Mirna Targeting and Alternative Splicing in the Stress Response – Events Hosted by Membrane-Less Compartments Mariya M
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Differential Analysis of Gene Expression and Alternative Splicing
i bioRxiv preprint doi: https://doi.org/10.1101/2020.08.23.234237; this version posted August 24, 2020. The copyright holder for this preprint i (which was not certified by peer review)“main” is the author/funder, — 2020/8/23 who has — granted 9:38 — bioRxiv page a1 license — #1 to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. i i EmpiReS: Differential Analysis of Gene Expression and Alternative Splicing Gergely Csaba∗, Evi Berchtold*,y, Armin Hadziahmetovic, Markus Gruber, Constantin Ammar and Ralf Zimmer Department of Informatics, Ludwig-Maximilians-Universitat¨ Munchen,¨ 80333, Munich, Germany ABSTRACT to translation. Different transcripts of the same gene are often expressed at the same time, possibly at different abundance, While absolute quantification is challenging in high- yielding a defined mixture of isoforms. Changes to this throughput measurements, changes of features composition are further referred to as differential alternative between conditions can often be determined with splicing (DAS). Various diseases can be linked to DAS high precision. Therefore, analysis of fold changes events (3). Most hallmarks of cancer like tumor progression is the standard method, but often, a doubly and immune escape (4, 5) can be attributed to changes in differential analysis of changes of changes is the transcript composition (6). DAS plays a prominent role required. Differential alternative splicing is an in various types of muscular dystrophy (MD) (7), splicing example of a doubly differential analysis, i.e. fold intervention by targeted exon removal is a therapeutic option changes between conditions for different isoforms in Duchenne MD (8). -
Crystal Structure of the Primary Pirna Biogenesis Factor Zucchini Reveals Similarity to the Bacterial PLD Endonuclease Nuc
Downloaded from rnajournal.cshlp.org on September 26, 2021 - Published by Cold Spring Harbor Laboratory Press LETTER TO THE EDITOR Crystal structure of the primary piRNA biogenesis factor Zucchini reveals similarity to the bacterial PLD endonuclease Nuc FRANKA VOIGT,1 MICHAEL REUTER,2,3 ANISA KASARUHO,2,3 EIKE C. SCHULZ,1 RAMESH S. PILLAI,2,3,4 and ORSOLYA BARABAS1,4 1European Molecular Biology Laboratory, 69117 Heidelberg, Germany 2European Molecular Biology Laboratory, 38042 Grenoble, France 3CNRS-UJF-EMBL International Unit (UMI 3265) for Virus Host Cell Interactions (UVHCI), 38042 Grenoble, France ABSTRACT Piwi-interacting RNAs (piRNAs) are a gonad-specific class of small RNAs that associate with the Piwi clade of Argonaute proteins and play a key role in transposon silencing in animals. Since biogenesis of piRNAs is independent of the double- stranded RNA-processing enzyme Dicer, an alternative nuclease that can process single-stranded RNA transcripts has been long sought. A Phospholipase D-like protein, Zucchini, that is essential for piRNA processing has been proposed to be a nuclease acting in piRNA biogenesis. Here we describe the crystal structure of Zucchini from Drosophila melanogaster and show that it is very similar to the bacterial endonuclease, Nuc. The structure also reveals that homodimerization induces major conforma- tional changes assembling the active site. The active site is situated on the dimer interface at the bottom of a narrow groove that can likely accommodate single-stranded nucleic acid substrates. Furthermore, biophysical analysis identifies protein segments essential for dimerization and provides insights into regulation of Zucchini’s activity. Keywords: Zucchini; piRNA; Piwi; nuclease; phospholipase; PLD6; MitoPLD INTRODUCTION stranded (ss) RNAs (Brennecke et al. -
Regulatory Micrornas in Brown, Brite and White Adipose Tissue
