Molecular Architecture of the 90S Small Subunit Pre-Ribosome
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The DEAD-Box RNA Helicase-Like Utp25 Is an SSU Processome Component
Downloaded from rnajournal.cshlp.org on September 25, 2021 - Published by Cold Spring Harbor Laboratory Press The DEAD-box RNA helicase-like Utp25 is an SSU processome component J. MICHAEL CHARETTE1,2 and SUSAN J. BASERGA1,2,3 1Department of Molecular Biophysics & Biochemistry, Yale University School of Medicine, New Haven, Connecticut 06520, USA 2Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, Connecticut 06520, USA 3Department of Genetics, Yale University School of Medicine, New Haven, Connecticut 06520, USA ABSTRACT The SSU processome is a large ribonucleoprotein complex consisting of the U3 snoRNA and at least 43 proteins. A database search, initiated in an effort to discover additional SSU processome components, identified the uncharacterized, conserved and essential yeast nucleolar protein YIL091C/UTP25 as one such candidate. The C-terminal DUF1253 motif, a domain of unknown function, displays limited sequence similarity to DEAD-box RNA helicases. In the absence of the conserved DEAD-box sequence, motif Ia is the only clearly identifiable helicase element. Since the yeast homolog is nucleolar and interacts with components of the SSU processome, we examined its role in pre-rRNA processing. Genetic depletion of Utp25 resulted in slowed growth. Northern analysis of pre-rRNA revealed an 18S rRNA maturation defect at sites A0,A1, and A2. Coimmunoprecipitation confirmed association with U3 snoRNA and with Mpp10, and with components of the t-Utp/UtpA, UtpB, and U3 snoRNP subcomplexes. Mutation of the conserved motif Ia residues resulted in no discernable temperature- sensitive or cold-sensitive growth defects, implying that this motif is dispensable for Utp25 function. -
Fibrillarin from Archaea to Human
Biol. Cell (2015) 107, 1–16 DOI: 10.1111/boc.201400077 Review Fibrillarin from Archaea to human Ulises Rodriguez-Corona*, Margarita Sobol†, Luis Carlos Rodriguez-Zapata‡, Pavel Hozak† and Enrique Castano*1 *Unidad de Bioquımica´ y Biologıa´ molecular de plantas, Centro de Investigacion´ Cientıfica´ de Yucatan,´ Colonia Chuburna´ de Hidalgo, Merida,´ Yucatan, Mexico, †Department of Biology of the Cell Nucleus, Institute of Molecular Genetics of the Academy of Sciences of the Czech Republic, Prague 14220, Czech Republic, and ‡Unidad de Biotecnologıa,´ Centro de Investigacion´ Cientıfica´ de Yucatan,´ Colonia Chuburna´ de Hidalgo, Merida,´ Yucatan, Mexico Fibrillarin is an essential protein that is well known as a molecular marker of transcriptionally active RNA polyme- rase I. Fibrillarin methyltransferase activity is the primary known source of methylation for more than 100 methylated sites involved in the first steps of preribosomal processing and required for structural ribosome stability. High expression levels of fibrillarin have been observed in several types of cancer cells, particularly when p53 levels are reduced, because p53 is a direct negative regulator of fibrillarin transcription. Here, we show fibrillarin domain conservation, structure and interacting molecules in different cellular processes as well as with several viral proteins during virus infection. Additional supporting information may be found in the online version of this article at the publisher’s web-site Introduction progression, senescence and biogenesis of small nu- The nucleolus is the largest visible structure inside clear RNA and tRNAs proliferation and many forms the cell nucleus. It exists both as a dynamic and sta- of stress response (Andersen et al., 2005; Hinsby ble region depending of the nature and amount of et al., 2006; Boisvert et al., 2007; Shaw and Brown, the molecules that it is made of. -
Bayesian Hierarchical Modeling of High-Throughput Genomic Data with Applications to Cancer Bioinformatics and Stem Cell Differentiation
