1
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Manning AC, Bashir MM, Jimenez AR, Upton HE, Collins K, Lowe TM, Tucker JM. Gammaherpesvirus infection alters transfer RNA splicing and triggers tRNA cleavage. bioRxiv 2024:2024.02.16.580780. [PMID: 38405876 PMCID: PMC10888928 DOI: 10.1101/2024.02.16.580780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Transfer RNAs (tRNAs) are fundamental for both cellular and viral gene expression during viral infection. Moreover, mounting evidence supports a noncanonical role for tRNA cleavage products in the control of gene expression during diverse conditions of stress and infection. We previously reported that infection with the model murine gammaherpesvirus, MHV68, leads to altered tRNA transcription, suggesting that tRNA regulation may play an important role in mediating viral replication or the host response. To better understand how viral infection alters tRNA expression, we combined Ordered Two Template Relay (OTTR) with tRNA-specific bioinformatic software called tRAX to profile full-length tRNAs and fragmented tRNA-derived RNAs (tDRs) during infection with MHV68. We find that OTTR-tRAX is a powerful sequencing strategy for combined tRNA/tDR profiling and reveals that MHV68 infection triggers pre-tRNA and mature tRNA cleavage, resulting in the accumulation of specific tDRs. Fragments of virally-encoded tRNAs (virtRNAs), as well as virtRNA base modification signatures are also detectable during infection. We present evidence that tRNA splicing factors are involved in the biogenesis of MHV68-induced cleavage products from pre-tRNAs and, in the case of CLP1 kinase, impact infectious virus production. Our data offers new insights into the importance of tRNA processing during gammaherpesvirus infection.
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Affiliation(s)
- Aidan C Manning
- Department of Biomolecular Engineering, Baskin School of Engineering, University of California, Santa Cruz, Santa Cruz, CA, 95064, USA
| | - Mahmoud M Bashir
- Department of Microbiology and Immunology, Carver College of Medicine, University of Iowa, Iowa City, IA, 52242, USA
| | - Ariana R Jimenez
- Department of Microbiology and Immunology, Carver College of Medicine, University of Iowa, Iowa City, IA, 52242, USA
- Interdisciplinary Graduate Program in Immunology, University of Iowa, Iowa City, IA, 52242, USA
| | - Heather E Upton
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, 94720, USA
| | - Kathleen Collins
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, 94720, USA
| | - Todd M Lowe
- Department of Biomolecular Engineering, Baskin School of Engineering, University of California, Santa Cruz, Santa Cruz, CA, 95064, USA
| | - Jessica M Tucker
- Department of Microbiology and Immunology, Carver College of Medicine, University of Iowa, Iowa City, IA, 52242, USA
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2
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Davey-Young J, Hasan F, Tennakoon R, Rozik P, Moore H, Hall P, Cozma E, Genereaux J, Hoffman KS, Chan PP, Lowe TM, Brandl CJ, O’Donoghue P. Mistranslating the genetic code with leucine in yeast and mammalian cells. RNA Biol 2024; 21:1-23. [PMID: 38629491 PMCID: PMC11028032 DOI: 10.1080/15476286.2024.2340297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/03/2024] [Indexed: 04/19/2024] Open
Abstract
Translation fidelity relies on accurate aminoacylation of transfer RNAs (tRNAs) by aminoacyl-tRNA synthetases (AARSs). AARSs specific for alanine (Ala), leucine (Leu), serine, and pyrrolysine do not recognize the anticodon bases. Single nucleotide anticodon variants in their cognate tRNAs can lead to mistranslation. Human genomes include both rare and more common mistranslating tRNA variants. We investigated three rare human tRNALeu variants that mis-incorporate Leu at phenylalanine or tryptophan codons. Expression of each tRNALeu anticodon variant in neuroblastoma cells caused defects in fluorescent protein production without significantly increased cytotoxicity under normal conditions or in the context of proteasome inhibition. Using tRNA sequencing and mass spectrometry we confirmed that each tRNALeu variant was expressed and generated mistranslation with Leu. To probe the flexibility of the entire genetic code towards Leu mis-incorporation, we created 64 yeast strains to express all possible tRNALeu anticodon variants in a doxycycline-inducible system. While some variants showed mild or no growth defects, many anticodon variants, enriched with G/C at positions 35 and 36, including those replacing Leu for proline, arginine, alanine, or glycine, caused dramatic reductions in growth. Differential phenotypic defects were observed for tRNALeu mutants with synonymous anticodons and for different tRNALeu isoacceptors with the same anticodon. A comparison to tRNAAla anticodon variants demonstrates that Ala mis-incorporation is more tolerable than Leu at nearly every codon. The data show that the nature of the amino acid substitution, the tRNA gene, and the anticodon are each important factors that influence the ability of cells to tolerate mistranslating tRNAs.