cells Review Regulatory microRNAs in Brown, Brite and White Adipose Tissue Seley Gharanei 1,2, Kiran Shabir 3 , James E. Brown 3,4, Martin O. Weickert 1,2,5 , 1,2 1,2,3, 1,2,3, , Thomas M. Barber , Ioannis Kyrou y and Harpal S. Randeva * y 1 Warwickshire Institute for the Study of Diabetes, Endocrinology and Metabolism (WISDEM), University Hospitals Coventry and Warwickshire NHS Trust, Coventry CV2 2DX, UK; [email protected] (S.G.); [email protected] (M.O.W.); [email protected] (T.M.B.); [email protected] (I.K.) 2 Warwick Medical School, University of Warwick, Coventry CV4 7AL, UK 3 Aston Medical Research Institute, Aston Medical School, College of Health and Life Sciences, Aston University, Birmingham B4 7ET, UK; [email protected] (K.S.); [email protected] (J.E.B.) 4 School of Biosciences, College of Health and Life Sciences, Aston University, Birmingham B4 7ET, UK 5 Centre of Applied Biological & Exercise Sciences, Faculty of Health & Life Sciences, Coventry University, Coventry CV1 5FB, UK * Correspondence: [email protected] Joint senior authors; contributed equally to the manuscript. y Received: 30 September 2020; Accepted: 13 November 2020; Published: 16 November 2020 Abstract: MicroRNAs (miRNAs) constitute a class of short noncoding RNAs which regulate gene expression by targeting messenger RNA, inducing translational repression and messenger RNA degradation. This regulation of gene expression by miRNAs in adipose tissue (AT) can impact on the regulation of metabolism and energy homeostasis, particularly considering the different types of adipocytes which exist in mammals, i.e., white adipocytes (white AT; WAT), brown adipocytes (brown AT; BAT), and inducible brown adipocytes in WAT (beige or brite or brown-in-white adipocytes). -
RNA Components of the Spliceosome Regulate Tissue- and Cancer-Specific Alternative Splicing
Downloaded from genome.cshlp.org on September 29, 2021 - Published by Cold Spring Harbor Laboratory Press Research RNA components of the spliceosome regulate tissue- and cancer-specific alternative splicing Heidi Dvinge,1,2,4 Jamie Guenthoer,3 Peggy L. Porter,3 and Robert K. Bradley1,2 1Computational Biology Program, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA; 2Basic Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA; 3Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA Alternative splicing of pre-mRNAs plays a pivotal role during the establishment and maintenance of human cell types. Characterizing the trans-acting regulatory proteins that control alternative splicing has therefore been the focus of much research. Recent work has established that even core protein components of the spliceosome, which are required for splicing to proceed, can nonetheless contribute to splicing regulation by modulating splice site choice. We here show that the RNA components of the spliceosome likewise influence alternative splicing decisions. Although these small nuclear RNAs (snRNAs), termed U1, U2, U4, U5, and U6 snRNA, are present in equal stoichiometry within the spliceosome, we found that their relative levels vary by an order of magnitude during development, across tissues, and across cancer samples. Physiologically relevant perturbation of individual snRNAs drove widespread gene-specific differences in alternative splic- ing but not transcriptome-wide splicing failure. Genes that were particularly sensitive to variations in snRNA abundance in a breast cancer cell line model were likewise preferentially misspliced within a clinically diverse cohort of invasive breast ductal carcinomas. -
Splicing Graphs and RNA-Seq Data
Splicing graphs and RNA-seq data Herv´ePag`es Daniel Bindreither Marc Carlson Martin Morgan Last modified: January 2019; Compiled: May 19, 2021 Contents 1 Introduction 1 2 Splicing graphs 2 2.1 Definitions and example . .2 2.2 Details about nodes and edges . .2 2.3 Uninformative nodes . .5 3 Computing splicing graphs from annotations 6 3.1 Choosing and loading a gene model . .6 3.2 Generating a SplicingGraphs object . .6 3.3 Basic manipulation of a SplicingGraphs object . .8 3.4 Extracting and plotting graphs from a SplicingGraphs object . 12 4 Splicing graph bubbles 15 4.1 Some definitions . 15 4.2 Computing the bubbles of a splicing graph . 17 4.3 AScodes ............................................... 18 4.4 Tabulating all the AS codes for Human chromosome 14 . 19 5 Counting reads 20 5.1 Assigning reads to the edges of a SplicingGraphs object . 22 5.2 How does read assignment work? . 23 5.3 Counting and summarizing the assigned reads . 25 6 Session Information 26 1 Introduction The SplicingGraphs package allows the user to create and manipulate splicing graphs [1] based on annotations for a given organism. Annotations must describe a gene model, that is, they need to contain the following information: The exact exon/intron structure (i.e., genomic coordinates) for the known transcripts. The grouping of transcripts by gene. Annotations need to be provided as a TxDb or GRangesList object, which is how a gene model is typically represented in Bioconductor. 1 The SplicingGraphs package defines the SplicingGraphs container for storing the splicing graphs together with the gene model that they are based on. -