BAYESIAN HIERARCHICAL MODELING OF HIGH-THROUGHPUT GENOMIC DATA WITH APPLICATIONS TO CANCER BIOINFORMATICS AND STEM CELL DIFFERENTIATION by Keegan D. Korthauer A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Statistics) at the UNIVERSITY OF WISCONSIN–MADISON 2015 Date of final oral examination: 05/04/15 The dissertation is approved by the following members of the Final Oral Committee: Christina Kendziorski, Professor, Biostatistics and Medical Informatics Michael A. Newton, Professor, Statistics Sunduz Kele¸s,Professor, Biostatistics and Medical Informatics Sijian Wang, Associate Professor, Biostatistics and Medical Informatics Michael N. Gould, Professor, Oncology © Copyright by Keegan D. Korthauer 2015 All Rights Reserved i in memory of my grandparents Ma and Pa FL Grandma and John ii ACKNOWLEDGMENTS First and foremost, I am deeply grateful to my thesis advisor Christina Kendziorski for her invaluable advice, enthusiastic support, and unending patience throughout my time at UW-Madison. She has provided sound wisdom on everything from methodological principles to the intricacies of academic research. I especially appreciate that she has always encouraged me to eke out my own path and I attribute a great deal of credit to her for the successes I have achieved thus far. I also owe special thanks to my committee member Professor Michael Newton, who guided me through one of my first collaborative research experiences and has continued to provide key advice on my thesis research. I am also indebted to the other members of my thesis committee, Professor Sunduz Kele¸s,Professor Sijian Wang, and Professor Michael Gould, whose valuable comments, questions, and suggestions have greatly improved this dissertation. -
Analysis of Gene Expression Data for Gene Ontology
ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION A Thesis Presented to The Graduate Faculty of The University of Akron In Partial Fulfillment of the Requirements for the Degree Master of Science Robert Daniel Macholan May 2011 ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION Robert Daniel Macholan Thesis Approved: Accepted: _______________________________ _______________________________ Advisor Department Chair Dr. Zhong-Hui Duan Dr. Chien-Chung Chan _______________________________ _______________________________ Committee Member Dean of the College Dr. Chien-Chung Chan Dr. Chand K. Midha _______________________________ _______________________________ Committee Member Dean of the Graduate School Dr. Yingcai Xiao Dr. George R. Newkome _______________________________ Date ii ABSTRACT A tremendous increase in genomic data has encouraged biologists to turn to bioinformatics in order to assist in its interpretation and processing. One of the present challenges that need to be overcome in order to understand this data more completely is the development of a reliable method to accurately predict the function of a protein from its genomic information. This study focuses on developing an effective algorithm for protein function prediction. The algorithm is based on proteins that have similar expression patterns. The similarity of the expression data is determined using a novel measure, the slope matrix. The slope matrix introduces a normalized method for the comparison of expression levels throughout a proteome. The algorithm is tested using real microarray gene expression data. Their functions are characterized using gene ontology annotations. The results of the case study indicate the protein function prediction algorithm developed is comparable to the prediction algorithms that are based on the annotations of homologous proteins. -
Essential Genes and Their Role in Autism Spectrum Disorder
University of Pennsylvania ScholarlyCommons Publicly Accessible Penn Dissertations 2017 Essential Genes And Their Role In Autism Spectrum Disorder Xiao Ji University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/edissertations Part of the Bioinformatics Commons, and the Genetics Commons Recommended Citation Ji, Xiao, "Essential Genes And Their Role In Autism Spectrum Disorder" (2017). Publicly Accessible Penn Dissertations. 