oil for four days during the first-feeding stage of development, and collected larvae at 14 days post hatch for transcriptional analysis. A genome-wide microarray was used to screen for effects and to assess whether molecular responses to chemically and mechanically dispersed oil were similar, given the same exposure to oil (droplet distribution and concentration) with and without the addition of a chemical dispersant (Dasic NS). Results: Mechanically dispersed oil induced expression changes in almost three times as many transcripts compared to chemically dispersed oil (fold change >+/−1.5). Functional analyses suggest that chemically dispersed oil affects partly different pathways than mechanically dispersed oil. By comparing the alteration in gene transcription in cod larvae exposed to the highest concentrations of either chemically or mechanically dispersed oil directly, the chemically dispersed oil affected transcription of genes involved nucleosome regulation, i.e. genes encoding proteins participating in DNA replication and chromatin formation and regulation of cell proliferation, whereas the mechanically dispersed oil most strongly affected genes encoding proteins involved in proteasome-mediated protein degradation.
    [Show full text]
  • Identification of Genomic Targets of Krüppel-Like Factor 9 in Mouse Hippocampal
    Identification of Genomic Targets of Krüppel-like Factor 9 in Mouse Hippocampal Neurons: Evidence for a role in modulating peripheral circadian clocks by Joseph R. Knoedler A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Neuroscience) in the University of Michigan 2016 Doctoral Committee: Professor Robert J. Denver, Chair Professor Daniel Goldman Professor Diane Robins Professor Audrey Seasholtz Associate Professor Bing Ye ©Joseph R. Knoedler All Rights Reserved 2016 To my parents, who never once questioned my decision to become the other kind of doctor, And to Lucy, who has pushed me to be a better person from day one. ii Acknowledgements I have a huge number of people to thank for having made it to this point, so in no particular order: -I would like to thank my adviser, Dr. Robert J. Denver, for his guidance, encouragement, and patience over the last seven years; his mentorship has been indispensable for my growth as a scientist -I would also like to thank my committee members, Drs. Audrey Seasholtz, Dan Goldman, Diane Robins and Bing Ye, for their constructive feedback and their willingness to meet in a frequently cold, windowless room across campus from where they work -I am hugely indebted to Pia Bagamasbad and Yasuhiro Kyono for teaching me almost everything I know about molecular biology and bioinformatics, and to Arasakumar Subramani for his tireless work during the home stretch to my dissertation -I am grateful for the Neuroscience Program leadership and staff, in particular
    [Show full text]
  • MAP3K11 Is a Tumor Suppressor Targeted by the Oncomir Mir-125B in Early B Cells
    Cell Death and Differentiation (2016) 23, 242–252 & 2016 Macmillan Publishers Limited All rights reserved 1350-9047/16 www.nature.com/cdd MAP3K11 is a tumor suppressor targeted by the oncomiR miR-125b in early B cells U Knackmuss1,4,5, SE Lindner2,5, T Aneichyk3, B Kotkamp1, Z Knust1, A Villunger2 and S Herzog1,2 MicroRNAs (miRNAs) are a class of small, non-coding RNAs that posttranscriptionally regulate gene expression and thereby control most, if not all, biological processes. Aberrant miRNA expression has been linked to a variety of human diseases including cancer, but the underlying molecular mechanism often remains unclear. Here we have screened a miRNA expression library in a growth factor-dependent mouse pre-B-cell system to identify miRNAs with oncogenic activity. We show that miR-125b is sufficient to render pre-B cells growth factor independent and demonstrate that continuous expression of miR-125b is necessary to keep these cells in a transformed state. Mechanistically, we find that the expression of miR-125b protects against apoptosis induced by growth factor withdrawal, and that it blocks the differentiation of pre-B to immature B cells. In consequence, miR-125b-transformed cells maintain expression of their pre-B-cell receptor that provides signals for continuous proliferation and survival even in the absence of growth factor. Employing microarray analysis, we identified numerous targets of miR-125b, but only reconstitution of MAP3K11, a critical regulator of mitogen- and stress-activated kinase signaling, interferes with the cellular fitness of the transformed cells. Together, this indicates that MAP3K11 might function as an important tumor suppressor neutralized by oncomiR-125b in B-cell leukemia.
    [Show full text]