Gene Expression Is a “Proxy” Measure for Transcription/Translation Events
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Systematic Analysis of Posttranscriptional Gene Expression Adam R
Advanced Review Systematic analysis of posttranscriptional gene expression Adam R. Morris,1 Neelanjan Mukherjee1 and Jack D. Keene1∗ Recent systems studies of gene expression have begun to dissect the layers of regulation that underlie the eukaryotic transcriptome, the combined consequence of transcriptional and posttranscriptional events. Among the regulatory layers of the transcriptome are those of the ribonome, a highly dynamic environment of ribonucleoproteins in which RNA-binding proteins (RBPs), noncoding regulatory RNAs (ncRNAs) and messenger RNAs (mRNAs) interact. While multiple mRNAs are coordinated together in groups within the ribonome of a eukaryotic cell, eachindividualtypeofmRNAconsistsofmultiplecopies,eachofwhichhas an opportunity to be a member of more than one modular group termed a posttranscriptional RNA operon or regulon (PTRO). The mRNAs associated with each PTRO encode functionally related proteins and are coordinated at the levels of RNA stability and translation by the actions of the specific RBPs and noncoding regulatory RNAs. This article examines the methods that led to the elucidation of PTROs and the coordinating mechanisms that appear to regulate the RNA components of PTROs. Moreover, the article considers the characteristics of the dynamic systems that drive PTROs and how mRNA components are bound collectively in physical ‘states’ to respond to cellular perturbations and diseases. In conclusion, these studies have challenged the extent to which cellular mRNA abundance can inform investigators of the functional -
Comparative Oncogenomics Identifies Tyrosine Kinase FES As a Tumor Suppressor in Melanoma
RESEARCH ARTICLE The Journal of Clinical Investigation Comparative oncogenomics identifies tyrosine kinase FES as a tumor suppressor in melanoma Michael Olvedy,1,2 Julie C. Tisserand,3 Flavie Luciani,1,2 Bram Boeckx,4,5 Jasper Wouters,6,7 Sophie Lopez,3 Florian Rambow,1,2 Sara Aibar,6,7 Bernard Thienpont,4,5 Jasmine Barra,1,2 Corinna Köhler,1,2 Enrico Radaelli,8 Sophie Tartare-Deckert,9 Stein Aerts,6,7 Patrice Dubreuil,3 Joost J. van den Oord,10 Diether Lambrechts,4,5 Paulo De Sepulveda,3 and Jean-Christophe Marine1,2 1Laboratory for Molecular Cancer Biology, Center for Cancer Biology, Vlaams Instituut voor Biotechnologie (VIB), Leuven, Belgium. 2Laboratory for Molecular Cancer Biology, Department of Oncology, KU Leuven, Leuven, Belgium. 3INSERM, Aix Marseille University, CNRS, Institut Paoli-Calmettes, CRCM, Equipe Labellisée Ligue Contre le Cancer, Marseille, France. 4Laboratory for Translational Genetics, Center for Cancer Biology, VIB, Leuven, Belgium. 5Laboratory for Translational Genetics, and 6Laboratory of Computational Biology, Department of Human Genetics, KU Leuven, Leuven, Belgium. 7Laboratory of Computational Biology, and 8Mouse Histopathology Core Facility, VIB Center for Brain & Disease Research, Leuven, Belgium. 9Centre Méditerranéen de Médecine Moléculaire (C3M), INSERM, U1065, Université Côte d’Azur, Nice, France. 10Laboratory of Translational Cell and Tissue Research, Department of Pathology, KU Leuven and UZ Leuven, Leuven, Belgium. Identification and functional validation of oncogenic drivers are essential steps toward -
Zinc Fingers and a Green Thumb: Manipulating Gene Expression in Plants Segal, Stege and Barbas 165
163 Zinc fingers and a green thumb: manipulating gene expression in plants David J Segaly, Justin T Stegez and Carlos F Barbas IIIç Artificial transcription factors can be rapidly constructed A variety of techniques have been developed to manip- from predefined zinc-finger modules to regulate virtually any ulate gene expression in plants. Increased expression of gene. Stable, heritable up- and downregulation of endogenous genes is most commonly achieved through endogenous genes has been demonstrated in transgenic transgene overexpression [1]. The introduction of tissue- plants. These advances promise new approaches for creating specific and inducible promoters has improved the utility functional knockouts and conditional