2369. https://repository.upenn.edu/edissertations/2369 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/edissertations/2369 For more information, please contact [email protected]. Essential Genes And Their Role In Autism Spectrum Disorder Abstract Essential genes (EGs) play central roles in fundamental cellular processes and are required for the survival of an organism. EGs are enriched for human disease genes and are under strong purifying selection. This intolerance to deleterious mutations, commonly observed haploinsufficiency and the importance of EGs in pre- and postnatal development suggests a possible cumulative effect of deleterious variants in EGs on complex neurodevelopmental disorders. Autism spectrum disorder (ASD) is a heterogeneous, highly heritable neurodevelopmental syndrome characterized by impaired social interaction, communication and repetitive behavior. More and more genetic evidence points to a polygenic model of ASD and it is estimated that hundreds of genes contribute to ASD. The central question addressed in this dissertation is whether genes with a strong effect on survival and fitness (i.e. EGs) play a specific oler in ASD risk. I compiled a comprehensive catalog of 3,915 mammalian EGs by combining human orthologs of lethal genes in knockout mice and genes responsible for cell-based essentiality. -
The Nucleolus – a Gateway to Viral Infection? Brief Review
Arch Virol (2002) 147: 1077–1089 DOI 10.1007/s00705-001-0792-0 The nucleolus – a gateway to viral infection? Brief Review J. A. Hiscox School of Animal and Microbial Sciences, University of Reading, U.K. Received August 24, 2001; accepted December 26, 2001 Published online March 18, 2002, © Springer-Verlag 2002 Summary. A number of viruses and viral proteins interact with a dynamic sub- nuclear structure called the nucleolus. The nucleolus is present during interphase in mammalian cells and is the site of ribosome biogenesis, and has been implicated in controlling regulatory processes such as the cell cycle. Viruses interact with the nucleolus and its antigens; viral proteins co-localise with factors such as nucleolin, B23 and fibrillarin, and can cause their redistribution during infection. Viruses can use these components as part of their replication process, and also use the nucleolus as a site of replication itself. Many of these properties are not restricted to any particular type of virus or replication mechanism, and examples of these processes can be found in DNA, RNA and retroviruses. Evidence suggests that viruses may target the nucleolus and its components to favour viral transcription, translation and perhaps alter the cell cycle in order to promote virus replication. Autoimmunity to nucleolin and fibrillarin have been associated with a number of diseases, and by targeting the nucleolus and displacing nucleolar antigens, virus infection might play a role in the initiation of these conditions. Introduction The eukaryotic nucleus contains a number of domains or subcompartments, which include nucleoli, nuclear Cajal bodies, nuclear speckles, transcription and replica- tion foci, and chromosome territories [34]. -
Supp Material.Pdf
Simon et al. Supplementary information: Table of contents p.1 Supplementary material and methods p.2-4 • PoIy(I)-poly(C) Treatment • Flow Cytometry and Immunohistochemistry • Western Blotting • Quantitative RT-PCR • Fluorescence In Situ Hybridization • RNA-Seq • Exome capture • Sequencing Supplementary Figures and Tables Suppl. items Description pages Figure 1 Inactivation of Ezh2 affects normal thymocyte development 5 Figure 2 Ezh2 mouse leukemias express cell surface T cell receptor 6 Figure 3 Expression of EZH2 and Hox genes in T-ALL 7 Figure 4 Additional mutation et deletion of chromatin modifiers in T-ALL 8 Figure 5 PRC2 expression and activity in human lymphoproliferative disease 9 Figure 6 PRC2 regulatory network (String analysis) 10 Table 1 Primers and probes for detection of PRC2 genes 11 Table 2 Patient and T-ALL characteristics 12 Table 3 Statistics of RNA and DNA sequencing 13 Table 4 Mutations found in human T-ALLs (see Fig. 3D and Suppl. Fig. 4) 14 Table 5 SNP populations in analyzed human T-ALL samples 15 Table 6 List of altered genes in T-ALL for DAVID analysis 20 Table 7 List of David functional clusters 31 Table 8 List of acquired SNP tested in normal non leukemic DNA 32 1 Simon et al. Supplementary Material and Methods PoIy(I)-poly(C) Treatment. pIpC (GE Healthcare Lifesciences) was dissolved in endotoxin-free D-PBS (Gibco) at a concentration of 2 mg/ml. Mice received four consecutive injections of 150 μg pIpC every other day. The day of the last pIpC injection was designated as day 0 of experiment. -
DDX5 Targets Tissue-Specific Rnas to Promote Intestine Tumorigenesis