Identification of Genes That Affect Acetylcholine
IDENTIFICATION OF GENES THAT AFFECT ACETYLCHOLINE SIGNALING AT THE C. ELEGANS NEUROMUSCULAR JUNCTION by Shrey Patel A thesis submitted to the Faculty of the University of Delaware in partial fulfillment of the requirements for the degree of Honors Bachelor of Arts in Biological Sciences with Distinction Spring 2018 © 2018 Shrey Patel All Rights Reserved IDENTIFICATION OF GENES THAT AFFECT ACETYLCHOLINE SIGNALING AT THE C. ELEGANS NEUROMUSCULAR JUNCTION by Shrey Patel Approved: __________________________________________________________ Jessica Tanis, Ph.D. Professor in charge of thesis on behalf of the Advisory Committee Approved: __________________________________________________________ Donna Woulfe, Ph.D. Committee member from the Department of Biological Sciences Approved: __________________________________________________________ Carlton Cooper, Ph.D. Committee member from the Board of Senior Thesis Readers Approved: __________________________________________________________ Paul Laux, Ph.D. Director, University Honors Program ACKNOWLEDGMENTS I would like to first thank Dr. Jessica Tanis for giving me the opportunity to conduct research towards a senior thesis. Her guidance, support, and encouragement throughout the process have been invaluable. Her mentorship has changed my views on research, helped me grow professionally and personally, and opened doors previously unimagined. I could not be more grateful. I would not be where I am without the assistance of the Tanis Lab team: Kirsten Kervin, Elaine Miller, Andy Lam, Michael Clupper, Amanda Addiego, Denis Touroutine, and Alyssa Reed. Thank you for help with laboratory techniques, input on my presentations, and for being great team members. I would like to specially thank Amanda, Kirsten, and Elaine for their contributions to this project, which has made significant progress in just one year. I could not have wished to be in another lab, for the enriching, collaborative, and friendly environment cannot be replicated. -
Microrna Co-Expression Networks Exhibit Increased Complexity in Pancreatic Ductal Compared to Vater’S Papilla Adenocarcinoma
www.impactjournals.com/oncotarget/ Oncotarget, 2017, Vol. 8, (No. 62), pp: 105320-105339 Research Paper MicroRNA co-expression networks exhibit increased complexity in pancreatic ductal compared to Vater’s papilla adenocarcinoma Tommaso Mazza1, Massimiliano Copetti2, Daniele Capocefalo1,8, Caterina Fusilli1, Tommaso Biagini1, Massimo Carella3, Antonio De Bonis4, Nicola Mastrodonato4, Ada Piepoli5, Valerio Pazienza5, Evaristo Maiello6, Fabio Francesco di Mola7, Pierluigi di Sebastiano7, Angelo Andriulli5 and Francesca Tavano5 1Unit of Bioinformatics, Research Hospital, San Giovanni Rotondo 71013, Italy 2Unit of Biostatistics, Research Hospital, San Giovanni Rotondo 71013, Italy 3Medical Genetics Unit, Research Hospital, San Giovanni Rotondo 71013, Italy 4Department of Surgery, Research Hospital, San Giovanni Rotondo 71013, Italy 5Division of Gastroenterology and Research Laboratory, San Giovanni Rotondo 71013, Italy 6Department of Oncology IRCCS “Casa Sollievo della Sofferenza”, Research Hospital, San Giovanni Rotondo 71013, Italy 7Division of Surgical Oncology “SS Annunziata” Hospital, Chieti 66100, Italy 8Department of Cellular Biotechnologies and Haematology, Sapienza University of Rome, Rome 00161, Italy Correspondence to: Francesca Tavano, email: [email protected] Keywords: microRNA; pancrearic ductal adenocarcinoma; ampullary carcinoma Received: December 06, 2016 Accepted: July 11, 2017 Published: October 31, 2017 Copyright: Mazza et al. This is an open-access article distributed under the terms of the Creative Commons Attribution -
Unknown Areas of Activity of Human Ribonuclease Dicer: a Putative Deoxyribonuclease Activity
