Transcription Control Region Within the Protein-Coding Portion of Adenovirus Ela Genes TIMOTHY F
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Transcription BIOL201 Daniel Gautheret [email protected] • Chapitre 1: Transcription et RNA polymérase • Chapitre 2: Initiation, élongation et terminaison • Chapitre 3: Régulation: l’exemple procaryote • Chapitre 4: Maturation de l’ARN chez les eucaryotes V. 2012.0 Chapitre 1 Transcription et RNA polymérase 2 L’intuition de la transcription Chez les eucaryotes: ADN dans le noyau Machinerie de synthèse dans le cytoplasme Hypothèse d’un l’intermédiaire ARN 3 Etapes-clé de la découverte de l’ARN messager • 1957: concept d’un « adaptateur ARN » (Crick) • 1956-57: Découverte progressive d’une nouvelle fraction d’ARN, polymorphe • 1959-60: découverte d’une « ARN polymérase » capable de synthétiser de l’ARN à partir d’ADN. • 1961. Mise au point des techniques d’hybridation ADN- ARN sur filtre de nitrocellulose. -> l’ARN est complémentaire d’un seul brin d’ADN • 1961. Démonstration de l’existence d’un ARN messager (Jacob & Monod) • 1961. Purification d’ARN polymérase bactérienne et synthèse in vitro d’ARN à partir de matrice ADN 4 Rappel: différences ADN/ARN ARN ADN ribose désoxyribose 5 Bases de l’ADN et de l’ARN Base puriques ADN: T ARN: U Base pyrimidiques 6 Structure des ARN • Molécule ordonnée linéaire O • Orientée 5’P->3’OH P • Grand nombre de O H2C structures secondaires possibles 7 Décodage du gène dans la cellule bactérienne ADN ARN polymérase Ribosome grande sous-Unité ribosome ARNm Ribosome petite sous-Unité Protéine ARNr ARNt aminoacides Membrane cellulaire 8 Les principaux ARN dans une bactérie • ARN ribosomiques (ARNr) -
Insights Into Comparative Genomics, Codon Usage Bias, And
plants Article Insights into Comparative Genomics, Codon Usage Bias, and Phylogenetic Relationship of Species from Biebersteiniaceae and Nitrariaceae Based on Complete Chloroplast Genomes Xiaofeng Chi 1,2 , Faqi Zhang 1,2 , Qi Dong 1,* and Shilong Chen 1,2,* 1 Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810008, China; [email protected] (X.C.); [email protected] (F.Z.) 2 Qinghai Provincial Key Laboratory of Crop Molecular Breeding, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810008, China * Correspondence: [email protected] (Q.D.); [email protected] (S.C.) Received: 29 October 2020; Accepted: 17 November 2020; Published: 18 November 2020 Abstract: Biebersteiniaceae and Nitrariaceae, two small families, were classified in Sapindales recently. Taxonomic and phylogenetic relationships within Sapindales are still poorly resolved and controversial. In current study, we compared the chloroplast genomes of five species (Biebersteinia heterostemon, Peganum harmala, Nitraria roborowskii, Nitraria sibirica, and Nitraria tangutorum) from Biebersteiniaceae and Nitrariaceae. High similarity was detected in the gene order, content and orientation of the five chloroplast genomes; 13 highly variable regions were identified among the five species. An accelerated substitution rate was found in the protein-coding genes, especially clpP. The effective number of codons (ENC), parity rule 2 (PR2), and neutrality plots together revealed that the codon usage bias is affected by mutation and selection. The phylogenetic analysis strongly supported (Nitrariaceae (Biebersteiniaceae + The Rest)) relationships in Sapindales. Our findings can provide useful information for analyzing phylogeny and molecular evolution within Biebersteiniaceae and Nitrariaceae. -
Mutation Bias Shapes Gene Evolution in Arabidopsis Thaliana
bioRxiv preprint doi: https://doi.org/10.1101/2020.06.17.156752; this version posted June 18, 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 4.0 International license. Mutation bias shapes gene evolution in Arabidopsis thaliana 1,2† 1 1 3,4 Monroe, J. Grey , Srikant, Thanvi , Carbonell-Bejerano, Pablo , Exposito-Alonso, Moises , 5 6 7 1† Weng, Mao-Lun , Rutter, Matthew T. , Fenster, Charles B. , Weigel, Detlef 1 Department of Molecular Biology, Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany 2 Department of Plant Sciences, University of California Davis, Davis, CA 95616, USA 3 Department of Plant Biology, Carnegie Institution for Science, Stanford, CA 94305, USA 4 Department of Biology, Stanford University, Stanford, CA 94305, USA 5 Department of Biology, Westfield State University, Westfield, MA 01086, USA 6 Department of Biology, College of Charleston, SC 29401, USA 7 Department of