Ribosome Profiling Reveals the What, When, Where and How of Protein Synthesis

Total Page:16

File Type:pdf, Size:1020Kb

Ribosome Profiling Reveals the What, When, Where and How of Protein Synthesis REVIEWS TECHNOLOGIES AND TECHNIQUES Ribosome profiling reveals the what, when, where and how of protein synthesis Gloria A. Brar1,3,4 and Jonathan S. Weissman2–4 Abstract | Ribosome profiling, which involves the deep sequencing of ribosome-protected mRNA fragments, is a powerful tool for globally monitoring translation in vivo. The method has facilitated discovery of the regulation of gene expression underlying diverse and complex biological processes, of important aspects of the mechanism of protein synthesis, and even of new proteins, by providing a systematic approach for experimental annotation of coding regions. Here, we introduce the methodology of ribosome profiling and discuss examples in which this approach has been a key factor in guiding biological discovery, including its prominent role in identifying thousands of novel translated short open reading frames and alternative translation products. Ribosome footprints Translation, which is the process by which a ribosome of the position of the ribosome at the time at which trans- mRNA fragments of ~30 reads an mRNA template to guide protein synthesis, is a lation was halted. Measuring the density of protected nucleotides that result from crucial step in gene expression. Translation is energeti- fragments on a given transcript provides a proxy for the nuclease treatment of cally costly and is therefore tightly regulated to conserve rate of protein synthesis. In addition, determining the translating ribosomes. These are mRNA regions that cellular resources, as well as to avoid mistakes that may positions of the protected fragments makes it possible to are protected by the ribosome result in the production of toxic proteins. Indeed, a wide empirically measure the identity of translation products as the mRNA is decoded to a range of disease states, including neurodegeneration, (for example, where they begin and end and even the protein sequence. anaemia and specific developmental defects, result when frame being read). This has led to the discovery of many the translational process is compromised (see selected novel or alternative protein products10–19. The distribu- REFS 1–6 1Department of Molecular ). Although much is known about the struc- tion of ribosome footprints can provide insights into the and Cell Biology, University of ture and function of the ribosome, our understanding mechanism of translational control (for example, it can California, Berkeley, of many aspects of the regulation of translation has been be used to identify regulatory translational pauses and California 94720, USA. far more limited. translated upstream open reading frames (uORFs)). Finally, 2Howard Hughes Medical Institute, Department of Efforts to globally monitor gene expression have novel adaptations of the ribosome profiling approach Cellular and Molecular historically focused on measuring mRNA levels (for make it possible to monitor translation mediated by sub- Pharmacology, University of example, using microarrays or RNA sequencing (RNA- sets of ribosomes on the basis of their physical location California, San Francisco, seq)), although we know that translational control is in the cell or their interaction partners. California 94158, USA. an essential and regulated step in determining levels of Here, we discuss the principles of the ribosome pro- 3Center for RNA Systems Biology, University of protein expression. Until recently, precisely monitoring filing approach, its strengths and limitations, and recent California, Berkeley, translation was far more challenging than was measur- examples in which it has guided biological discovery. California 94720, USA. ing mRNA levels. This has changed with the develop- We focus on the value of ribosome profiling as a tool 4California Institute for ment of the ribosome profiling approach, which was first to interrogate what is being translated, how this transla- Quantitative Biosciences (REF. 7) (QB3), University of described in 2009 . tion is regulated and where in the cell the translation of California, San Francisco, Ribosome profiling is a deep-sequencing-based tool specific sets of proteins occurs. California 94158, USA. that facilitates the detailed measurement of translation e-mails: globally and in vivo7. At the core of this approach is the What is ribosome profiling and what can it reveal? [email protected]; observation that a translating ribosome strongly protects Ribosome profiling exploits the classical molecular [email protected] 8,9 doi:10.1038/nrm4069 about 30 nucleotides of an mRNA from nuclease activ- method of ribosome footprinting , in which in vitro 8,9 Published online ity . Sequencing of these ribosome-protected fragments, translated mRNAs are treated with nuclease to destroy 14 October 2015 termed ribosome footprints, thus provides a precise record the