DOCSLIB.ORG

Identification of Novel Branch Points Reveals Insights Into RNA Processing

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Identification of Novel Branch Points Reveals Insights Into RNA Processing Identification of Novel Branch Points Reveals Insights into RNA Processing by Genevieve Michelle Gould B.A. Molecular and Cell Biology with an emphasis in Genetics, Genomics, and Development University of California, Berkeley (2009) Submitted to the Department of Biology in Partial Fulfillment of the Requirements for the Degree of DOCTOR OF PHILOSOPHY at the MASSACHUSETTS INSTITUTE OF TECHNOLOGY September 2015 © Massachusetts Institute of Technology 2015. All rights reserved. Signature of Author .................................................................................................................................................... Department of Biology August 31, 2015 Certified by .................................................................................................................................................................... Christopher B. Burge Professor of Biology Thesis Supervisor Accepted by.................................................................................................................................................................... Michael Hemann Associate Professor of Biology Co-Chair, Biology Graduate Committee 1 2 Identification of Novel Branch Points Reveals Insights into RNA Processing by Genevieve Michelle Gould Submitted to the Department of Biology on August 31, 2015 in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Biology Abstract Pre-mRNA splicing is a ubiquitous process necessary for the production of functional eukaryotic mRNAs. The branch point (BP) sequence is one of three key nucleotide sequences required for pre-mRNA splicing, however, in metazoa it has been less comprehensively studied than the 5' splice site (5'SS) and 3' splice site (3'SS) due to the relative difficulty of identifying each sequence element. 5'SS and 3'SS are readily identified by aligning spliced cDNAs, ESTs, or RNA-Seq reads to the genome, while lower throughput techniques such as primer extension are usually required to map BPs, with some exceptions. To understand how the BP affects splicing outcomes, we developed an experimental method to locate BPs on a genome-wide scale. Applying our method to Saccharomyces cerevisiae (S. cerevisiae), one of the only eukaryotes for which most BPs are known, allowed us to assess the sensitivity and specificity of our method. We enriched for RNA lariats by isolating RNA from debranching enzyme null yeast and purified circular RNAs (including lariats) from linear RNAs using a 2D PAGE gel. This was followed by a custom library preparation protocol that produced insert ends that identified the BP and 5'SS of individual lariats. Using this method, we located known BPs and discovered a substantial number of novel BPs both in annotated introns and other genomic regions. We attempted to verify these novel introns using RNA-seq and Lariat-seq and surprisingly observed considerable amounts of alternative splicing (AS) in S. cerevisiae beyond the previously known stress-regulated intron retention events and handful of alterative splice sites. Additionally, we observed several introns with 2 BPs and one intron with 3 BPs. In the LSM2 transcript, we showed alternative BP usage was associated with alternative splice site usage, where one of the mRNA isoforms contains a premature termination codon and leads to nonsense-mediated mRNA decay of the transcript. This suggests AS may control gene expression levels in yeast as is known to be the case in metazoans. Preliminary application of our method to Drosophila melanogaster showed recursive splicing, a phenomenon known only to occur in introns larger than 10Kb, to occur in a 383nt intron. Thesis supervisor: Christopher B. Burge Title: Professor of Biology 3 Acknowledgements I’d like to begin by thanking my advisor, Chris Burge, for allowing me to join his lab and pursue a risky project that let me combine my desire to perform both experimental and computational biology research. The Burge lab has been a great environment for me to learn and grow. Thank you Chris for being receptive to my requests over the years, agreeing to meet with me regularly to discuss my research and allowing me to present my findings at several scientific venues. To my committee members, Phil Sharp and Tom RajBhandary, thank you for all of your helpful advice over the years. Also, Robin Reed, thank you for agreeing to serve on my thesis committee and for providing me with the HeLa Nuclear Extracts that were essential to the success of my research. Next, thank you to all the members of the Burge lab, past and present, who have made the lab a great environment for doing research. I appreciate all you have taught me through sharing your own knowledge of techniques and through your efforts critiquing my presentations and writing over the years. Special thanks