molecules Article Unknown Areas of Activity of Human Ribonuclease Dicer: A Putative Deoxyribonuclease Activity Marta Wojnicka , Agnieszka Szczepanska and Anna Kurzynska-Kokorniak * Department of Ribonucleoprotein Biochemistry, Institute of Bioorganic Chemistry Polish Academy of Sciences, 61-704 Poznan, Poland; [email protected] (M.W.); [email protected] (A.S.) * Correspondence: [email protected] Received: 31 January 2020; Accepted: 17 March 2020; Published: 20 March 2020 Abstract: The Dicer ribonuclease plays a crucial role in the biogenesis of small regulatory RNAs (srRNAs) by processing long double-stranded RNAs and single-stranded hairpin RNA precursors into small interfering RNAs (siRNAs) and microRNAs (miRNAs), respectively. Dicer-generated srRNAs can control gene expression by targeting complementary transcripts and repressing their translation or inducing their cleavage. Human Dicer (hDicer) is a multidomain enzyme comprising a putative helicase domain, a DUF283 domain, platform, a PAZ domain, a connector helix, two RNase III domains (RNase IIIa and RNase IIIb) and a dsRNA-binding domain. Specific, ~20-base pair siRNA or miRNA duplexes with 2 nucleotide (nt) 3’-overhangs are generated by Dicer when an RNA substrate is anchored within the platform-PAZ-connector helix (PPC) region. However, increasing number of reports indicate that in the absence of the PAZ domain, binding of RNA substrates can occur by other Dicer domains. Interestingly, truncated variants of Dicer, lacking the PPC region, have been found to display a DNase activity. Inspired by these findings, we investigated how the lack of the PAZ domain, or the entire PPC region, would influence the cleavage activity of hDicer. Using immunopurified 3xFlag-hDicer produced in human cells and its two variants: one lacking the PAZ domain, and the other lacking the entire PPC region, we show that the PAZ domain deletion variants of hDicer are not able to process a pre-miRNA substrate, a dsRNA with 2-nt 30-overhangs, and a blunt-ended dsRNA. -
RNA Splicing in the Transition from B Cells
RNA Splicing in the Transition from B Cells to Antibody-Secreting Cells: The Influences of ELL2, Small Nuclear RNA, and Endoplasmic Reticulum Stress This information is current as of September 24, 2021. Ashley M. Nelson, Nolan T. Carew, Sage M. Smith and Christine Milcarek J Immunol 2018; 201:3073-3083; Prepublished online 8 October 2018; doi: 10.4049/jimmunol.1800557 Downloaded from http://www.jimmunol.org/content/201/10/3073 Supplementary http://www.jimmunol.org/content/suppl/2018/10/05/jimmunol.180055 http://www.jimmunol.org/ Material 7.DCSupplemental References This article cites 44 articles, 16 of which you can access for free at: http://www.jimmunol.org/content/201/10/3073.full#ref-list-1 Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision by guest on September 24, 2021 • No Triage! Every submission reviewed by practicing scientists • Fast Publication! 4 weeks from acceptance to publication *average Subscription Information about subscribing to The Journal of Immunology is online at: http://jimmunol.org/subscription Permissions Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Email Alerts Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2018 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. The Journal of Immunology RNA Splicing in the Transition from B Cells to Antibody-Secreting Cells: The Influences of ELL2, Small Nuclear RNA, and Endoplasmic Reticulum Stress Ashley M. -
Post-Transcriptional Control of Mirna Biogenesis
Downloaded from rnajournal.cshlp.org on October 2, 2021 - Published by Cold Spring Harbor Laboratory Press Michlewski and Caceres Post-transcriptional control of miRNA biogenesis GRACJAN MICHLEWSKI1,2 and JAVIER F. CÁCERES3 1Division of Infection and Pathway Medicine, University of Edinburgh, The Chancellor's Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK; 2Zhejiang University-University of Edinburgh Institute, Zhejiang University, 718 East Haizhou Rd., Haining, Zhejiang 314400, P.R. China; 3MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh EH4 2XU, UK Corresponding authors: [email protected], [email protected] 1 Downloaded from rnajournal.cshlp.org on October 2, 2021 - Published by Cold Spring Harbor Laboratory Press Michlewski and Caceres ABSTRACT MicroRNAs (miRNAs) are important regulators of gene expression that bind complementary target mRNAs and repress their expression. Precursor miRNA molecules undergo nuclear and cytoplasmic processing events, carried out by the endoribonucleases, DROSHA and DICER, respectively, to produce mature miRNAs that are loaded onto the RISC (RNA-induced silencing complex) to exert their biological function. Regulation of mature miRNA levels is critical in development, differentiation and disease, as demonstrated by multiple levels of control during their biogenesis cascade. Here, we will focus on post- transcriptional mechanisms and will discuss the impact of cis-acting sequences in precursor miRNAs, as well as trans-acting factors that bind to these precursors and influence their processing. In particular, we will highlight the role of general RNA-binding proteins (RBPs) as factors that control the processing of specific miRNAs, revealing a complex layer of regulation in miRNA production and function. -