overexpression, and of this approach, and efficient and robust plant transforma- for other gene discovery and manipulation applications in tion techniques have made the construction of transgenes plants. a relatively routine task. However, variable expression and co-suppression of transgenes often complicate this process. Addresses Furthermore, transgenes cannot accommodate alternative ÃThe Skaggs Institute for Chemical Biology and the Department of splicing, which may be important for the appropriate Molecular Biology, The Scripps Research Institute, La Jolla, function of some transgenes [2]. California 92037, USA yDepartment of Pharmacology and Toxicology, University of Arizona, Tucson, Arizona 85721, USA Reducing or eliminating the expression of a gene in plants zDiversa Corporation, San Diego, California 92121, USA is not as simple as overexpressing a gene. Gene disruption §The Scripps Research Institute, BCC-550, North Torrey Pines Road, by homologous recombination, tDNA insertions and che- La Jolla, California 92037, USA mical mutagenesis has been used successfully, but these e-mail: [email protected] Correspondence: Carlos F Barbas III approaches are inefficient and time-consuming technolo- gies. -
Systems Biology Lecture Outline (Systems Biology) Michael K
Spring 2019 – Epigenetics and Systems Biology Lecture Outline (Systems Biology) Michael K. Skinner – Biol 476/576 CUE 418, 10:35-11:50 am, Tuesdays & Thursdays January 22 & 29, 2019 Weeks 3 and 4 Systems Biology (Components & Technology) Components (DNA, Expression, Cellular, Organ, Physiology, Organism, Differentiation, Development, Phenotype, Evolution) Technology (Genomics, Transcriptomes, Proteomics) (Interaction, Signaling, Metabolism) Omics (Data Processing and Resources) Required Reading ENCODE (2012) ENCODE Explained. Nature 489:52-55. Tavassoly I, Goldfarb J, Iyengar R. (2018) Essays Biochem. 62(4):487-500. Literature Sundaram V, Wang T. Transposable Element Mediated Innovation in Gene Regulatory Landscapes of Cells: Re-Visiting the "Gene-Battery" Model. Bioessays. 2018 40(1). doi: 10.1002/bies.201700155. Abil Z, Ellefson JW, Gollihar JD, Watkins E, Ellington AD. Compartmentalized partnered replication for the directed evolution of genetic parts and circuits. Nat Protoc. 2017 Dec;12(12):2493- 2512. Filipp FV. Crosstalk between epigenetics and metabolism-Yin and Yang of histone demethylases and methyltransferases in cancer. Brief Funct Genomics. 2017 Nov 1;16(6):320-325. Chen Z, Li S, Subramaniam S, Shyy JY, Chien S. Epigenetic Regulation: A New Frontier for Biomedical Engineers. Annu Rev Biomed Eng. 2017 Jun 21;19:195-219. Hollick JB. Paramutation and related phenomena in diverse species. Nat Rev Genet. 2017 Jan;18(1):5-23. Macovei A, Pagano A, Leonetti P, Carbonera D, Balestrazzi A, Araújo SS. Systems biology and genome-wide approaches to unveil the molecular players involved in the pre-germinative metabolism: implications on seed technology traits. Plant Cell Rep. 2017 May;36(5):669-688. Bagchi DN, Iyer VR. -
The Human Proteome Co-Regulation Map Reveals Functional Relationships Between Proteins
bioRxiv preprint doi: https://doi.org/10.1101/582247; this version posted March 19, 2019. The copyright holder for this preprint (which was 19/03/2019not certified by peer review) is the author/funder, who hasNBT_manuscript_revised granted bioRxiv a license - toGoogle display Docs the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. 1 The human proteome co-regulation map reveals functional relationships 2 between proteins 3 Georg Kustatscher1 *, Piotr Grabowski2 *, Tina A. Schrader3 , Josiah B. Passmore3 , Michael 4 Schrader3 , Juri Rappsilber1,2# 5 1 Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh EH9 3BF, UK 6 2 Bioanalytics, Institute of Biotechnology, Technische Universität Berlin, 13355 Berlin, 7 Germany 8 3 Biosciences, University of Exeter, Exeter EX4 4QD, UK 9 * Equal contribution 10 # Communicating author: [email protected] 11 Submission as Resource article. 