regions that are not protected by the ribosome7,9. NATURE REVIEWS | MOLECULAR CELL BIOLOGY VOLUME 16 | NOVEMBER 2015 | 651 © 2015 Macmillan Publishers Limited. All rights reserved REVIEWS Upstream open reading Such treatment leaves ‘footprints’ of ~30 nucleotides, ribosome profiling has a range of uses, from a broad pro- frames which can be mapped back to the original mRNA to teomic tool to a specific probe of translation in an in vivo (uORFs). ORFs in the 5′ leader define the exact location of the translating ribosome. setting, and as a valuable complement to mRNA-seq. region of a characterized Ribosome profiling extends this method by mapping Ribosome profiling requires collection of a physio­ mRNA transcript. Translation of uORFs may regulate and measuring the full complement of in vivo ribosome logical sample; inhibition of translation to freeze ribo- translation of a downstream footprints to quantify new protein synthesis and to anno- somes in the act of translation; nuclease digestion to ORF. Ribosome profiling allows tate coding regions globally7,10–12 (FIGS 1,2). Extraordinary produce ribosome-protected fragments; and isolation of for the empirical identification advances in sequencing technology20 now make it possible ribosomes and, subsequently, of ribosome footprints21. of all translated uORFs in vivo to deeply sample all translating ribosomes. In mammalian Ribosome footprints are converted to a strand-specific under a condition of interest. Although uORFs are short, cells, for example, which encode ~20,000 proteins with an library and subjected to next-generation sequencing, here we do not include them in average mRNA coding region of ~500 nucleotide triplets, and the fragments are then mapped to the appropriate the class of ‘short ORFs’, which nuclease digestion of all translating ribosome–mRNA reference genome. Ribosome profiling is typically car- are on an mRNA that was not complexes yields 10 million possible footprints. The bil- ried out on a split sample, with parallel libraries con- previously thought to encode a protein. lions of reads that are now possible with next-generation structed for measuring mRNA abundance by mRNA-seq. sequencing enable the reliable quantification of the set of Comparison between the rates of protein synthesis and footprints tiling across all but the rarest mRNAs, and a the abundance of mRNAs makes it possible to determine recently developed kit facilitates sample preparation21,22. the translational efficiency for each mRNA7 (FIGS 1a,b;2b,c). With such easily attainable and quantitative information, The common biophysical properties of the ribosome and Cell type of interest In vivo capture of translating ribosomes and mRNAs, lysis a Ribosome profiling b mRNA-seq c High % of ORF covered AAAAAAAAAA AAAAAAAAAA by ribosome footprints AAAAAAAAA AAAAAAAAA Low density of footprints before start codons and after stop codons (high inside/out ratio) AAAAAAAAAAA AAAAAAAAAAA AAAAAAAAAA AAAAAAAAAA Ribosome footprint reads Genomic AAAAAAAAAAAA AAAAAAAAAAAA position Start Stop Nuclease treatment Random fragmentation AAAAAAAA A Codon periodicity Ribosome AAAA footprints AAA AAAAAAAAAA Library generation Library generation Deep sequencing Deep sequencing AAGCTGCTTACGACCTGCATGCAG Read mapping Read mapping 5′ leader 3′ UTR mRNA-seq reads Ribosome footprint reads Coding region Genomic position AUG Stop 5′ transcript end 3′ transcript end Genomic position (often indicates (often indicates transcription start site) transcription stop site) Figure 1 | An overview of ribosome profiling. a | Ribosome-bound allows approximate determinationNature of transcript Reviews boundaries,| Molecular Cell but Biologyit is less mRNAs are isolated by size and treated with a nonspecific nuclease precise than that collected by ribosome profiling, owing to the loss of 5ʹ (typically RNase I or micrococcal nuclease), resulting in protected mRNA and 3ʹ ends during the fragment generation method that is typically fragments termed ‘footprints’. These ribosome footprints are isolated used. c | Translated open reading frames (ORFs) contain a stereotyped and converted to a library for deep sequencing. The ribosome footprints organization of ribosome footprints. Ribosome footprint density over typically show precise positioning between the start and the stop codon ORFs begins sharply at the start codon, ends sharply at the stop codon of a gene, which facilitates global and experimental identification of and shows evidence of codon periodicity. True translated regions tend to genomic coding regions. b | By comparison, mRNA sequencing show ribosome footprint coverage over the majority of the ORF and not (mRNA-seq) captures random fragments covering the entire mRNA typically
Recommended publications
  • Polysome-Profiling in Small Tissue Samples