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Affiliation(s)
- Josephine Davey-Young
- Department of Biochemistry, The University of Western Ontario, London, Ontario, Canada
| | - Farah Hasan
- Department of Biochemistry, The University of Western Ontario, London, Ontario, Canada
| | - Rasangi Tennakoon
- Department of Biochemistry, The University of Western Ontario, London, Ontario, Canada
| | - Peter Rozik
- Department of Biochemistry, The University of Western Ontario, London, Ontario, Canada
| | - Henry Moore
- Department of Biomolecular Engineering, Baskin School of Engineering & UCSC Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Peter Hall
- Department of Biochemistry, The University of Western Ontario, London, Ontario, Canada
| | - Ecaterina Cozma
- Department of Biochemistry, The University of Western Ontario, London, Ontario, Canada
| | - Julie Genereaux
- Department of Biochemistry, The University of Western Ontario, London, Ontario, Canada
| | | | - Patricia P. Chan
- Department of Biomolecular Engineering, Baskin School of Engineering & UCSC Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Todd M. Lowe
- Department of Biomolecular Engineering, Baskin School of Engineering & UCSC Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Christopher J. Brandl
- Department of Biochemistry, The University of Western Ontario, London, Ontario, Canada
| | - Patrick O’Donoghue
- Department of Biochemistry, The University of Western Ontario, London, Ontario, Canada
- Department of Chemistry, The University of Western Ontario, London, Ontario, Canada
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3
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Holmes AD, Chan PP, Chen Q, Ivanov P, Drouard L, Polacek N, Kay MA, Lowe TM. A standardized ontology for naming tRNA-derived RNAs based on molecular origin. Nat Methods 2023; 20:627-628. [PMID: 36869120 PMCID: PMC10334869 DOI: 10.1038/s41592-023-01813-2] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/05/2023]
Affiliation(s)
- Andrew D Holmes
- Department of Biomolecular Engineering, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Patricia P Chan
- Department of Biomolecular Engineering, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Qi Chen
- Division of Urology, Department of Surgery, School of Medicine, University of Utah, Salt Lake City, UT, USA
| | - Pavel Ivanov
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Laurence Drouard
- Institut de biologie moléculaire des plantes-CNRS, Université de Strasbourg, Strasbourg, France
| | - Norbert Polacek
- Department of Chemistry, Biochemistry and Pharmaceutical Sciences, University of Bern, Bern, Switzerland
| | - Mark A Kay
- Departments of Pediatrics and Genetics, Stanford University, Stanford, CA, USA
| | - Todd M Lowe
- Department of Biomolecular Engineering, University of California, Santa Cruz, Santa Cruz, CA, USA.
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4
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Li G, Manning AC, Bagi A, Yang X, Gokulnath P, Spanos M, Howard J, Chan PP, Sweeney T, Kitchen R, Li H, Laurent BD, Aranki SF, Kontaridis MI, Laurent LC, Van Keuren‐Jensen K, Muehlschlegel J, Lowe TM, Das S. Distinct Stress-Dependent Signatures of Cellular and Extracellular tRNA-Derived Small RNAs. Adv Sci (Weinh) 2022; 9:e2200829. [PMID: 35373532 PMCID: PMC9189662 DOI: 10.1002/advs.202200829] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Indexed: 05/11/2023]
Abstract
The cellular response to stress is an important determinant of disease pathogenesis. Uncovering the molecular fingerprints of distinct stress responses may identify novel biomarkers and key signaling pathways for different diseases. Emerging evidence shows that transfer RNA-derived small RNAs (tDRs) play pivotal roles in stress responses. However, RNA modifications present on tDRs are barriers to accurately quantifying tDRs using traditional small RNA sequencing. Here, AlkB-facilitated methylation sequencing is used to generate a comprehensive landscape of cellular and extracellular tDR abundances in various cell types during different stress responses. Extracellular tDRs are found to have distinct fragmentation signatures from intracellular tDRs and these tDR signatures are better indicators of different stress responses than miRNAs. These distinct extracellular tDR fragmentation patterns and signatures are also observed in plasma from patients on cardiopulmonary bypass. It is additionally demonstrated that angiogenin and RNASE1 are themselves regulated by stressors and contribute to the stress-modulated abundance of sub-populations of cellular and extracellular tDRs. Finally, a sub-population of extracellular tDRs is identified for which AGO2 appears to be required for their expression. Together, these findings provide a detailed profile of stress-responsive tDRs and provide insight about tDR biogenesis and stability in response to cellular stressors.