12 The annotation of protein function is a longstanding challenge of cell biology that 13 suffers from the sheer magnitude of the task. Here we present ProteomeHD, which 14 documents the response of 10,323 human proteins to 294 biological perturbations, 15 measured by isotope-labelling mass spectrometry. Using this data matrix and robust 16 machine learning we create a co-regulation map of the cell that reflects functional 17 associations between human proteins. The map identifies a functional context for 18 many uncharacterized proteins, including microproteins that are difficult to study with 19 traditional methods. Co-regulation also captures relationships between proteins 20 which do not physically interact or co-localize. For example, co-regulation of the 21 peroxisomal membrane protein PEX11β with mitochondrial respiration factors led us 22 to discover a novel organelle interface between peroxisomes and mitochondria in 23 mammalian cells. -
Rare Variants in the DNA Repair Pathway and the Risk of Colorectal Cancer Marco Matejcic1, Hiba A
Author Manuscript Published OnlineFirst on February 24, 2021; DOI: 10.1158/1055-9965.EPI-20-1457 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Rare variants in the DNA repair pathway and the risk of colorectal cancer Marco Matejcic1, Hiba A. Shaban1, Melanie W. Quintana2, Fredrick R. Schumacher3,4, Christopher K. Edlund5, Leah Naghi6, Rish K. Pai7, Robert W. Haile8, A. Joan Levine8, Daniel D. Buchanan9,10,11, Mark A. Jenkins12, Jane C. Figueiredo13, Gad Rennert14, Stephen B. Gruber15, Li Li16, Graham Casey17, David V. Conti18†, Stephanie L. Schmit1,19† † These authors contributed equally to this work. Affiliations 1 Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL 33612, USA 2 Berry Consultants, Austin, TX, 78746, USA 3 Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH 44106, USA 4 Seidman Cancer Center, University Hospitals, Cleveland, OH 44106, USA 5 Department of Preventive Medicine, USC Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA 6 Department of Medicine, Montefiore Medical Center, Albert Einstein College of Medicine, NY 10467, USA 7 Department of Laboratory Medicine and Pathology, Mayo Clinic Arizona, Scottsdale, AZ 85259, USA 8 Department of Medicine, Research Center for Health Equity, Cedars-Sinai Samuel Oschin Comprehensive Cancer Center, Los Angeles, CA 90048, USA 9 Colorectal Oncogenomics Group, Department of Clinical Pathology, The University of Melbourne, Parkville, Victoria 3010, Australia 10 Victorian Comprehensive Cancer Centre, University of Melbourne, Centre for Cancer Research, Parkville, Victoria 3010, Australia 1 Downloaded from cebp.aacrjournals.org on September 29, 2021. -
A Sleeping Beauty Mutagenesis Screen Reveals a Tumor Suppressor
A Sleeping Beauty mutagenesis screen reveals a tumor PNAS PLUS suppressor role for Ncoa2/Src-2 in liver cancer Kathryn A. O’Donnella,b,1,2, Vincent W. Kengc,d,e, Brian Yorkf, Erin L. Reinekef, Daekwan Seog, Danhua Fanc,h, Kevin A. T. Silversteinc,h, Christina T. Schruma,b, Wei Rose Xiea,b,3, Loris Mularonii,j, Sarah J. Wheelani,j, Michael S. Torbensonk, Bert W. O’Malleyf, David A. Largaespadac,d,e, and Jef D. Boekea,b,i,2 Departments of aMolecular Biology and Genetics, iOncology, jDivision of Biostatistics and Bioinformatics, and kPathology and bThe High Throughput Biology Center, The Johns Hopkins University School of Medicine, Baltimore, MD 21205; cMasonic Cancer Center, dDepartment of Genetics, Cell Biology, and Development, eCenter for Genome Engineering, and hBiostatistics and Bioinformatics Core, University of Minnesota, Minneapolis, MN 55455; fDepartment of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX 77030; and gLaboratory of Experimental Carcinogenesis, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892 Edited by Harold Varmus, National Cancer Institute, Bethesda, MD, and approved March 23, 2012 (received for review September 21, 2011) The Sleeping Beauty (SB) transposon mutagenesis system is a pow- alterations have been documented in liver cancer, the key genetic erful tool that facilitates the discovery of mutations that accelerate alterations that drive hepatocellular transformation remain tumorigenesis. In this study, we sought to identify mutations that poorly understood. Nevertheless, a unifying feature of human cooperate with MYC, one of the most commonly dysregulated HCC is amplification or overexpression of the MYC oncogene (8, genes in human malignancy. -