    bioRxiv preprint doi: https://doi.org/10.1101/104596; this version posted February 1, 2017. 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. Polysome-profiling in small tissue samples Shuo Liang1,#, Hermano Bellato2,#, Julie Lorent1,#, Fernanda Lupinacci2, Vincent Van Hoef1, Laia Masvidal1,*, Glaucia Hajj2,* and Ola Larsson1,* 1. Department of Oncology-Pathology, Karolinska Institutet, Stockholm, 171 77, Sweden 2. International Research Center, A.C. Camargo Cancer Center, São Paulo, Brazil # Equally contributing authors * Correspondence: Laia Masvidal ([email protected]), Glaucia Hajj ([email protected]) and Ola Larsson ([email protected]) ABSTRACT Polysome-profiling is commonly used to study genome wide patterns of translational efficiency, i.e. the translatome. The standard approach for collecting efficiently translated polysome-associated RNA results in laborious extraction of RNA from a large volume spread across multiple fractions. This property makes polysome-profiling inconvenient for larger experimental designs or samples with low RNA amounts such as primary cells or frozen tissues. To address this we optimized a non-linear sucrose gradient which reproducibly enriches for mRNAs associated with >3 ribosomes in only one or two fractions, thereby reducing sample handling 5-10 fold. The technique can be applied to cells and frozen tissue samples from biobanks, and generates RNA with a quality reflecting the starting material. When coupled with smart-seq2, a single-cell RNA sequencing technique, translatomes from small tissue samples can be obtained. Translatomes acquired using optimized non-linear gradients are very similar to those obtained when applying linear gradients.
    [Show full text]
  • Using Ribosome Profiling to Quantify Differences in Protein Expression
    bioRxiv preprint doi: https://doi.org/10.1101/501478; this version posted December 19, 2018. 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. 1 Using ribosome profiling to quantify differences in protein expression: 2 a case study in Saccharomyces cerevisiae oxidative stress conditions 3 4 5 William R. Blevins1,#, Teresa Tavella1,#, Simone G. Moro1, Bernat Blasco-Moreno2, 6 Adrià Closa-Mosquera2, Juana Díez2, Lucas B. Carey2, M. Mar Albà1,2,3,* 7 8 1Evolutionary Genomics Groups, Research Programme on Biomedical Informatics (GRIB), Hospital del 9 Mar Research Institute (IMIM), Barcelona, Spain 10 2Health and Experimental Sciences Department, Universitat Pompeu Fabra(UPF), Barcelona, Spain 11 3Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain. 12 #Shared first co-authorship 13 *To whom correspondence should be addressed. 14 Running title: differential gene translation 15 Keywords: differential gene expression, ribosome profiling, RNA-Seq, translation, oxidative stress 1 bioRxiv preprint doi: https://doi.org/10.1101/501478; this version posted December 19, 2018. 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. 16 Abstract 17 18 Cells respond to changes in the environment by modifying the concentration of specific 19 proteins. Paradoxically, the cellular response is usually examined by measuring variations 20 in transcript abundance by high throughput RNA sequencing (RNA-Seq), instead of 21 directly measuring protein concentrations.
    [Show full text]
  • Super-Resolution Ribosome Profiling Reveals Unannotated Translation Events in Arabidopsis
    Super-resolution ribosome profiling reveals unannotated translation events in Arabidopsis Polly Yingshan Hsua, Lorenzo Calviellob,c, Hsin-Yen Larry Wud,1, Fay-Wei Lia,e,f,1, Carl J. Rothfelse,f, Uwe Ohlerb,c, and Philip N. Benfeya,g,2 aDepartment of Biology, Duke University, Durham, NC 27708; bBerlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine, 13125 Berlin, Germany; cDepartment of Biology, Humboldt Universität zu Berlin, 10099 Berlin, Germany; dBioinformatics Research Center and Department of Statistics, North Carolina State University, Raleigh, NC 27695; eUniversity Herbarium, University of California, Berkeley, CA 94720; fDepartment of Integrative Biology, University of California, Berkeley, CA 94720; and gHoward Hughes Medical Institute, Duke University, Durham, NC 27708 Contributed by Philip N. Benfey, September 13, 2016 (sent for review June 30, 2016; reviewed by Pam J. Green and Albrecht G. von Arnim) Deep sequencing of ribosome footprints (ribosome profiling) maps and contaminants. Several metrics associated with translation have and quantifies mRNA translation. Because ribosomes decode mRNA been exploited (11), for example, the following: (i)ribosomesre- every 3 nt, the periodic property of ribosome footprints could be lease after encountering a stop codon (9), (ii) local enrichment of used to identify novel translated ORFs. However, due to the limited footprints within the predicted ORF (4, 13), (iii) ribosome footprint resolution of existing methods, the 3-nt periodicity is observed length distribution (7), and (iv) 3-nt periodicity displayed by trans- mostly in a global analysis, but not in individual transcripts. Here, we lating ribosomes (2, 6, 10, 14, 15). Among these features, some work report a protocol applied to Arabidopsis that maps over 90% of the well in distinguishing groups of coding vs.