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Affiliation(s)
- Guoping Li
- Cardiovascular Research CenterMassachusetts General Hospital and Harvard Medical SchoolBostonMA02114USA
| | - Aidan C. Manning
- Department of Biomolecular EngineeringBaskin School of EngineeringUniversity of CaliforniaSanta CruzSanta CruzCA95064USA
| | - Alex Bagi
- Department of Biomolecular EngineeringBaskin School of EngineeringUniversity of CaliforniaSanta CruzSanta CruzCA95064USA
| | - Xinyu Yang
- Fangshan Hospital of BeijingUniversity of Traditional Chinese MedicineBeijing102499China
| | - Priyanka Gokulnath
- Cardiovascular Research CenterMassachusetts General Hospital and Harvard Medical SchoolBostonMA02114USA
| | - Michail Spanos
- Cardiovascular Research CenterMassachusetts General Hospital and Harvard Medical SchoolBostonMA02114USA
| | - Jonathan Howard
- Department of Biomolecular EngineeringBaskin School of EngineeringUniversity of CaliforniaSanta CruzSanta CruzCA95064USA
| | - Patricia P. Chan
- Department of Biomolecular EngineeringBaskin School of EngineeringUniversity of CaliforniaSanta CruzSanta CruzCA95064USA
| | - Thadryan Sweeney
- Cardiovascular Research CenterMassachusetts General Hospital and Harvard Medical SchoolBostonMA02114USA
| | - Robert Kitchen
- Cardiovascular Research CenterMassachusetts General Hospital and Harvard Medical SchoolBostonMA02114USA
| | - Haobo Li
- Cardiovascular Research CenterMassachusetts General Hospital and Harvard Medical SchoolBostonMA02114USA
| | - Brice D. Laurent
- Cardiovascular Research CenterMassachusetts General Hospital and Harvard Medical SchoolBostonMA02114USA
| | - Sary F. Aranki
- Division of Cardiac SurgeryDepartment of SurgeryBrigham and Women's HospitalHarvard Medical SchoolBostonMA02115USA
| | - Maria I. Kontaridis
- Department of Biomedical Research and Translational MedicineMasonic Medical Research InstituteUticaNY13501USA
- Department of Biological Chemistry and Molecular PharmacologyHarvard Medical SchoolBostonMA02115USA
- Department of MedicineDivision of CardiologyBeth Israel Deaconess Medical CenterHarvard Medical SchoolBostonMA02215USA
| | - Louise C. Laurent
- Department of Obstetrics, Gynecology, and Reproductive SciencesUniversity of CaliforniaSan DiegoLa JollaCA92093USA
| | | | - Jochen Muehlschlegel
- Department of Anesthesiology, Perioperative and Pain MedicineBrigham and Women's Hospital and Harvard Medical SchoolBostonMA02115USA
| | - Todd M. Lowe
- Department of Biomolecular EngineeringBaskin School of EngineeringUniversity of CaliforniaSanta CruzSanta CruzCA95064USA
| | - Saumya Das
- Cardiovascular Research CenterMassachusetts General Hospital and Harvard Medical SchoolBostonMA02114USA
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5
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Marygold SJ, Chan PP, Lowe TM. Systematic identification of tRNA genes in Drosophila melanogaster. MicroPubl Biol 2022; 2022:10.17912/micropub.biology.000560. [PMID: 35789696 PMCID: PMC9249942 DOI: 10.17912/micropub.biology.000560] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Revised: 04/19/2022] [Accepted: 04/19/2022] [Indexed: 12/04/2022]
Abstract
Transfer RNAs (tRNAs) are ubiquitous adapter molecules that link specific codons in messenger RNA (mRNA) with their corresponding amino acids during protein synthesis. The tRNA genes of Drosophila have been investigated for over half a century but have lacked systematic identification and nomenclature. Here, we review and integrate data within FlyBase and the Genomic tRNA Database (GtRNAdb) to identify the full complement of tRNA genes in the D. melanogaster nuclear and mitochondrial genomes. We apply a logical and informative nomenclature to all tRNA genes, and provide an overview of their characteristics and genomic features.
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Affiliation(s)
- Steven J Marygold
- FlyBase, Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, CB2 3DY, UK
,
Correspondence to: Steven J Marygold (
)
| | - Patricia P Chan
- Department of Biomolecular Engineering, University of California Santa Cruz, CA 95064, USA
| | - Todd M Lowe
- Department of Biomolecular Engineering, University of California Santa Cruz, CA 95064, USA
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6
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Westhof E, Thornlow B, Chan PP, Lowe TM. Eukaryotic tRNA sequences present conserved and amino acid-specific structural signatures. Nucleic Acids Res 2022; 50:4100-4112. [PMID: 35380696 PMCID: PMC9023262 DOI: 10.1093/nar/gkac222] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Revised: 03/16/2022] [Accepted: 03/22/2022] [Indexed: 11/18/2022] Open
Abstract
Metazoan organisms have many tRNA genes responsible for decoding amino acids. The set of all tRNA genes can be grouped in sets of common amino acids and isoacceptor tRNAs that are aminoacylated by corresponding aminoacyl-tRNA synthetases. Analysis of tRNA alignments shows that, despite the high number of tRNA genes, specific tRNA sequence motifs are highly conserved across multicellular eukaryotes. The conservation often extends throughout the isoacceptors and isodecoders with, in some cases, two sets of conserved isodecoders. This study is focused on non-Watson–Crick base pairs in the helical stems, especially GoU pairs. Each of the four helical stems may contain one or more conserved GoU pairs. Some are amino acid specific and could represent identity elements for the cognate aminoacyl tRNA synthetases. Other GoU pairs are found in more than a single amino acid and could be critical for native folding of the tRNAs. Interestingly, some GoU pairs are anticodon-specific, and others are found in phylogenetically-specific clades. Although the distribution of conservation likely reflects a balance between accommodating isotype-specific functions as well as those shared by all tRNAs essential for ribosomal translation, such conservations may indicate the existence of specialized tRNAs for specific translation targets, cellular conditions, or alternative functions.