bioRxiv preprint doi: https://doi.org/10.1101/2020.03.25.006668; this version posted March 26, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. DDX5 targets tissue-specific RNAs to promote intestine tumorigenesis Nazia Abbasi1,4, Tianyun Long1,4, Yuxin Li1, Evelyn Ma1, Brian A. Yee1, Parth R. Patel1, Ibrahim M SayeD2, Nissi Varki2, Soumita Das2, PraDipta Ghosh1, 3, Gene W. Yeo1, WenDy J.M. Huang1,5 1 Department of Cellular anD Molecular MeDicine, University of California San Diego, La Jolla, CA 2 Department of Pathology, University of California San Diego, La Jolla, CA 3 Department of MeDicine, University of California San Diego, La Jolla, CA 4 These authors contributeD equally 5 CorresponDing author email: [email protected] Abstract Tumorigenesis in Different segments of the intestinal tract involves tissue-specific oncogenic Drivers. In the colon, complement component 3 (C3) activation is a major contributor to inflammation anD malignancies. By contrast, tumorigenesis in the small intestine involves fatty aciD-binding protein 1 (FABP1). However, little is known of the upstream mechanisms Driving their expressions in Different segments of the intestinal tract. Here, we report that an RNA binDing protein DDX5 augments C3 and FABP1 expressions post-transcriptionally to promote tumorigenesis in the colon anD small intestine, respectively. Mice with epithelial-specific knockout of DDX5 are protecteD from intestine tumorigenesis. The iDentification of DDX5 as the common upstream regulator of tissue-specific oncogenic molecules proviDes a new therapeutic target for intestine cancers. -
Mouse Utp15 Conditional Knockout Project (CRISPR/Cas9)
https://www.alphaknockout.com Mouse Utp15 Conditional Knockout Project (CRISPR/Cas9) Objective: To create a Utp15 conditional knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Utp15 gene (NCBI Reference Sequence: NM_178918 ; Ensembl: ENSMUSG00000041747 ) is located on Mouse chromosome 13. 13 exons are identified, with the ATG start codon in exon 2 and the TAA stop codon in exon 13 (Transcript: ENSMUST00000040972). Exon 3~4 will be selected as conditional knockout region (cKO region). Deletion of this region should result in the loss of function of the Mouse Utp15 gene. To engineer the targeting vector, homologous arms and cKO region will be generated by PCR using BAC clone RP23-267C22 as template. Cas9, gRNA and targeting vector will be co-injected into fertilized eggs for cKO Mouse production. The pups will be genotyped by PCR followed by sequencing analysis. Note: Exon 3 starts from about 5.74% of the coding region. The knockout of Exon 3~4 will result in frameshift of the gene. The size of intron 2 for 5'-loxP site insertion: 1332 bp, and the size of intron 4 for 3'-loxP site insertion: 1090 bp. The size of effective cKO region: ~862 bp. The cKO region does not have any other known gene. Page 1 of 7 https://www.alphaknockout.com Overview of the Targeting Strategy Wildtype allele gRNA region 5' gRNA region 3' 1 2 3 4 5 6 13 Targeting vector Targeted allele Constitutive KO allele (After Cre recombination) Legends Exon of mouse Utp15 Homology arm cKO region loxP site Page 2 of 7 https://www.alphaknockout.com Overview of the Dot Plot Window size: 10 bp Forward Reverse Complement Sequence 12 Note: The sequence of homologous arms and cKO region is aligned with itself to determine if there are tandem repeats. -
Kras Mutant Genetically Engineered Mouse Models of Human Cancers
Kras mutant genetically engineered mouse models of PNAS PLUS human cancers are genomically heterogeneous Wei-Jen Chunga,1,2, Anneleen Daemena,1, Jason H. Chengb, Jason E. Longb, Jonathan E. Cooperb, Bu-er Wangb, Christopher Tranb, Mallika Singhb,3, Florian Gnada,4, Zora Modrusanc, Oded Foremand, and Melissa R. Junttilab,5 aBioinformatics & Computational Biology, Genentech, Inc., South San Francisco, CA 94080; bTranslational Oncology, Genentech, Inc., South San Francisco, CA 94080; cMolecular Biology, Genentech, Inc., South San Francisco, CA 94080; and dPathology, Genentech, Inc., South San Francisco, CA 94080 Edited by Anton Berns, The Netherlands Cancer Institute, Amsterdam, The Netherlands, and approved November 6, 2017 (received for review May 23, 2017) KRAS mutant tumors are largely recalcitrant to targeted therapies. treatment susceptibility and tumor evolution under selective pres- Genetically engineered mouse models (GEMMs) of Kras mutant sure of drug therapy. cancer recapitulate critical aspects of this disease and are widely used for preclinical validation of targets and therapies. Through