    [Show full text]
  • Integrated Analyses of Translatome and Proteome Identify the Rules of Translation Selectivity in RPS14-Deficient Cells
    ARTICLE Red Cell Biology and its Disorders Integrated analyses of translatome and Ferrata Storti Foundation proteome identify the rules of translation selectivity in RPS14-deficient cells Ismael Boussaid,1 Salomé Le Goff,1,2,* Célia Floquet,1,* Emilie-Fleur Gautier,1,3 Anna Raimbault,1 Pierre-Julien Viailly,4 Dina Al Dulaimi,1 Barbara Burroni,5 Isabelle Dusanter-Fourt,1 Isabelle Hatin,6 Patrick Mayeux,1,2,3,# Bertrand Cosson7,# and Michaela Fontenay1,2,3,4,8 Haematologica 2021 1 Université de Paris, Institut Cochin, CNRS UMR 8104, INSERM U1016, Paris; Volume 106(3):746-758 2Laboratoire d’Excellence du Globule Rouge GR-Ex, Université de Paris, Paris; 3Proteomic Platform 3P5, Université de Paris, Paris; 4Centre Henri-Becquerel, Institut de Recherche et d’Innovation Biomedicale de Haute Normandie, INSERM U1245, Rouen; 5Assistance Publique-Hôpitaux de Paris, Centre-Université de Paris - Cochin, Service de Pathologie, Paris; 6Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Université de Paris-Sud, Université Paris-Saclay, Gif-sur-Yvette Cedex; 7Université de Paris, Epigenetics and Cell Fate, CNRS UMR 7216, Paris and 8Assistance Publique- Hôpitaux de Paris, Centre-Université de Paris - Hôpital Cochin, Service d’Hématologie Biologique, Paris, France *SLG and CF contributed equally to this work. #PM and BC contributed equally as co-senior authors. ABSTRACT n ribosomopathies, the Diamond-Blackfan anemia (DBA) or 5q- syn- drome, ribosomal protein (RP) genes are affected by mutation or deletion, Iresulting in bone marrow erythroid hypoplasia. Unbalanced production of ribosomal subunits leading to a limited ribosome cellular content regu- lates translation at the expense of the master erythroid transcription factor GATA1.
    [Show full text]
  • Minireview: Novel Micropeptide Discovery by Proteomics and Deep Sequencing Methods
    fgene-12-651485 May 6, 2021 Time: 11:28 # 1 MINI REVIEW published: 06 May 2021 doi: 10.3389/fgene.2021.651485 Minireview: Novel Micropeptide Discovery by Proteomics and Deep Sequencing Methods Ravi Tharakan1* and Akira Sawa2,3 1 National Institute on Aging, National Institutes of Health, Baltimore, MD, United States, 2 Departments of Psychiatry, Neuroscience, Biomedical Engineering, and Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States, 3 Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States A novel class of small proteins, called micropeptides, has recently been discovered in the genome. These proteins, which have been found to play important roles in many physiological and cellular systems, are shorter than 100 amino acids and were overlooked during previous genome annotations. Discovery and characterization of more micropeptides has been ongoing, often using -omics methods such as proteomics, RNA sequencing, and ribosome profiling. In this review, we survey the recent advances in the micropeptides field and describe the methodological and Edited by: conceptual challenges facing future micropeptide endeavors. Liangliang Sun, Keywords: micropeptides, miniproteins, proteogenomics, sORF, ribosome profiling, proteomics, genomics, RNA Michigan State University, sequencing United States Reviewed by: Yanbao Yu, INTRODUCTION J. Craig Venter Institute (Rockville), United States The sequencing and publication of complete genomic sequences of many organisms have aided Hongqiang Qin, the medical sciences greatly, allowing advances in both human genetics and the biology of human Dalian Institute of Chemical Physics, Chinese Academy of Sciences, China disease, as well as a greater understanding of the biology of human pathogens (Firth and Lipkin, 2013).