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Affiliation(s)
- Eric Westhof
- Université de Strasbourg, Institut de Biologie Moléculaire et Cellulaire, Architecture et Réactivité de l'ARN, CNRS UPR 9002, 2, allée Konrad Roentgen, F-67084 Strasbourg, France
| | - Bryan Thornlow
- Department of Biomolecular Engineering, Baskin School of Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA.,UCSC Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Patricia P Chan
- Department of Biomolecular Engineering, Baskin School of Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA.,UCSC Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Todd M Lowe
- Department of Biomolecular Engineering, Baskin School of Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA.,UCSC Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA
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7
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Chan PP, Lin BY, Mak AJ, Lowe TM. tRNAscan-SE 2.0: improved detection and functional classification of transfer RNA genes. Nucleic Acids Res 2021; 49:9077-9096. [PMID: 34417604 PMCID: PMC8450103 DOI: 10.1093/nar/gkab688] [Citation(s) in RCA: 422] [Impact Index Per Article: 140.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 07/23/2021] [Accepted: 07/27/2021] [Indexed: 12/17/2022] Open
Abstract
tRNAscan-SE has been widely used for transfer RNA (tRNA) gene prediction for over twenty years, developed just as the first genomes were decoded. With the massive increase in quantity and phylogenetic diversity of genomes, the accurate detection and functional prediction of tRNAs has become more challenging. Utilizing a vastly larger training set, we created nearly one hundred specialized isotype- and clade-specific models, greatly improving tRNAscan-SE’s ability to identify and classify both typical and atypical tRNAs. We employ a new comparative multi-model strategy where predicted tRNAs are scored against a full set of isotype-specific covariance models, allowing functional prediction based on both the anticodon and the highest-scoring isotype model. Comparative model scoring has also enhanced the program's ability to detect tRNA-derived SINEs and other likely pseudogenes. For the first time, tRNAscan-SE also includes fast and highly accurate detection of mitochondrial tRNAs using newly developed models. Overall, tRNA detection sensitivity and specificity is improved for all isotypes, particularly those utilizing specialized models for selenocysteine and the three subtypes of tRNA genes encoding a CAU anticodon. These enhancements will provide researchers with more accurate and detailed tRNA annotation for a wider variety of tRNAs, and may direct attention to tRNAs with novel traits.
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Affiliation(s)
- Patricia P Chan
- Department of Biomolecular Engineering, Baskin School of Engineering, University of California, Santa Cruz, CA 95064, USA
| | - Brian Y Lin
- Department of Biomolecular Engineering, Baskin School of Engineering, University of California, Santa Cruz, CA 95064, USA
| | - Allysia J Mak
- Department of Biomolecular Engineering, Baskin School of Engineering, University of California, Santa Cruz, CA 95064, USA
| | - Todd M Lowe
- Department of Biomolecular Engineering, Baskin School of Engineering, University of California, Santa Cruz, CA 95064, USA
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8
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Sweeney BA, Hoksza D, Nawrocki EP, Ribas CE, Madeira F, Cannone JJ, Gutell R, Maddala A, Meade CD, Williams LD, Petrov AS, Chan PP, Lowe TM, Finn RD, Petrov AI. R2DT is a framework for predicting and visualising RNA secondary structure using templates. Nat Commun 2021; 12:3494. [PMID: 34108470 PMCID: PMC8190129 DOI: 10.1038/s41467-021-23555-5] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Accepted: 05/04/2021] [Indexed: 02/05/2023] Open
Abstract
Non-coding RNAs (ncRNA) are essential for all life, and their functions often depend on their secondary (2D) and tertiary structure. Despite the abundance of software for the visualisation of ncRNAs, few automatically generate consistent and recognisable 2D layouts, which makes it challenging for users to construct, compare and analyse structures. Here, we present R2DT, a method for predicting and visualising a wide range of RNA structures in standardised layouts. R2DT is based on a library of 3,647 templates representing the majority of known structured RNAs. R2DT has been applied to ncRNA sequences from the RNAcentral database and produced >13 million diagrams, creating the world's largest RNA 2D structure dataset. The software is amenable to community expansion, and is freely available at https://github.com/rnacentral/R2DT and a web server is found at https://rnacentral.org/r2dt .
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Affiliation(s)
- Blake A Sweeney
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - David Hoksza
- Department of Software Engineering, Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic
| | - Eric P Nawrocki
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Carlos Eduardo Ribas
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Fábio Madeira
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Jamie J Cannone
- Department of Integrative Biology, The University of Texas at Austin, Austin, TX, USA
| | - Robin Gutell
- Department of Integrative Biology, The University of Texas at Austin, Austin, TX, USA
| | - Aparna Maddala
- School of Chemistry and Biochemistry, Center for the Origins of Life, Georgia Institute of Technology, Atlanta, GA, USA
| | - Caeden D Meade
- School of Chemistry and Biochemistry, Center for the Origins of Life, Georgia Institute of Technology, Atlanta, GA, USA
| | - Loren Dean Williams
- School of Chemistry and Biochemistry, Center for the Origins of Life, Georgia Institute of Technology, Atlanta, GA, USA
| | - Anton S Petrov
- School of Chemistry and Biochemistry, Center for the Origins of Life, Georgia Institute of Technology, Atlanta, GA, USA
| | - Patricia P Chan
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Todd M Lowe
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Robert D Finn
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Anton I Petrov
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK.