In-Cell Architecture of an Actively Transcribing-Translating Expressome
bioRxiv preprint doi: https://doi.org/10.1101/2020.02.28.970111; this version posted February 28, 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. In-cell architecture of an actively transcribing-translating expressome Francis J. O’Reilly1, †, Liang Xue2,3, †, Andrea Graziadei1, †, Ludwig Sinn1, Swantje Lenz1, 5 Dimitry Tegunov4, Cedric Blötz5, Wim J. H. Hagen2, Patrick Cramer4, Jörg Stülke5, Julia Mahamid2,*, Juri Rappsilber1,6,* Affiliations: 1 Bioanalytics, Institute of Biotechnology, Technische Universität Berlin, 13355 Berlin, 10 Germany 2 Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), Meyerhofstraße 1, 69117 Heidelberg, Germany. 3 Collaboration for joint PhD degree between EMBL and Heidelberg University, Faculty of Biosciences 15 4 Department of Molecular Biology, Max-Planck-Institute for Biophysical Chemistry, Am Faßberg 11, 37077, Göttingen, Germany 5 Department of General Microbiology, Institute of Microbiology and Genetics, GZMB, Georg- August-University Göttingen, Grisebachstraße 8, 37077 Göttingen, Germany 6 Wellcome Centre for Cell Biology, University of Edinburgh, Max Born Crescent, Edinburgh, 20 EH9 3BF, UK *Correspondence to: [email protected], [email protected] †These authors contributed equally to this work. 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.02.28.970111; this version posted February 28, 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. -
Oncogenomics: Clinical Pathogenesis Approach
International Journal of Genetics, ISSN: 0975–2862, Volume 1, Issue 2, 2009, pp-25-43 Oncogenomics: Clinical pathogenesis approach Gupta G. 1, Gupta N. 2, Trivedi S. 3, Patil P. 5, Gupta M. 2, Jhadav A. 4, Vamsi K.K.6, Khairnar Y. 4, Boraste A. 4, Mujapara A.K. 7, Joshi B.8 1S.D.S.M. College Palghar, Mumbai 2Sindhu Mahavidyalaya Panchpaoli Nagpur 3V.V.P. Engineering College, Rajkot, Gujrat 4Padmashree Dr. D.Y. Patil University, Navi Mumbai, 400614, India 5Dr. D. Y. Patil ACS College, Pimpri, Pune 6Rai foundations College CBD Belapur Navi Mumbai 7Sir PP Institute of Science, Bhavnagar 8Rural College of Pharmacy, D.S Road, Bevanahalli, Banglore Abstract - Oncogenomics is new research sub-field of genomics, which applies high throughput technologies to characterize genes associated with cancer and synonymous with cancer genomics. The goal of oncogenomics is to identify new oncogenes or tumor suppressor genes that may provide new insights into cancer diagnosis, predicting clinical outcome of cancers, and new targets for cancer therapies. Oncoproteomics is the term used to describe the application of proteomic technologies in oncology and parallels the related field of oncogenomics. It is now contributing to the development of personalized management of cancer. Genomics has generated a wealth of data that is now being used to identify additional molecular alterations associated with cancer development. Mapping these alterations in the cancer genome is a critical first step in dissecting oncological pathways. Keywords - Biomarkers, Drug development, Drug resistance, Gene therapy, Oncogenomics Introduction Oncogenomics applies high throughput technologies to characterize genes associated transducing cellular signals of cell growth or with cancer and is used to identify new death. -
Chapter 12 Gene Expression and Regulation
PYF12 3/21/05 8:04 PM Page 191 Chapter 12 Gene expression and regulation Bacterial genomes usually contain several thousand different genes. Some of the gene products are required by the cell under all growth conditions and are called house- keeping genes. These include the genes that encode such proteins as DNA poly- merase, RNA polymerase, and DNA gyrase. Many other gene products are required under specific growth conditions. These include enzymes that synthesize amino acids, break down specific sugars, or respond to a specific environmental condition such as DNA damage. Housekeeping genes must be expressed at some level all of the time. Frequently, as the cell grows faster, more of the housekeeping gene products are needed. Even under very slow growth, some of each housekeeping gene product is made. The gene prod- ucts required for specific