Results comprehensive profiling of exomes and matched transcriptomes Spontaneous Acquisition of Genomic Aberrations in KrasG12D-Initiated of >200 KrasG12D-initiated GEMM tumors from one lung and two GEMM Tumors. To better define the genomic landscape of estab- pancreatic cancer models, we discover that significant intratumoral lished Kras mutant tumor models, we focused on three models of and intertumoral genomic heterogeneity evolves during tumorigen- Kras mutant cancer: a nonsmall cell lung cancer (NSCLC) model esis. Known oncogenes and tumor suppressor genes, beyond those with adenovirus-induced expression of KrasG12D and homozygous engineered, are mutated, amplified, and deleted. Unlike human tu- p53 targeting (KP:KrasLSL.G12D/wt;p53frt/frt) (11, 13), and two models mors, the GEMM genomic landscapes are dominated by copy num- ber alterations, while protein-altering mutations are rare. -
The Genetic Basis for Individual Differences in Mrna Splicing and APOBEC1 Editing Activity in Murine Macrophages
The genetic basis for individual differences in mRNA splicing and APOBEC1 editing activity in murine macrophages The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Citation Hassan, M. A., V. Butty, K. D. C. Jensen, and J. P. J. Saeij. “The Genetic Basis for Individual Differences in mRNA Splicing and APOBEC1 Editing Activity in Murine Macrophages.” Genome Research 24, no. 3 (March 1, 2014): 377–389. As Published http://dx.doi.org/10.1101/gr.166033.113 Publisher Cold Spring Harbor Laboratory Press Version Final published version Citable link http://hdl.handle.net/1721.1/89091 Terms of Use Creative Commons Attribution-Noncommerical Detailed Terms http://creativecommons.org/licenses/by-nc/3.0/ Downloaded from genome.cshlp.org on August 27, 2014 - Published by Cold Spring Harbor Laboratory Press The genetic basis for individual differences in mRNA splicing and APOBEC1 editing activity in murine macrophages Musa A. Hassan, Vincent Butty, Kirk D.C. Jensen, et al. Genome Res. 2014 24: 377-389 originally published online November 18, 2013 Access the most recent version at doi:10.1101/gr.166033.113 Supplemental http://genome.cshlp.org/content/suppl/2014/01/07/gr.166033.113.DC1.html Material References This article cites 95 articles, 32 of which can be accessed free at: http://genome.cshlp.org/content/24/3/377.full.html#ref-list-1 Creative This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the Commons first six months after the full-issue publication date (see License http://genome.cshlp.org/site/misc/terms.xhtml). -
Utpa and Utpb Chaperone Nascent Pre-Ribosomal RNA and U3 Snorna to Initiate Eukaryotic Ribosome Assembly
ARTICLE Received 6 Apr 2016 | Accepted 27 May 2016 | Published 29 Jun 2016 DOI: 10.1038/ncomms12090 OPEN UtpA and UtpB chaperone nascent pre-ribosomal RNA and U3 snoRNA to initiate eukaryotic ribosome assembly Mirjam Hunziker1,*, Jonas Barandun1,*, Elisabeth Petfalski2, Dongyan Tan3, Cle´mentine Delan-Forino2, Kelly R. Molloy4, Kelly H. Kim5, Hywel Dunn-Davies2, Yi Shi4, Malik Chaker-Margot1,6, Brian T. Chait4, Thomas Walz5, David Tollervey2 & Sebastian Klinge1 Early eukaryotic ribosome biogenesis involves large multi-protein complexes, which co-transcriptionally associate with pre-ribosomal RNA to form the small subunit processome. The precise mechanisms by which two of the largest multi-protein complexes—UtpA and UtpB—interact with nascent pre-ribosomal RNA are poorly understood. Here, we combined biochemical and structural biology approaches with ensembles of RNA–protein cross-linking data to elucidate the essential functions of both complexes. We show that UtpA contains a large composite RNA-binding site and captures the 50 end of pre-ribosomal RNA. UtpB forms an extended structure that binds early pre-ribosomal intermediates in close proximity to architectural sites such as an RNA duplex formed by the 50 ETS and U3 snoRNA as well as the 30 boundary of the 18S rRNA. Both complexes therefore act as vital RNA chaperones to initiate eukaryotic ribosome assembly. 1 Laboratory of Protein and Nucleic Acid Chemistry, The Rockefeller University, New York, New York 10065, USA. 2 Wellcome Trust Centre for Cell Biology, University of Edinburgh, Michael Swann Building, Max Born Crescent, Edinburgh EH9 3BF, UK. 3 Department of Cell Biology, Harvard Medical School, Boston, Massachusetts 02115, USA.