Biology and Microbiology, South Dakota State University, Brookings, SD 57007, USA † corresponding authors: [email protected], [email protected] Classical evolutionary theory maintains that mutation rate variation between genes should be random with respect to fitness 1–4 and evolutionary optimization of genic 3,5 mutation rates remains controversial . However, it has now become known that cytogenetic (DNA sequence + epigenomic) features influence local mutation probabilities 6 , which is predicted by more recent theory to be a prerequisite for beneficial mutation 7 rates between different classes of genes to readily evolve . To test this possibility, we used de novo mutations in Arabidopsis thaliana to create a high resolution predictive model of mutation rates as a function of cytogenetic features across the genome. -
Chapter 3. the Beginnings of Genomic Biology – Molecular
Chapter 3. The Beginnings of Genomic Biology – Molecular Genetics Contents 3. The beginnings of Genomic Biology – molecular genetics 3.1. DNA is the Genetic Material 3.6.5. Translation initiation, elongation, and termnation 3.2. Watson & Crick – The structure of DNA 3.6.6. Protein Sorting in Eukaryotes 3.3. Chromosome structure 3.7. Regulation of Eukaryotic Gene Expression 3.3.1. Prokaryotic chromosome structure 3.7.1. Transcriptional Control 3.3.2. Eukaryotic chromosome structure 3.7.2. Pre-mRNA Processing Control 3.3.3. Heterochromatin & Euchromatin 3.4. DNA Replication 3.7.3. mRNA Transport from the Nucleus 3.4.1. DNA replication is semiconservative 3.7.4. Translational Control 3.4.2. DNA polymerases 3.7.5. Protein Processing Control 3.4.3. Initiation of replication 3.7.6. Degradation of mRNA Control 3.4.4. DNA replication is semidiscontinuous 3.7.7. Protein Degradation Control 3.4.5. DNA replication in Eukaryotes. 3.8. Signaling and Signal Transduction 3.4.6. Replicating ends of chromosomes 3.8.1. Types of Cellular Signals 3.5. Transcription 3.8.2. Signal Recognition – Sensing the Environment 3.5.1. Cellular RNAs are transcribed from DNA 3.8.3. Signal transduction – Responding to the Environment 3.5.2. RNA polymerases catalyze transcription 3.5.3. Transcription in Prokaryotes 3.5.4. Transcription in Prokaryotes - Polycistronic mRNAs are produced from operons 3.5.5. Beyond Operons – Modification of expression in Prokaryotes 3.5.6. Transcriptions in Eukaryotes 3.5.7. Processing primary transcripts into mature mRNA 3.6. Translation 3.6.1. -
Molecular Biology, Third Edition Neuroscience, Second Edition Plant Biology, Second Edition Sport & Exercise Biomechanics Sport & Exercise Physiology
Molecular Biology Third Edition ii Section K – Lipid metabolism BIOS INSTANT NOTES Series Editor: B.D. Hames, School of Biochemistry and Microbiology, University of Leeds, Leeds, UK Biology Animal Biology, Second Edition Biochemistry, Third Edition Bioinformatics Chemistry for Biologists, Second Edition Developmental Biology Ecology, Second Edition Genetics, Second Edition Immunology, Second Edition Mathematics & Statistics for Life Scientists Medical Microbiology Microbiology, Second Edition Molecular Biology, Third Edition Neuroscience, Second Edition Plant Biology, Second Edition Sport & Exercise Biomechanics Sport & Exercise Physiology Chemistry Consulting Editor: Howard Stanbury Analytical Chemistry Inorganic Chemistry, Second Edition Medicinal Chemistry Organic Chemistry, Second Edition Physical Chemistry Psychology Sub-series Editor: Hugh Wagner, Dept of Psychology, University of Central Lancashire, Preston, UK Cognitive Psychology Physiological Psychology Psychology Sport & Exercise Psychology Molecular Biology Third Edition Phil Turner, Alexander McLennan, Andy Bates & Mike White School of Biological Sciences, University of Liverpool, Liverpool, UK Published by: Taylor & Francis Group In US: 270 Madison Avenue New York, NY 10016 In UK: 4 Park Square, Milton Park Abingdon, OX14 4RN © 2005 by Taylor & Francis Group This edition published in the Taylor & Francis e-Library, 2007. “To purchase your own copy of this or any of Taylor & Francis or Routledge’s collection of thousands of eBooks please go to www.eBookstore.tandf.co.uk.” First edition published in 1997 Second edition published in 2000 Third edition published in 2005 ISBN 0–203–96732–1 Master e-book ISBN ISBN: 0-415-35167-7 (Print Edition) This book contains information obtained from authentic and highly regarded sources. Reprinted material is quoted with permission, and sources are indicated. -
"The" Genetic Code?