to Nicole for encouraging me to purify yeast DBR1 protein which was the key to getting my protocol to work, to Athma for patiently helping me learn R, Alex, Jason, Noah, Charles, Maria, Peter F. and Peter S. for teaching me new Python tricks, Matt for insightful suggestions on ways to plot data, Eric for initial ideas pertaining to my project, Jess for talking some sense into me when trying to get last minute experiments to work the night before group meeting, Reut for helpful conversations over her late-morning breakfast in the dry lab, Joe for being always being upbeat and being a wonderfully motivated guy to work with, and to Jennifer, Dan, Caitlin, Razvan, Robin, Yarden, Albert, Rob, Vincent, Monica, Yevgenia, Chetan, Abby, Cassie, Ritu, Dima, Daniel, Phil, and Brad for making my time in the lab so memorable. Thank you to my collaborators Boris, Yuchun, and Joe for countless conversations and questions; they have been some of the best parts of grad school. I’d also like to thank all of my friends in the building, especially all of my 2nd and 3rd floor neighbors for making the lab a lively place to do science, providing moral support, and organizing fun extracurricular activities. Thank you to my classmates. It’s been great bouncing ideas off of you and it has been comforting to know I always have good friends nearby. I believe the bonds we have formed will last a lifetime and I look forward to learning of everyone’s future accomplishments. Also, thank you to my BBS friends. It’s been fun to observe the differences between the MIT and Harvard Biology PhD programs over the years and it’s been wonderful having more friends in the area who understand the time requirements of research. Also thank you to my roommates, past and present, who have always been there for me when I needed to unwind at the end of the day. Thanks to MIT’s extracurricular activities, I’ve been able to maintain a work-life balance. Thank you to the friendly staff and volunteers at the MIT Sailing Pavilion, members of the MIT Figure Skating Club, and volunteers at the MIT Rock Wall for creating positive outlets. 4 Thank you to my friends from home. Even though some of you admitted you probably wouldn’t understand what I was studying, you were always willing to give it a try and wanted to catch up anyway. Thank you to my college friends, especially the Cal Sailing Team, who still make the time to get together even though we are now scattered across the globe. And to those Cal Sailors whom I discuss scientific topics with from afar, I look forward to our future conversations about scientific breakthroughs, and what the general public thinks of them. Thank you to Mike Eisen for allowing me to experience what computational biology was all about first hand. If I hadn’t worked in your lab, I wouldn’t have come to grad school. Thank you to my additional mentors outside the lab, Kim Hamad-Schifferli, Frank Solomon, and Alan Grossman, who have provided me with valuable advice over the years. I would like to especially thank my best friend, Dr. Lauren Barclay, for always being there for me. As we both know, grad school can be trying at times, and having my best friend nearby, who was going through a PhD herself, was the best thing I could have asked for. Thanks for making time to catch up and getting me out of the lab to enjoy New England! I’d like to thank my high school biology teacher for instilling in me my love of biology. Mr. Van Loo was an excellent teacher who really worked hard to make the subject matter he was teaching interesting and memorable. I’ll never forget when he dressed up a hockey player to demonstrate the Calvin Cycle, bringing a puck of “carbon” in the open “stomata” door to show us where the carbon went and what happened to it once it entered the “cell” classroom, or the time when he had a student volunteer stand on a chair, hold a couple of branches, and try, to no avail, to drink water through a long straw from a water bottle on the floor to demonstrate why transpiration was important for plants to transport water from their roots to their branches. He made biology fun and accessible. It was also through his course that I learned about the UC Davis Young Scholars Program and ended up having my first of many research experiences. I’d like to thank my extended family in the Boston area that made Cambridge a home away from home for me. It’s been great spending time with you, especially since we lived so far apart while I was growing up. I’ve really enjoyed all of our great meals together, Red Sox games, trips to the Cape and other outings. Also, thank you for opening your home to me after the Boston Marathon bombing. A special thank you to the officers who protect MIT, especially Officer Sean Collier. To my grandparents, thank you for always wanting to hear about my latest endeavors. To my “little” brother, thanks for being born after me, you would have been a tough act to follow. I’ve enjoyed all of our fun East Coast visits and appreciate all your advice over the years.