    [Show full text]
  • Efficient Analysis of Mammalian Polysomes in Cells and Tissues
    TOOLS AND RESOURCES Efficient analysis of mammalian polysomes in cells and tissues using Ribo Mega-SEC Harunori Yoshikawa1†, Mark Larance1,2†, Dylan J Harney2, Ramasubramanian Sundaramoorthy1, Tony Ly1,3, Tom Owen-Hughes1, Angus I Lamond1* 1Centre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dundee, United Kingdom; 2Charles Perkins Centre, School of Life and Environmental Sciences, University of Sydney, Sydney, Australia; 3Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh, United Kingdom Abstract We describe Ribo Mega-SEC, a powerful approach for the separation and biochemical analysis of mammalian polysomes and ribosomal subunits using Size Exclusion Chromatography and uHPLC. Using extracts from either cells, or tissues, polysomes can be separated within 15 min from sample injection to fraction collection. Ribo Mega-SEC shows translating ribosomes exist predominantly in polysome complexes in human cell lines and mouse liver tissue. Changes in polysomes are easily quantified between treatments, such as the cellular response to amino acid starvation. Ribo Mega-SEC is shown to provide an efficient, convenient and highly reproducible method for studying functional translation complexes. We show that Ribo Mega-SEC is readily combined with high-throughput MS-based proteomics to characterize proteins associated with polysomes and ribosomal subunits. It also facilitates isolation of complexes for electron microscopy and structural studies. *For correspondence: DOI: https://doi.org/10.7554/eLife.36530.001 [email protected] †These authors contributed equally to this work Introduction Competing interests: The The ribosome is a large RNA-protein complex, comprising four ribosomal RNAs (rRNAs) and >80 authors declare that no ribosomal proteins (RPs), which coordinates mRNA-templated protein synthesis.
    [Show full text]
  • Comparative Analysis Reveals Genomic Features of Stress
    Comparative analysis reveals genomic features of PNAS PLUS stress-induced transcriptional readthrough Anna Vilborga,b,1, Niv Sabathc, Yuval Wieselc, Jenny Nathansa,b, Flonia Levy-Adamc, Therese A. Yarioa,b, Joan A. Steitza,b, and Reut Shalgic,1 aDepartment of Molecular Biophysics and Biochemistry, Boyer Center for Molecular Medicine, Yale University School of Medicine, New Haven, CT 06536; bHoward Hughes Medical Institute, Yale University School of Medicine, New Haven, CT 06536; and cDepartment of Biochemistry, Rappaport Faculty of Medicine, Technion–Israel Institute of Technology, Haifa 31096, Israel Edited by Jasper Rine, University of California, Berkeley, CA, and approved July 14, 2017 (received for review July 10, 2017) Transcription is a highly regulated process, and stress-induced degraded by exonucleases that access the unprotected 5′ end changes in gene transcription have been shown to play a major role generated by cleavage at the polyA site (12, 13). However, recent in stress responses and adaptation. Genome-wide studies reveal studies show that various stress and disease states, including prevalent transcription beyond known protein-coding gene loci, osmotic stress (10), HSV-1 infection (9), and renal carcinoma generating a variety of RNA classes, most of unknown function. (8), increase both the levels and length of transcripts mapping to One such class, termed downstream of gene-containing transcripts regions downstream of the cleavage and polyadenylation sites. (DoGs), was reported to result from transcriptional readthrough Ourpreviousstudy(10)showedthat these transcripts are contin- upon osmotic stress in human cells. However, how widespread the uous with the RNAs generated from the upstream protein-coding readthrough phenomenon is, and what its causes and consequences gene, suggesting that they result from alterations in cleavage and are, remain elusive.