Evolutionary Anthropology 14:6–11 (2005) CROTCHETS & QUIDDITIES “The” Genetic Code? KENNETH M. WEISS AND ANNE V. BUCHANAN The DNA-based code for protein through messenger and transfer RNA is widely themselves, that carry the informa- regarded as the code of life. But genomes are littered with other kinds of coding tion. elements as well, and all of them probably came after a supercode for the tRNA Your life depends on the fidelity of system itself. these many codes. Aberrant codes re- lated to cell behavior can lead to dys- genesis or various metabolic diseases. Evolution and the diversification of Everyone knows of “the” genetic Anomalous cell-surface proteins can organisms are made possible by code, by which nucleotide triplets in cause autoimmune destruction, and vi- codes, or arbitrary assignments of DNA in the nucleus of cells specify the ruses are the Alan Turings of life that “meaning,” in multiple ways. Many amino acid (aa) sequence of proteins. evolve ways to break their receptor are not widely appreciated. Codes al- This is the code described in text- codes to gain illicit entry into cells (Fig. low the same system of components books as the heart of the genetic the- 1). to be used for multiple purposes. ory of life and its evolution. Discover- But there is an additional code, a These can be open-ended, the way the ies in recent years have made things code of codes, that makes all of this alphabet and vocabulary make this more complicated by showing that ge- possible, including “the” genetic code column possible, but the flexibility of nomes are littered with all sorts of itself, and may be the oldest and most a code can become constrained once a other kinds of coding elements. -
Designing Lentiviral Vectors for Gene Therapy of Genetic Diseases
viruses Review Designing Lentiviral Vectors for Gene Therapy of Genetic Diseases Valentina Poletti 1,2,3,* and Fulvio Mavilio 4 1 Department of Woman and Child Health, University of Padua, 35128 Padua, Italy 2 Harvard Medical School, Harvard University, Boston, MA 02115, USA 3 Pediatric Research Institute City of Hope, 35128 Padua, Italy 4 Department of Life Sciences, University of Modena and Reggio Emilia, 41125 Modena, Italy; [email protected] * Correspondence: [email protected] Abstract: Lentiviral vectors are the most frequently used tool to stably transfer and express genes in the context of gene therapy for monogenic diseases. The vast majority of clinical applications involves an ex vivo modality whereby lentiviral vectors are used to transduce autologous somatic cells, ob- tained from patients and re-delivered to patients after transduction. Examples are hematopoietic stem cells used in gene therapy for hematological or neurometabolic diseases or T cells for immunotherapy of cancer. We review the design and use of lentiviral vectors in gene therapy of monogenic diseases, with a focus on controlling gene expression by transcriptional or post-transcriptional mechanisms in the context of vectors that have already entered a clinical development phase. Keywords: lentiviral vectors; transcriptional regulation; post-transcriptional regulation; miRNA; promoters; retroviral integration; ex vivo gene therapy Citation: Poletti, V.; Mavilio, F. 1. Introduction Designing Lentiviral Vectors for Gene Therapy of Genetic Diseases. -
Analysis of Codon Usage Patterns in Giardia Duodenalis Based on Transcriptome Data from Giardiadb
G C A T T A C G G C A T genes Article Analysis of Codon Usage Patterns in Giardia duodenalis Based on Transcriptome Data from GiardiaDB Xin Li, Xiaocen Wang, Pengtao Gong, Nan Zhang, Xichen Zhang and Jianhua Li * Key Laboratory of Zoonosis Research, Ministry of Education, College of Veterinary Medicine, Jilin University, Changchun 130062, China; [email protected] (X.L.); [email protected] (X.W.); [email protected] (P.G.); [email protected] (N.Z.); [email protected] (X.Z.) * Correspondence: [email protected]; Tel.: +86-431-8783-6172; Fax: +86-431-8798-1351 Abstract: Giardia duodenalis, a flagellated parasitic protozoan, the most common cause of parasite- induced diarrheal diseases worldwide. Codon usage bias (CUB) is an important evolutionary