Load more

Recommended publications
  • Molecular Basis for the Distinct Cellular Functions of the Lsm1-7 and Lsm2-8 Complexes
    bioRxiv preprint doi: https://doi.org/10.1101/2020.04.22.055376; this version posted April 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Molecular basis for the distinct cellular functions of the Lsm1-7 and Lsm2-8 complexes Eric J. Montemayor1,2, Johanna M. Virta1, Samuel M. Hayes1, Yuichiro Nomura1, David A. Brow2, Samuel E. Butcher1 1Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA. 2Department of Biomolecular Chemistry, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA. Correspondence should be addressed to E.J.M. ([email protected]) and S.E.B. ([email protected]). Abstract Eukaryotes possess eight highly conserved Lsm (like Sm) proteins that assemble into circular, heteroheptameric complexes, bind RNA, and direct a diverse range of biological processes. Among the many essential functions of Lsm proteins, the cytoplasmic Lsm1-7 complex initiates mRNA decay, while the nuclear Lsm2-8 complex acts as a chaperone for U6 spliceosomal RNA. It has been unclear how these complexes perform their distinct functions while differing by only one out of seven subunits. Here, we elucidate the molecular basis for Lsm-RNA recognition and present four high-resolution structures of Lsm complexes bound to RNAs. The structures of Lsm2-8 bound to RNA identify the unique 2′,3′ cyclic phosphate end of U6 as a prime determinant of specificity. In contrast, the Lsm1-7 complex strongly discriminates against cyclic phosphates and tightly binds to oligouridylate tracts with terminal purines.
    [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]
  • 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]
  • A Master Autoantigen-Ome Links Alternative Splicing, Female Predilection, and COVID-19 to Autoimmune Diseases
    bioRxiv preprint doi: https://doi.org/10.1101/2021.07.30.454526; this version posted August 4, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. A Master Autoantigen-ome Links Alternative Splicing, Female Predilection, and COVID-19 to Autoimmune Diseases Julia Y. Wang1*, Michael W. Roehrl1, Victor B. Roehrl1, and Michael H. Roehrl2* 1 Curandis, New York, USA 2 Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, USA * Correspondence: [email protected] or [email protected] 1 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.30.454526; this version posted August 4, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. Abstract Chronic and debilitating autoimmune sequelae pose a grave concern for the post-COVID-19 pandemic era. Based on our discovery that the glycosaminoglycan dermatan sulfate (DS) displays peculiar affinity to apoptotic cells and autoantigens (autoAgs) and that DS-autoAg complexes cooperatively stimulate autoreactive B1 cell responses, we compiled a database of 751 candidate autoAgs from six human cell types. At least 657 of these have been found to be affected by SARS-CoV-2 infection based on currently available multi-omic COVID data, and at least 400 are confirmed targets of autoantibodies in a wide array of autoimmune diseases and cancer.
    [Show full text]
  • Defining Essential Elements and Genetic Interactions of the Yeast
    Downloaded from rnajournal.cshlp.org on September 28, 2021 - Published by Cold Spring Harbor Laboratory Press 1 Defining essential elements and genetic interactions of the yeast Lsm2-8 ring and demonstration that essentiality of Lsm2-8 is bypassed via overexpression of U6 snRNA or the U6 snRNP subunit Prp24 Allen J. Roth1, Stewart Shuman2, and Beate Schwer1 1 Microbiology and Immunology Department, Weill Cornell Medical College, New York, NY 10065; and 2 Molecular Biology Program, Sloan-Kettering Institute, New York, NY 10065 correspondence: [email protected]; [email protected] Downloaded from rnajournal.cshlp.org on September 28, 2021 - Published by Cold Spring Harbor Laboratory Press 2 ABSTRACT A seven-subunit Lsm2-8 protein ring assembles on the U-rich 3' end of the U6 snRNA. A structure-guided mutational analysis of the Saccharomyces cerevisiae Lsm2-8 ring affords new insights to structure-function relations and genetic interactions of the Lsm subunits. Alanine scanning of 39 amino acids comprising the RNA-binding sites or inter-subunit interfaces of Lsm2, Lsm3, Lsm4, Lsm5, and Lsm8 identified only one instance of lethality (Lsm3-R69A) and one severe growth defect (Lsm2-R63A), both involving amino acids that bind the 3'-terminal UUU trinucleotide. All other Ala mutations were benign with respect to vegetative growth. Tests of 235 pairwise combinations of benign Lsm mutants identified six instances of inter-Lsm synthetic lethality and 45 cases of non-lethal synthetic growth defects. Thus, Lsm2-8 ring function is buffered by a network of internal genetic redundancies. A salient finding was that otherwise lethal single-gene deletions lsm2∆, lsm3∆, lsm4∆, lsm5, and lsm8∆ were rescued by overexpression of U6 snRNA from a high-copy plasmid.