Development of the Renal Arterioles
BRIEF REVIEW www.jasn.org Development of the Renal Arterioles Maria Luisa S. Sequeira Lopez and R. Ariel Gomez Department of Pediatrics, University of Virginia School of Medicine, Charlottesville, Virginia ABSTRACT The kidney is a highly vascularized organ that normally receives a fifth of the first arterioles are seen around 15 to 16 cardiac output. The unique spatial arrangement of the kidney vasculature with each days of gestation. By 18 to 19 days of ges- nephron is crucial for the regulation of renal blood flow, GFR, urine concentration, tation, there is a basic blueprint of arte- and other specialized kidney functions. Thus, the proper and timely assembly of rial and arteriolar development.15 This is kidney vessels with their respective nephrons is a crucial morphogenetic event followed in the ensuing days by a burst of leading to the formation of a functioning kidney necessary for independent extra- branching and elongation of new arteri- uterine life. Mechanisms that govern the development of the kidney vasculature oles that repeat the basic pattern for are poorly understood. In this review, we discuss the anatomical development, about a week after birth, resulting in a embryological origin, lineage relationships, and key regulators of the kidney arte- remarkable increase in the complexity rioles and postglomerular circulation. Because renal disease is associated with and surface area of the vasculature. These deterioration of the kidney microvasculature and/or the reenactment of embryonic orchestrated series of events require that pathways, understanding the morphogenetic events and processes that maintain progenitor cells differentiate, acquire po- the renal vasculature may open new avenues for the preservation of renal structure sitional information, assemble in the and function and prevent the progression of renal disease. -
What Is a Gene, Post-ENCODE? History and Updated Definition
Downloaded from genome.cshlp.org on October 2, 2021 - Published by Cold Spring Harbor Laboratory Press Perspective What is a gene, post-ENCODE? History and updated definition Mark B. Gerstein,1,2,3,9 Can Bruce,2,4 Joel S. Rozowsky,2 Deyou Zheng,2 Jiang Du,3 Jan O. Korbel,2,5 Olof Emanuelsson,6 Zhengdong D. Zhang,2 Sherman Weissman,7 and Michael Snyder2,8 1Program in Computational Biology & Bioinformatics, Yale University, New Haven, Connecticut 06511, USA; 2Molecular Biophysics & Biochemistry Department, Yale University, New Haven, Connecticut 06511, USA; 3Computer Science Department, Yale University, New Haven, Connecticut 06511, USA; 4Center for Medical Informatics, Yale University, New Haven, Connecticut 06511, USA; 5European Molecular Biology Laboratory, 69117 Heidelberg, Germany; 6Stockholm Bioinformatics Center, Albanova University Center, Stockholm University, SE-10691 Stockholm, Sweden; 7Genetics Department, Yale University, New Haven, Connecticut 06511, USA; 8Molecular, Cellular, & Developmental Biology Department, Yale University, New Haven, Connecticut 06511, USA While sequencing of the human genome surprised us with how many protein-coding genes there are, it did not fundamentally change our perspective on what a gene is. In contrast, the complex patterns of dispersed regulation and pervasive transcription uncovered by the ENCODE project, together with non-genic conservation and the abundance of noncoding RNA genes, have challenged the notion of the gene. To illustrate this, we review the evolution of operational definitions of a gene over the past century—from the abstract elements of heredity of Mendel and Morgan to the present-day ORFs enumerated in the sequence databanks. We then summarize the current ENCODE findings and provide a computational metaphor for the complexity.