character in most species. However, G. duodenalis CUB remains unclear. Thus, this study analyzes codon usage patterns to assess the restriction factors and obtain useful information in shaping G. duo- denalis CUB. The neutrality analysis result indicates that G. duodenalis has a wide GC3 distribution, which significantly correlates with GC12. ENC-plot result—suggesting that most genes were close to the expected curve with only a few strayed away points. This indicates that mutational pressure and natural selection played an important role in the development of CUB. The Parity Rule 2 plot (PR2) result demonstrates that the usage of GC and AT was out of proportion. Interestingly, we identified 26 optimal codons in the G. duodenalis genome, ending with G or C. In addition, GC content, gene expression, and protein size also influence G. -
Transcription and Open Reading Frame
Transcription The expression of genetic information stored in the DNA sequence starts with synthesis of the RNA copy of the gene in a process called transcription. The RNA copy of the gene is called messenger RNA (mRNA). A special enzyme, RNA polymerase, recognizes a sequence, called promoter, on the DNA double helix upstream from the protein coding sequence. RNA polymerase binds to the promoter and opens it up: separates the complementary strands at about 12-nt-long region of the promoter. Then the enzyme starts the mRNA synthesis using all 4 NTPs. The DNA strand, which is used as a template by RNA polymerase, is called the template or antisense strand. The opposite strand of the gene, which sequence is identical to the sequence of mRNA (except the substitution T U, of course), is called the coding or sense strand. There is also a special sequence after the end of the gene, which signals to RNA polymerase to terminate the mRNA synthesis. Thus synthesized mRNA molecule, which includes the protein coding region flanked by short unrelated sequences from both sides, is either translated by the ribosome into the protein molecule at the spot (in case of prokaryotes) or is transported from the nucleus to the cytoplasm (in case of eukaryotes) and there it is translated by the ribosome. Open Reading Frame (ORF) Since the genetic code is triplet, three reading frames are possible for the same mRNA molecule. For instance, the sequence: …..AUUGCCUAACCCUUAGGG…. can be separated into triplets by three possible ways: ….AUUGCCUAACCCUUAGGG…. ….AUUGCCUAACCCUUAGGG…. ….AUUGCCUAACCCUUAGGG…. The frame, in which no stop codons are encountered, is called the Open Reading Frame (ORF). -
Retl-1, a Yeast Mutant Affecting Transcription Termination by RNA Polymerase I11
Copyright 0 1990 by the Genetics Societyof America retl-1, a Yeast Mutant Affecting Transcription Termination by RNA Polymerase I11 Philip Jamesand Benjamin D. Hall Department of Genetics, SK-50,University of Washington, Seattle, WA 98195 Manuscript received December 8, 1989 Accepted for publication February 27, 1990 ABSTRACT In eukaryotes, extended tractsof T residues are known to signal the termination of RNA polymerase 111 transcription. However, it is not understood how the transcription complex interacts with this signal. We have developed a selection system in yeast that uses ochre suppressors weakenedby altered transcription termination signals to identify mutations in the proteins involved in termination of transcription by RNA polymerase 111. Over 7600 suppression-plus yeast mutants were selected and screened, leading to the identification of one whose effect is mediated transcriptionally. The retl-1 mutation arose in conjunction withmultiple rare events, including uninduced sporulation, gene amplification, and mutation.In vitro transcription extracts from retl-1 cells terminate less efficiently at weak transcriptiontermination signals than thosefrom RET1 cells,using a varietyof tRNA templates. In vivo this reduced termination efficiency can lead to either an increase or a further decrease in suppressor strength, depending on the location of the altered terminationsignal present in the suppressor tRNA gene. Fractionationof in vitro transcription extracts and purificationof RNA polymerase I11 has shown that the mutant effect is mediated byhighly purified polymerase in a reconstituted system. N eukaryotic cells, RNA polymerase I11 is respon- imum of six is required (ALLISONand HALL 1985). I sible forthe transcriptionof tRNA genes, the Sequences surrounding the T tract also affect termi- genes for 5s RNA, and those for a number of other nation (BOGENHAGENand BROWN198 1 ; MAZABRAUD low molecular weight RNAs of the nucleus and cyto- et al. -