    [Show full text]
  • Ontology Applications in Systems Biology: a Machine Learning Approach
    Ontology Applications in Systems Biology: a Machine Learning Approach by Elma Hussanna Akand Master of Information Technology, University of Queensland, Australia, 2001. BSc. Electrical & Electronic Engineering, Bangladesh University of Engineering & Technology, 1999. A thesis submitted in partial fulfillment for the degree of Doctor of Philosophy in the Faculty of Engineering School of Computer Science and Engineering The University of New South Wales July 2014 PLEASE TYPE THE UNIVERSITY OF NEW SOUTH WALES Thesis/Dissertation Sheet Surname or Family name: Akand First name: Elma Other name/s: Hussanna Abbreviation for degree as given in the University calendar : PhD School: School of Computer Science and Engineering Faculty: Faculty of Engineering Title: Ontology Applications in Systems Biology: a Machine Learning Approach Abstract 350 words maximum: (PLEASE TYPE) Biology is flooded with an overwhelming accumulation of data and biologists require methods to apply their knowledge to explain biological networks of interacting genes or proteins in comprehensible terms. Therefore the focus of modern bioinformatics has shifted towards systems-wide analysis to understand mechanisms such as those underlying important diseases. Knowledge acquisition from such exponentially growing, inherently noisy and unstructured data is only likely to be achieved by combining bioinformatics, machine learning and semantic technologies such as ontologies. The major contribution of this thesis is on novel ontology applications to integrate complex multi-relational data towards learning models of biological systems. First we examined machine learning using ontology annotations to integrate heterogeneous data on systems biology. A series of propositional learning tasks to learn predictive models of intra-cellular expression in cells showed that feature construction and selection improved performance.
    [Show full text]
  • A High-Throughput Approach to Uncover Novel Roles of APOBEC2, a Functional Orphan of the AID/APOBEC Family
    Rockefeller University Digital Commons @ RU Student Theses and Dissertations 2018 A High-Throughput Approach to Uncover Novel Roles of APOBEC2, a Functional Orphan of the AID/APOBEC Family Linda Molla Follow this and additional works at: https://digitalcommons.rockefeller.edu/ student_theses_and_dissertations Part of the Life Sciences Commons A HIGH-THROUGHPUT APPROACH TO UNCOVER NOVEL ROLES OF APOBEC2, A FUNCTIONAL ORPHAN OF THE AID/APOBEC FAMILY A Thesis Presented to the Faculty of The Rockefeller University in Partial Fulfillment of the Requirements for the degree of Doctor of Philosophy by Linda Molla June 2018 © Copyright by Linda Molla 2018 A HIGH-THROUGHPUT APPROACH TO UNCOVER NOVEL ROLES OF APOBEC2, A FUNCTIONAL ORPHAN OF THE AID/APOBEC FAMILY Linda Molla, Ph.D. The Rockefeller University 2018 APOBEC2 is a member of the AID/APOBEC cytidine deaminase family of proteins. Unlike most of AID/APOBEC, however, APOBEC2’s function remains elusive. Previous research has implicated APOBEC2 in diverse organisms and cellular processes such as muscle biology (in Mus musculus), regeneration (in Danio rerio), and development (in Xenopus laevis). APOBEC2 has also been implicated in cancer. However the enzymatic activity, substrate or physiological target(s) of APOBEC2 are unknown. For this thesis, I have combined Next Generation Sequencing (NGS) techniques with state-of-the-art molecular biology to determine the physiological targets of APOBEC2. Using a cell culture muscle differentiation system, and RNA sequencing (RNA-Seq) by polyA capture, I demonstrated that unlike the AID/APOBEC family member APOBEC1, APOBEC2 is not an RNA editor. Using the same system combined with enhanced Reduced Representation Bisulfite Sequencing (eRRBS) analyses I showed that, unlike the AID/APOBEC family member AID, APOBEC2 does not act as a 5-methyl-C deaminase.