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9
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Sweeney BA, Petrov AI, Ribas CE, Finn RD, Bateman A, Szymanski M, Karlowski WM, Seemann SE, Gorodkin J, Cannone JJ, Gutell RR, Kay S, Marygold S, dos Santos G, Frankish A, Mudge JM, Barshir R, Fishilevich S, Chan PP, Lowe TM, Seal R, Bruford E, Panni S, Porras P, Karagkouni D, Hatzigeorgiou AG, Ma L, Zhang Z, Volders PJ, Mestdagh P, Griffiths-Jones S, Fromm B, Peterson KJ, Kalvari I, Nawrocki EP, Petrov AS, Weng S, Bouchard-Bourelle P, Scott M, Lui LM, Hoksza D, Lovering RC, Kramarz B, Mani P, Ramachandran S, Weinberg Z. RNAcentral 2021: secondary structure integration, improved sequence search and new member databases. Nucleic Acids Res 2021; 49:D212-D220. [PMID: 33106848 PMCID: PMC7779037 DOI: 10.1093/nar/gkaa921] [Citation(s) in RCA: 115] [Impact Index Per Article: 38.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Accepted: 10/05/2020] [Indexed: 12/16/2022] Open
Abstract
RNAcentral is a comprehensive database of non-coding RNA (ncRNA) sequences that provides a single access point to 44 RNA resources and >18 million ncRNA sequences from a wide range of organisms and RNA types. RNAcentral now also includes secondary (2D) structure information for >13 million sequences, making RNAcentral the world's largest RNA 2D structure database. The 2D diagrams are displayed using R2DT, a new 2D structure visualization method that uses consistent, reproducible and recognizable layouts for related RNAs. The sequence similarity search has been updated with a faster interface featuring facets for filtering search results by RNA type, organism, source database or any keyword. This sequence search tool is available as a reusable web component, and has been integrated into several RNAcentral member databases, including Rfam, miRBase and snoDB. To allow for a more fine-grained assignment of RNA types and subtypes, all RNAcentral sequences have been annotated with Sequence Ontology terms. The RNAcentral database continues to grow and provide a central data resource for the RNA community. RNAcentral is freely available at https://rnacentral.org.
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10
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Fernandes JD, Hinrichs AS, Clawson H, Gonzalez JN, Lee BT, Nassar LR, Raney BJ, Rosenbloom KR, Nerli S, Rao AA, Schmelter D, Fyfe A, Maulding N, Zweig AS, Lowe TM, Ares M, Corbet-Detig R, Kent WJ, Haussler D, Haeussler M. The UCSC SARS-CoV-2 Genome Browser. Nat Genet 2020; 52:991-998. [PMID: 32908258 PMCID: PMC8016453 DOI: 10.1038/s41588-020-0700-8] [Citation(s) in RCA: 58] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Background: Researchers are generating molecular data pertaining to the SARS-CoV-2 RNA genome and its proteins at an unprecedented rate during the COVID-19 pandemic. As a result, there is a critical need for rapid and continuously updated access to the latest molecular data in a format in which all data can be quickly cross-referenced and compared. We adapted our genome browser visualization tool to the viral genome for this purpose. Molecular data, curated from published studies or from database submissions, are mapped to the viral genome and grouped together into “annotation tracks” where they can be visualized along the linear map of the viral genome sequence and programmatically downloaded in standard format for analysis. Results: The UCSC Genome Browser for SARS-CoV-2 (https://genome.ucsc.edu/covid19.html ) provides continuously updated access to the mutations in the many thousands of SARS-CoV-2 genomes deposited in GISAID and the international nucleotide sequencing databases, displayed alongside phylogenetic trees. These data are augmented with alignments of bat, pangolin, and other animal and human coronavirus genomes, including per-base evolutionary rate analysis. All available annotations are cross-referenced on the virus genome, including those from major databases (PDB, RFAM, IEDB, UniProt) as well as up-to-date individual results from preprints. Annotated data include predicted and validated immune epitopes, promising antibodies, RT-PCR and sequencing primers, CRISPR guides (from research, diagnostics, vaccines, and therapies), and points of interaction between human and viral genes. As a community resource, any user can add manual annotations which are quality checked and shared publicly on the browser the next day. Conclusions: We invite all investigators to contribute additional data and annotations to this resource to accelerate research and development activities globally. Contact us at genome-www@soe.ucsc.edu with data suggestions or requests for support for adding data. Rapid sharing of data will accelerate SARS-CoV-2 research, especially when researchers take time to integrate their data with those from other labs on a widely-used community browser platform with standardized machine-readable data formats, such as the SARS-CoV-2 Genome Browser.
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Affiliation(s)
- Jason D Fernandes
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
- Howard Hughes Medical Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Angie S Hinrichs
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Hiram Clawson
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | | | - Brian T Lee
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Luis R Nassar
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Brian J Raney
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Kate R Rosenbloom
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Santrupti Nerli
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Arjun A Rao
- ImmunoX Initiative, University of California San Francisco, San Francisco, CA, USA
| | - Daniel Schmelter
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Alastair Fyfe
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Nathan Maulding
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Ann S Zweig
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Todd M Lowe
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
- Center for Molecular Biology of RNA, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Manuel Ares
- Molecular, Cell and Developmental Biology, University of California, Santa Cruz, Santa Cruz, CA, USA
- Center for Molecular Biology of RNA, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Russ Corbet-Detig
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - W James Kent
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - David Haussler
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA.
- Howard Hughes Medical Institute, University of California, Santa Cruz, Santa Cruz, CA, USA.
- Center for Molecular Biology of RNA, University of California Santa Cruz, Santa Cruz, CA, USA.