Codon Usage Biases Co-Evolve with Transcription Termination Machinery
RESEARCH ARTICLE Codon usage biases co-evolve with transcription termination machinery to suppress premature cleavage and polyadenylation Zhipeng Zhou1†, Yunkun Dang2,3†*, Mian Zhou4, Haiyan Yuan1, Yi Liu1* 1Department of Physiology, The University of Texas Southwestern Medical Center, Dallas, United States; 2State Key Laboratory for Conservation and Utilization of Bio- Resources in Yunnan, Yunnan University, Kunming, China; 3Center for Life Science, School of Life Sciences, Yunnan University, Kunming, China; 4State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, China Abstract Codon usage biases are found in all genomes and influence protein expression levels. The codon usage effect on protein expression was thought to be mainly due to its impact on translation. Here, we show that transcription termination is an important driving force for codon usage bias in eukaryotes. Using Neurospora crassa as a model organism, we demonstrated that introduction of rare codons results in premature transcription termination (PTT) within open reading frames and abolishment of full-length mRNA. PTT is a wide-spread phenomenon in Neurospora, and there is a strong negative correlation between codon usage bias and PTT events. Rare codons lead to the formation of putative poly(A) signals and PTT. A similar role for codon *For correspondence: usage bias was also observed in mouse cells. Together, these results suggest that codon usage [email protected] (YD); biases co-evolve with the transcription termination machinery to suppress premature termination of [email protected] (YL) transcription and thus allow for optimal gene expression. †These authors contributed DOI: https://doi.org/10.7554/eLife.33569.001 equally to this work Competing interests: The authors declare that no Introduction competing interests exist. -
Small Open Reading Frames Tiny Treasures of the Non-Coding Genomic Regions
GENERAL ARTICLE Small Open Reading Frames Tiny Treasures of the Non-coding Genomic Regions A Yazhini Open Reading Frames (ORFs) are the DNA sequences in the genome that has the potential to be translated. Generally, only long ORFs (≥ 300 nucleotides or nt) are thought to be protein coding regions and are considered as genes in the genome annotation pipeline. Until recent years, small ORFs (smORFs) of less than 100 codons (< 300 nt) were regarded as non-functional on the basis of empirical observations. How- A Yazhini is a research ever, recent work on ribosome profiling and mass spectrom- student at Molecular etry have led to the discovery of many translating functional Biophysics Unit, Indian Institute of Science. She small ORFs and presence of their stable peptide products. works mainly on protein Further, examples of biologically active peptides with vital evolution, protein structure regulatory functions underline the importance of smORFs prediction and structure of in cell functions. Genome-wide analysis shows that smORFs macromolecule assemblies under the guidance of Prof. N are conserved across diverse species, and the functional char- Srinivasan. Overall, her acterization of their peptides reveals their critical role in a research revolves around broad spectrum of regulatory mechanisms. Further analy- structural and mechanistic sis of small ORFs is likely throw light on many exciting, un- understanding of proteins. explored regulatory mechanisms in different developmental stages and tissue types. 1. Introduction Gene is the protein encoding functional unit in the genome. It consists of promoter, protein coding (exon) and terminal regions. The protein coding regions of the gene are called the ‘open read- ing frames’ (ORFs).