    [Show full text]
  • Molecular Basis for the Distinct Cellular Functions of the Lsm1-7 and Lsm2-8 Complexes
    Downloaded from rnajournal.cshlp.org on October 3, 2021 - Published by Cold Spring Harbor Laboratory Press Molecular basis for the distinct cellular functions of the Lsm1-7 and Lsm2-8 complexes Eric J. Montemayor1,2, Johanna M. Virta1, Samuel M. Hayes1, Yuichiro Nomura1, David A. Brow2, Samuel E. Butcher1 1Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA. 2Department of Biomolecular Chemistry, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA. Correspondence should be addressed to E.J.M. ([email protected]) and S.E.B. ([email protected]). Abstract Eukaryotes possess eight highly conserved Lsm (like Sm) proteins that assemble into circular, heteroheptameric complexes, bind RNA, and direct a diverse range of biological processes. Among the many essential functions of Lsm proteins, the cytoplasmic Lsm1-7 complex initiates mRNA decay, while the nuclear Lsm2-8 complex acts as a chaperone for U6 spliceosomal RNA. It has been unclear how these complexes perform their distinct functions while differing by only one out of seven subunits. Here, we elucidate the molecular basis for Lsm-RNA recognition and present four high-resolution structures of Lsm complexes bound to RNAs. The structures of Lsm2-8 bound to RNA identify the unique 2′,3′ cyclic phosphate end of U6 as a prime determinant of specificity. In contrast, the Lsm1-7 complex strongly discriminates against cyclic phosphates and tightly binds to oligouridylate tracts with terminal purines. Lsm5 uniquely recognizes purine bases, explaining its divergent sequence relative to other Lsm subunits. Lsm1-7 loads onto RNA from the 3′ end and removal of the Lsm1 C-terminal region allows Lsm1-7 to scan along RNA, suggesting a gated mechanism for accessing internal binding sites.
    [Show full text]
  • Dramatically Reduced Spliceosome in Cyanidioschyzon Merolae
    Dramatically reduced spliceosome in PNAS PLUS Cyanidioschyzon merolae Martha R. Starka, Elizabeth A. Dunnb, William S. C. Dunna, Cameron J. Grisdalec, Anthony R. Danielea, Matthew R. G. Halsteada, Naomi M. Fastc, and Stephen D. Radera,b,1 aDepartment of Chemistry, University of Northern British Columbia, Prince George, BC, V2N 4Z9 Canada; and Departments of bBiochemistry and Molecular Biology, and cBotany, University of British Columbia, Vancouver, BC, V6T 1Z4 Canada Edited by Joan A. Steitz, Howard Hughes Medical Institute, Yale University, New Haven, CT, and approved February 9, 2015 (received for review September 1, 2014) The human spliceosome is a large ribonucleoprotein complex that C. merolae is an acidophilic, unicellular red alga that grows at catalyzes pre-mRNA splicing. It consists of five snRNAs and more temperatures of up to 56 °C (6). At 16.5 million base pairs, its than 200 proteins. Because of this complexity, much work has genome is similar in size to that of S. cerevisiae and contains focusedontheSaccharomyces cerevisiae spliceosome, viewed as a comparable number of genes; however only one tenth as many a highly simplified system with fewer than half as many splicing introns were annotated in C. merolae: 26 intron-containing factors as humans. Nevertheless, it has been difficult to ascribe genes, 0.5% of the genome (6). The small number of introns in a mechanistic function to individual splicing factors or even to dis- C. merolae raises the questions of whether the full complexity cern which are critical for catalyzing the splicing reaction. We have of the canonical splicing machinery has been maintained or C merolae identified and characterized the splicing machinery from the red alga whether .
    [Show full text]
  • Multiple Functional Interactions Between Components of the Lsm2–Lsm8 Complex, U6 Snrna, and the Yeast La Protein
    Copyright 2001 by the Genetics Society of America Multiple Functional Interactions Between Components of the Lsm2±Lsm8 Complex, U6 snRNA, and the Yeast La Protein Barbara K. Pannone, Sang Do Kim, Dennis A. Noe and Sandra L. Wolin Departments of Cell Biology and Molecular Biophysics and Biochemistry, Howard Hughes Medical Institute, Yale University School of Medicine, New Haven, Connecticut 06536 Manuscript received November 29, 2000 Accepted for publication February 13, 2001 ABSTRACT The U6 small nuclear ribonucleoprotein is a critical component of the eukaryotic spliceosome. The ®rst protein that binds the U6 snRNA is the La protein, an abundant phosphoprotein that binds the 3Ј end of many nascent small RNAs. A complex of seven Sm-like proteins, Lsm2±Lsm8, also binds the 3Ј end of U6 snRNA. A mutation within the Sm motif of Lsm8p causes Saccharomyces cerevisiae cells to require the La protein Lhp1p to stabilize nascent U6 snRNA. Here we describe functional interactions between Lhp1p, the Lsm proteins, and U6 snRNA. LSM2 and LSM4, but not other LSM genes, act as allele-speci®c, low-copy suppressors of mutations in Lsm8p. Overexpression of LSM2 in the lsm8 mutant strain increases the levels of both Lsm8p and U6 snRNPs. In the presence of extra U6 snRNA genes, LSM8 becomes dispensable for growth, suggesting that the only essential function of LSM8 is in U6 RNA biogenesis or function. Furthermore, deletions of LSM5, LSM6,orLSM7 cause LHP1 to become required for growth. Our experiments are consistent with a model in which Lsm2p and Lsm4p contact Lsm8p in the Lsm2±Lsm8 ring and suggest that Lhp1p acts redundantly with the entire Lsm2±Lsm8 complex to stabilize nascent U6 snRNA.