    [Show full text]
  • Riboviz 2: a Flexible and Robust Ribosome Profiling Data Analysis
    bioRxiv preprint doi: https://doi.org/10.1101/2021.05.14.443910; this version posted May 17, 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 a CC-BY 4.0 International license. i “RiboViz2_paper” — 2021/5/14 — 15:13 — page 1 — #1 i i i Application Note riboviz 2: A flexible and robust ribosome profiling data analysis and visualization workflow Alexander L. Cope 1, Felicity Anderson 2, John Favate 1, Michael Jackson 3, Amanda Mok 4, Anna Kurowska 2, Emma MacKenzie 2, Vikram Shivakumar 5, Peter Tilton 1, Sophie M. Winterbourne 2, Siyin Xue 2, Kostas Kavoussanakis 3, Liana F. Lareau 4,5, Premal Shah 1, Edward W.J. Wallace 2, 1Rutgers University, Department of Genetics, Piscataway, NJ, USA 2Institute for Cell Biology and SynthSys, School of Biological Sciences, The University of Edinburgh, Edinburgh, UK 3EPCC, The University of Edinburgh, Edinburgh, UK 4Center for Computational Biology, University of California, Berkeley, CA, USA 5Department of Bioengineering, University of California, Berkeley, CA, USA To whom correspondence should be addressed. E-mail: [email protected]; [email protected]; [email protected] Abstract Motivation: Ribosome profiling, or Ribo-seq, is the state of the art method for quantifying protein synthesis in living cells. Computational analysis of Ribo-seq data remains challenging due to the complexity of the procedure, as well as variations introduced for specific organisms or specialized analyses. Many bioinformatic pipelines have been developed, but these pipelines have key limitations in terms of functionality or usability.
    [Show full text]
  • Improving Bacterial Ribosome Profiling Data Quality
    bioRxiv preprint doi: https://doi.org/10.1101/863266; this version posted December 3, 2019. 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. Improving Bacterial Ribosome Profiling Data Quality Alina Glaub1, Christopher Huptas1, Klaus Neuhaus1,2, Zachary Ardern1* 1Chair for Microbial Ecology, Technical University of Munich, Freising, Germany, 2Core Facility Microbiome/NGS, Institute for Food & Health, Technical University of Munich, Freising, Germany *corresponding author Abstract Ribosome profiling (RIBO-seq) in prokaryotes has the potential to facilitate accurate detection of translation initiation sites, to increase understanding of translational dynamics, and has already allowed detection of many unannotated genes. However, protocols for ribosome profiling and corresponding data analysis are not yet standardized. To better understand the influencing factors, we analysed 48 ribosome profiling samples from 9 studies on E. coli K12 grown in LB medium. We particularly investigated the size selection step in each experiment since the selection for ribosome-protected footprints (RPFs) has been performed at various read lengths. We suggest choosing a size range between 22-30 nucleotides in order to obtain protein-coding fragments. In order to use RIBO-seq data for improving gene annotation of weakly expressed genes, the total amount of reads mapping to protein-coding sequences and not rRNA or tRNA is important, but no consensus about the appropriate sequencing depth has been reached. Again, this causes significant variation between studies. Our analysis suggests that 20 million non rRNA/tRNA mapping reads are required for global detection of translated annotated genes.
    [Show full text]
  • Computational Resources for Ribosome Profiling: from Database to Web Server and Software Hongwei Wang*, Yan Wang* and Zhi Xie
    Briefings in Bioinformatics, 2017, 1–12 doi: 10.1093/bib/bbx093 Paper Computational resources for ribosome profiling: from database to Web server and software Hongwei Wang*, Yan Wang* and Zhi Xie Corresponding authors: Hongwei Wang, State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China. Tel.: þ86 20 87335131; E-mail: [email protected]; Zhi Xie, State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China. Tel.: þ86 20 87335131; E-mail: [email protected] *These authors contributed equally to the work as joint first authors. Abstract Ribosome profiling is emerging as a powerful technique that enables genome-wide investigation of in vivo translation at sub-codon resolution. The increasing application of ribosome profiling in recent years has achieved remarkable progress to- ward understanding the composition, regulation and mechanism of translation. This benefits from not only the awesome power of ribosome profiling but also an extensive range of computational resources available for ribosome profiling. At pre- sent, however, a comprehensive review on these resources is still lacking. Here, we survey the recent computational ad- vances guided by ribosome profiling, with a focus on databases, Web servers and software tools for storing, visualizing and analyzing ribosome profiling data. This review is intended to provide experimental and computational biologists with a ref- erence to make appropriate choices among existing resources for the question at hand. Key words: ribosome profiling; translational regulation; database; Web server; software Introduction sub-codon resolution [6, 7]. By precisely pinpointing ribosomes during translation, this technique has provided unprecedented Precise control of gene expression can be directly modulated insights into the complexity of translatome [8–12].