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11
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Lin BY, Chan PP, Lowe TM. tRNAviz: explore and visualize tRNA sequence features. Nucleic Acids Res 2020; 47:W542-W547. [PMID: 31127306 PMCID: PMC6602477 DOI: 10.1093/nar/gkz438] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Revised: 05/06/2019] [Accepted: 05/23/2019] [Indexed: 01/12/2023] Open
Abstract
Transfer RNAs (tRNAs) are ubiquitous across the tree of life. Although tRNA structure is highly conserved, there is still significant variation in sequence features between clades, isotypes and even isodecoders. This variation not only impacts translation, but as shown by a variety of recent studies, nontranslation-associated functions are also sensitive to small changes in tRNA sequence. Despite the rapidly growing number of sequenced genomes, there is a lack of tools for both small- and large-scale comparative genomics analysis of tRNA sequence features. Here, we have integrated over 150 000 tRNAs spanning all domains of life into tRNAviz, a web application for exploring and visualizing tRNA sequence features. tRNAviz implements a framework for determining consensus sequence features and can generate sequence feature distributions by isotypes, clades and anticodons, among other tRNA properties such as score. All visualizations are interactive and exportable. The web server is publicly available at http://trna.ucsc.edu/tRNAviz/.
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Affiliation(s)
- Brian Y Lin
- Department of Biomolecular Engineering, University of California Santa Cruz, CA 95064, USA
| | - Patricia P Chan
- Department of Biomolecular Engineering, University of California Santa Cruz, CA 95064, USA
| | - Todd M Lowe
- Department of Biomolecular Engineering, University of California Santa Cruz, CA 95064, USA
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12
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Seal RL, Chen LL, Griffiths-Jones S, Lowe TM, Mathews MB, O'Reilly D, Pierce AJ, Stadler PF, Ulitsky I, Wolin SL, Bruford EA. A guide to naming human non-coding RNA genes. EMBO J 2020; 39:e103777. [PMID: 32090359 PMCID: PMC7073466 DOI: 10.15252/embj.2019103777] [Citation(s) in RCA: 64] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2019] [Revised: 01/23/2020] [Accepted: 01/30/2020] [Indexed: 12/15/2022] Open
Abstract
Research on non-coding RNA (ncRNA) is a rapidly expanding field. Providing an official gene symbol and name to ncRNA genes brings order to otherwise potential chaos as it allows unambiguous communication about each gene. The HUGO Gene Nomenclature Committee (HGNC, www.genenames.org) is the only group with the authority to approve symbols for human genes. The HGNC works with specialist advisors for different classes of ncRNA to ensure that ncRNA nomenclature is accurate and informative, where possible. Here, we review each major class of ncRNA that is currently annotated in the human genome and describe how each class is assigned a standardised nomenclature.
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Affiliation(s)
- Ruth L Seal
- Department of Haematology, University of Cambridge School of Clinical Medicine, Cambridge, UK.,European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Ling-Ling Chen
- State Key Laboratory of Molecular Biology, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Science, Shanghai, China
| | - Sam Griffiths-Jones
- School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Todd M Lowe
- Department of Biomolecular Engineering, University of California, Santa Cruz, CA, USA
| | - Michael B Mathews
- Department of Medicine, Rutgers New Jersey Medical School, Newark, NJ, USA
| | - Dawn O'Reilly
- Computational Biology and Integrative Genomics Lab, MRC/CRUK Oxford Institute and Department of Oncology, University of Oxford, Oxford, UK
| | - Andrew J Pierce
- Translational Medicine, Oncology R&D, AstraZeneca, Cambridge, UK
| | - Peter F Stadler
- Bioinformatics Group, Department of Computer Science, Interdisciplinary Center for Bioinformatics, University of Leipzig, Leipzig, Germany.,Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany.,Institute of Theoretical Chemistry, University of Vienna, Vienna, Austria.,Facultad de Ciencias, Universidad National de Colombia, Sede Bogotá, Colombia.,Santa Fe Institute, Santa Fe, USA
| | - Igor Ulitsky
- Department of Biological Regulation, Weizmann Institute of Science, Rehovot, Israel
| | - Sandra L Wolin
- RNA Biology Laboratory, National Cancer Institute, National Institutes of Health, Frederick, MD, USA
| | - Elspeth A Bruford
- Department of Haematology, University of Cambridge School of Clinical Medicine, Cambridge, UK.,European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
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13
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Thornlow BP, Armstrong J, Holmes AD, Howard JM, Corbett-Detig RB, Lowe TM. Predicting transfer RNA gene activity from sequence and genome context. Genome Res 2020; 30:85-94. [PMID: 31857444 PMCID: PMC6961574 DOI: 10.1101/gr.256164.119] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Accepted: 12/12/2019] [Indexed: 01/25/2023]
Abstract
Transfer RNA (tRNA) genes are among the most highly transcribed genes in the genome owing to their central role in protein synthesis. However, there is evidence for a broad range of gene expression across tRNA loci. This complexity, combined with difficulty in measuring transcript abundance and high sequence identity across transcripts, has severely limited our collective understanding of tRNA gene expression regulation and evolution. We establish sequence-based correlates to tRNA gene expression and develop a tRNA gene classification method that does not require, but benefits from, comparative genomic information and achieves accuracy comparable to molecular assays. We observe that guanine + cytosine (G + C) content and CpG density surrounding tRNA loci is exceptionally well correlated with tRNA gene activity, supporting a prominent regulatory role of the local genomic context in combination with internal sequence features. We use our tRNA gene activity predictions in conjunction with a comprehensive tRNA gene ortholog set spanning 29 placental mammals to estimate the evolutionary rate of functional changes among orthologs. Our method adds a new dimension to large-scale tRNA functional prediction and will help prioritize characterization of functional tRNA variants. Its simplicity and robustness should enable development of similar approaches for other clades, as well as exploration of functional diversification of members of large gene families.