    [Show full text]
  • Integrative Framework for Identification of Key Cell Identity Genes Uncovers
    Integrative framework for identification of key cell PNAS PLUS identity genes uncovers determinants of ES cell identity and homeostasis Senthilkumar Cinghua,1, Sailu Yellaboinaa,b,c,1, Johannes M. Freudenberga,b, Swati Ghosha, Xiaofeng Zhengd, Andrew J. Oldfielda, Brad L. Lackfordd, Dmitri V. Zaykinb, Guang Hud,2, and Raja Jothia,b,2 aSystems Biology Section and dStem Cell Biology Section, Laboratory of Molecular Carcinogenesis, and bBiostatistics Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709; and cCR Rao Advanced Institute of Mathematics, Statistics, and Computer Science, Hyderabad, Andhra Pradesh 500 046, India Edited by Norbert Perrimon, Harvard Medical School and Howard Hughes Medical Institute, Boston, MA, and approved March 17, 2014 (received for review October 2, 2013) Identification of genes associated with specific biological pheno- (mESCs) for genes essential for the maintenance of ESC identity types is a fundamental step toward understanding the molecular resulted in only ∼8% overlap (8, 9), although many of the unique basis underlying development and pathogenesis. Although RNAi- hits in each screen were known or later validated to be real. The based high-throughput screens are routinely used for this task, lack of concordance suggest that these screens have not reached false discovery and sensitivity remain a challenge. Here we describe saturation (14) and that additional genes of importance remain a computational framework for systematic integration of published to be discovered. gene expression data to identify genes defining a phenotype of Motivated by the need for an alternative approach for iden- interest. We applied our approach to rank-order all genes based on tification of key cell identity genes, we developed a computa- their likelihood of determining ES cell (ESC) identity.
    [Show full text]
  • Defining Essential Elements and Genetic Interactions of the Yeast Lsm2–8 Ring and Demonstration That Essentiality of Lsm2–8
    Downloaded from rnajournal.cshlp.org on October 6, 2021 - Published by Cold Spring Harbor Laboratory Press Defining essential elements and genetic interactions of the yeast Lsm2–8 ring and demonstration that essentiality of Lsm2–8 is bypassed via overexpression of U6 snRNA or the U6 snRNP subunit Prp24 ALLEN J. ROTH,1 STEWART SHUMAN,2 and BEATE SCHWER1 1Microbiology and Immunology Department, Weill Cornell Medical College, New York, New York 10065, USA 2Molecular Biology Program, Sloan-Kettering Institute, New York, New York 10065, USA ABSTRACT A seven-subunit Lsm2–8 protein ring assembles on the U-rich 3′′′′′ end of the U6 snRNA. A structure-guided mutational analysis of the Saccharomyces cerevisiae Lsm2–8 ring affords new insights to structure–function relations and genetic interactions of the Lsm subunits. Alanine scanning of 39 amino acids comprising the RNA-binding sites or intersubunit interfaces of Lsm2, Lsm3, Lsm4, Lsm5, and Lsm8 identified only one instance of lethality (Lsm3-R69A) and one severe growth defect (Lsm2-R63A), both involving amino acids that bind the 3′′′′′-terminal UUU trinucleotide. All other Ala mutations were benign with respect to vegetative growth. Tests of 235 pairwise combinations of benign Lsm mutants identified six instances of inter-Lsm synthetic lethality and 45 cases of nonlethal synthetic growth defects. Thus, Lsm2–8 ring function is buffered by a network of internal genetic redundancies. A salient finding was that otherwise lethal single-gene deletions lsm2Δ, lsm3Δ, lsm4Δ, lsm5, and lsm8Δ were rescued by overexpression of U6 snRNA from a high-copy plasmid. Moreover, U6 overexpression rescued myriad lsmΔ lsmΔ double-deletions and lsmΔ lsmΔ lsmΔ triple-deletions.
    [Show full text]