    [Show full text]
  • Modeling Translation Initiation in Eukaryotes Based on TCP-Seq Data Tamar Neumann, Tamir Tuller [email protected]
    Modeling Translation Initiation in Eukaryotes Based on TCP-seq Data Tamar Neumann, Tamir Tuller [email protected] Introduction Results Discretization Process AUGsAUG's in in 5’UTR 5'UTR Signal Signal DiscretizationDiscretized Signal of AUG's- AUGs in 5'UTRin 5’UTR Signal Translation regulation and specifically its initiation step is fundamental to gene expression control. Highest 10% AUG Context Score Values Highest 10% AUG Context Score Values 100 3 85 However, various aspects related to the biophysics of translation initiation in eukaryotes are 2.8 85 2.6 75 currently not well understood or modeled. 75 2.4 65 A novel protocol named Translation Complex Profile Sequencing (TCP-seq) was developed and 65 2.2 55 55 2 implemented on S. cerevisiae. This protocol provides the footprints of the small subunit (SSU) of the 1.8 45 45 Footprint length [nt] length Footprint [nt] length Footprint Foot print length [nt] Foot print length [nt] 1.6 35 ribosome (possibly with additional factors) across the entire transcriptome. 35 1.4 25 25 In this study, based the TCP-seq data, we develop for the first-time quantitative model related to 1.2 15 1 15 the affect of transcript features on the dynamic of the SSU. -50 -25 AUG +25 +50 -50 -25 AUG +25 +50 Position relative to AUG Codon [nt] Position relative to AUG Codon [nt] MIC Score of AUGs in 5’UTR with High/Low Context Score Methods MIC Score P Value (1000 Permutations) AUG Start Codon 0.8795 <0.001 1 Translation Complex Profile Sequencing (TCP-seq) AUGs With High AUG Context Score 0.5230 <0.001 AUGs With Low AUG Context Score 0.1389 0.08 Yeast cells were crosslinked using formaldehyde, which Ø efficiently stabilizes the preinitiation complexes.
    [Show full text]
  • Mrna-Seq and Ribosome Profiling Protocol Huili Guo, Bartel Lab, August 8, 2010
    mRNA-Seq and Ribosome Profiling Protocol Huili Guo, Bartel lab, August 8, 2010 mRNA-Seq and Ribosome Profiling protocol Citation: Guo et al., Nature 466: 835‒840 (2010) This protocol describes the procedures used to perform mRNA-Seq and ribosome profiling on mammalian cells. In general, you would want to split each biological sample such that mRNA- Seq and ribosome profiling can be carried out in parallel for the same sample. If you are performing mRNA-Seq or ribosome profiling only for a given sample, skip to section 2 or 3, respectively. Structure In this protocol, some steps are specific to mRNA-Seq/ribosome profiling and indicated so. The library generation steps are largely common for both procedures. The last section includes steps for miscellaneous procedures used in the protocol. Section 1: Harvesting cells for parallel mRNA-Seq and ribosome profiling 1.1 Harvesting of cells/biological material The example below is written for cells grown in monolayer culture. (e.g. untransfected HeLa cells) Estimate of number of cells required: mRNA-Seq: Use enough cells to get ~15-20 μg total RNA Ribosome profiling: This varies depending on cell type/size, but as an example, I usually use ~10 million HeLa cells per sucrose gradient Day before: Split cells such that dish will be 70-80% confluent on day of harvesting. Day of harvesting: Arrest translation with cycloheximide (CHX) 1. Spike medium that cells are growing in with CHX (final 100 μg/ml, therefore NOTE the volume of media in the dish/container beforehand!) 2. Return cells to 37 °C for 10 min Harvesting cells 1.
    [Show full text]