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Affiliation(s)
- Bryan P Thornlow
- Department of Biomolecular Engineering, University of California, Santa Cruz, California 95064, USA
| | - Joel Armstrong
- Department of Biomolecular Engineering, University of California, Santa Cruz, California 95064, USA
- Genomics Institute, University of California, Santa Cruz, California 95064, USA
| | - Andrew D Holmes
- Department of Biomolecular Engineering, University of California, Santa Cruz, California 95064, USA
| | - Jonathan M Howard
- Department of Biomolecular Engineering, University of California, Santa Cruz, California 95064, USA
| | - Russell B Corbett-Detig
- Department of Biomolecular Engineering, University of California, Santa Cruz, California 95064, USA
- Genomics Institute, University of California, Santa Cruz, California 95064, USA
| | - Todd M Lowe
- Department of Biomolecular Engineering, University of California, Santa Cruz, California 95064, USA
- Genomics Institute, University of California, Santa Cruz, California 95064, USA
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14
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Lui LM, Uzilov AV, Bernick DL, Corredor A, Lowe TM, Dennis PP. Methylation guide RNA evolution in archaea: structure, function and genomic organization of 110 C/D box sRNA families across six Pyrobaculum species. Nucleic Acids Res 2019; 46:5678-5691. [PMID: 29771354 PMCID: PMC6009581 DOI: 10.1093/nar/gky284] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2017] [Accepted: 04/23/2018] [Indexed: 12/21/2022] Open
Abstract
Archaeal homologs of eukaryotic C/D box small nucleolar RNAs (C/D box sRNAs) guide precise 2′-O-methyl modification of ribosomal and transfer RNAs. Although C/D box sRNA genes constitute one of the largest RNA gene families in archaeal thermophiles, most genomes have incomplete sRNA gene annotation because reliable, fully automated detection methods are not available. We expanded and curated a comprehensive gene set across six species of the crenarchaeal genus Pyrobaculum, particularly rich in C/D box sRNA genes. Using high-throughput small RNA sequencing, specialized computational searches and comparative genomics, we analyzed 526 Pyrobaculum C/D box sRNAs, organizing them into 110 families based on synteny and conservation of guide sequences which determine methylation targets. We examined gene duplications and rearrangements, including one family that has expanded in a pattern similar to retrotransposed repetitive elements in eukaryotes. New training data and inclusion of kink-turn secondary structural features enabled creation of an improved search model. Our analyses provide the most comprehensive, dynamic view of C/D box sRNA evolutionary history within a genus, in terms of modification function, feature plasticity, and gene mobility.
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Affiliation(s)
- Lauren M Lui
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Andrew V Uzilov
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - David L Bernick
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Andrea Corredor
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Todd M Lowe
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Patrick P Dennis
- Department of Biology, Whitman College, Walla Walla, WA 99362, USA
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15
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de Crécy-Lagard V, Boccaletto P, Mangleburg CG, Sharma P, Lowe TM, Leidel SA, Bujnicki JM. Matching tRNA modifications in humans to their known and predicted enzymes. Nucleic Acids Res 2019; 47:2143-2159. [PMID: 30698754 PMCID: PMC6412123 DOI: 10.1093/nar/gkz011] [Citation(s) in RCA: 93] [Impact Index Per Article: 18.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2018] [Revised: 12/28/2018] [Accepted: 01/10/2019] [Indexed: 12/25/2022] Open
Abstract
tRNA are post-transcriptionally modified by chemical modifications that affect all aspects of tRNA biology. An increasing number of mutations underlying human genetic diseases map to genes encoding for tRNA modification enzymes. However, our knowledge on human tRNA-modification genes remains fragmentary and the most comprehensive RNA modification database currently contains information on approximately 20% of human cytosolic tRNAs, primarily based on biochemical studies. Recent high-throughput methods such as DM-tRNA-seq now allow annotation of a majority of tRNAs for six specific base modifications. Furthermore, we identified large gaps in knowledge when we predicted all cytosolic and mitochondrial human tRNA modification genes. Only 48% of the candidate cytosolic tRNA modification enzymes have been experimentally validated in mammals (either directly or in a heterologous system). Approximately 23% of the modification genes (cytosolic and mitochondrial combined) remain unknown. We discuss these 'unidentified enzymes' cases in detail and propose candidates whenever possible. Finally, tissue-specific expression analysis shows that modification genes are highly expressed in proliferative tissues like testis and transformed cells, but scarcely in differentiated tissues, with the exception of the cerebellum. Our work provides a comprehensive up to date compilation of human tRNA modifications and their enzymes that can be used as a resource for further studies.