growth conditions are not needed all of the time. These genes are frequently expressed at extremely low levels, or not expressed at all when they are not needed and yet made when they are needed. This chapter will examine gene regulation or how bacteria regulate the expression of their genes so that the genes that are being expressed meet the needs of the cell for a specific growth condition. Gene regulation can occur at three possible places in the production of an active gene product. First, the transcription of the gene can be regulated. This is known as transcriptional regulation. When the gene is transcribed and how much it is transcribed influences the amount of gene product that is made. Second, if the gene encodes a protein, it can be regulated at the translational level. -
Gene Expression: Layers of Gene Regulation
RESEARCH HIGHLIGHTS GENE EXPRESSION methylation. Spearman’s rank cor- relation between methylation levels Layers of gene regulation (within 50 kb on either side of the transcription start site) and alterna- A new study investigates genetic and expression and DNA methylation lev- tive splicing levels show that, for epigenetic influences on genome els often overlap functional elements. many of the genes tested, there is a regulation and alternative splicing, Across cell types, expression quantita- significant association. Of note, many and highlights the tissue specificity of tive trait loci (eQTLs) are enriched in of the associations between DNA some of these interactions. DNase I-hypersensitive sites, whereas methylation and alternative splicing In a previous study, the researchers methylation QTLs (mQTLs) are are cell type-specific, illustrating examined the relationship between enriched in enhancers and insulators. another layer of cellular variability. genetic variation, DNA methyation Their statistical analyses show that, A complex relationship between and gene expression using samples generally, genetic variation has a more DNA methylation and gene expres- from the GenCord cohort that were consistent effect on gene expres- sion is beginning to emerge. This derived from umbilical cords of 204 sion across cell types, although the study further defines the roles of newborn children. They genotyped strength of the effect can be variable. genomic and epigenomic variation 2.5 million single-nucleotide poly- However, the effects of epigenetic in determining cellular phenotypes, morphisms (SNPs), assayed the meth- variation on gene expression are more and the mechanisms by which these ylation levels of 482,421 CpG sites tissue-specific. Methylation sites effects might occur. -
How Are Protein Products Made from a Gene?
How are protein products made from a gene? Copyright 2016 by the Rector and Visitors of the University of Virginia How are protein products made from a gene? Step 1: Deoxyribonucleic acid (DNA) is stored within the compartment of the cell called the nucleus. Nucleus DNA is a sequence made up of building blocks called nucleotides (more information can be found DNA in “What is some basic information about DNA?”). RNA When a gene is expressed, the DNA opens up and is transcribed into RNA; this step is called transcription. Cytoplasm Copyright 2016 by the Rector and Visitors of the University of Virginia How are protein products made from a gene? Step 2: Nucleus Ribonucleic acid (RNA) is created from transcribing DNA. DNA The RNA is exported from the nucleus into RNA the large compartment of the cell called the cytoplasm. A structure called the ribosome will read the RNA sequence; this step is called translation. protein ribosome In this step, an amino acid sequence will be Cytoplasm generated. There are 20 amino acids used to make proteins (more details about DNA, RNA and amino acids can be found in “What is some basic information about DNA?”, “What is transcription?” and “What is translation?”). Copyright 2016 by the Rector and Visitors of the University of Virginia How are protein products made from a gene? Nucleus Step 3: Once the amino acid sequence is DNA generated, the molecule will fold into a three-dimensional (3-D) RNA structure. The protein may go through other processing, but essentially is ready protein to perform its function.