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Affiliation(s)
- Valérie de Crécy-Lagard
- Department of Microbiology and Cell Sciences, University of Florida, Gainesville, FL 32611, USA
- Cancer and Genetic Institute, University of Florida, Gainesville, FL 32611, USA
| | - Pietro Boccaletto
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology, ul. Trojdena 4, 02-109 Warsaw, Poland
| | - Carl G Mangleburg
- Department of Microbiology and Cell Sciences, University of Florida, Gainesville, FL 32611, USA
| | - Puneet Sharma
- Max Planck Research Group for RNA Biology, Max Planck Institute for Molecular Biomedicine, 48149 Muenster, Germany
- Cells-in-Motion Cluster of Excellence, University of Muenster, 48149 Muenster, Germany
| | - Todd M Lowe
- Department of Biomolecular Engineering, University of California, Santa Cruz, Santa Cruz, CA 95064, USA
| | - Sebastian A Leidel
- Max Planck Research Group for RNA Biology, Max Planck Institute for Molecular Biomedicine, 48149 Muenster, Germany
- Cells-in-Motion Cluster of Excellence, University of Muenster, 48149 Muenster, Germany
- Research Group for RNA Biochemistry, Institute of Chemistry and Biochemistry, University of Bern, 3012 Bern, Switzerland
| | - Janusz M Bujnicki
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology, ul. Trojdena 4, 02-109 Warsaw, Poland
- Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, ul. Umultowska 89, 61-614 Poznań, Poland
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16
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Abstract
Transfer RNAs are the largest, most complex non-coding RNA family, universal to all living organisms. tRNAscan-SE has been the de facto tool for predicting tRNA genes in whole genomes. The newly developed version 2.0 has incorporated advanced methodologies with improved probabilistic search software and a suite of new gene models, enabling better functional classification of predicted genes. This chapter describes the use of the UNIX command-driven and online web versions, illustrating different search modes and options.
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Affiliation(s)
- Patricia P Chan
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Todd M Lowe
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, USA.
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17
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Abstract
Transfer RNAs (tRNAs) are a central component for the biological synthesis of proteins, and they are among the most highly conserved and frequently transcribed genes in all living things. Despite their clear significance for fundamental cellular processes, the forces governing tRNA evolution are poorly understood. We present evidence that transcription-associated mutagenesis and strong purifying selection are key determinants of patterns of sequence variation within and surrounding tRNA genes in humans and diverse model organisms. Remarkably, the mutation rate at broadly expressed cytosolic tRNA loci is likely between 7 and 10 times greater than the nuclear genome average. Furthermore, evolutionary analyses provide strong evidence that tRNA genes, but not their flanking sequences, experience strong purifying selection acting against this elevated mutation rate. We also find a strong correlation between tRNA expression levels and the mutation rates in their immediate flanking regions, suggesting a simple method for estimating individual tRNA gene activity. Collectively, this study illuminates the extreme competing forces in tRNA gene evolution and indicates that mutations at tRNA loci contribute disproportionately to mutational load and have unexplored fitness consequences in human populations.
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Affiliation(s)
- Bryan P Thornlow
- Department of Biomolecular Engineering, University of California, Santa Cruz, CA 95064
| | - Josh Hough
- Department of Biomolecular Engineering, University of California, Santa Cruz, CA 95064
| | - Jacquelyn M Roger
- Department of Biomolecular Engineering, University of California, Santa Cruz, CA 95064
| | - Henry Gong
- Department of Biomolecular Engineering, University of California, Santa Cruz, CA 95064
| | - Todd M Lowe
- Department of Biomolecular Engineering, University of California, Santa Cruz, CA 95064;
- Genomics Institute, University of California, Santa Cruz, CA 95064
| | - Russell B Corbett-Detig
- Department of Biomolecular Engineering, University of California, Santa Cruz, CA 95064;
- Genomics Institute, University of California, Santa Cruz, CA 95064
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18
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Petrov AI, Kay SJE, Kalvari I, Howe KL, Gray KA, Bruford EA, Kersey PJ, Cochrane G, Finn RD, Bateman A, Kozomara A, Griffiths-Jones S, Frankish A, Zwieb CW, Lau BY, Williams KP, Chan PP, Lowe TM, Cannone JJ, Gutell R, Machnicka MA, Bujnicki JM, Yoshihama M, Kenmochi N, Chai B, Cole JR, Szymanski M, Karlowski WM, Wood V, Huala E, Berardini TZ, Zhao Y, Chen R, Zhu W, Paraskevopoulou MD, Vlachos IS, Hatzigeorgiou AG, Ma L, Zhang Z, Puetz J, Stadler PF, McDonald D, Basu S, Fey P, Engel SR, Cherry JM, Volders PJ, Mestdagh P, Wower J, Clark MB, Quek XC, Dinger ME. RNAcentral: a comprehensive database of non-coding RNA sequences. Nucleic Acids Res 2017; 45:D128-D134. [PMID: 27794554 PMCID: PMC5210518 DOI: 10.1093/nar/gkw1008] [Citation(s) in RCA: 132] [Impact Index Per Article: 18.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2016] [Revised: 10/13/2016] [Accepted: 10/18/2016] [Indexed: 12/12/2022] Open
Abstract
RNAcentral is a database of non-coding RNA (ncRNA) sequences that aggregates data from specialised ncRNA resources and provides a single entry point for accessing ncRNA sequences of all ncRNA types from all organisms. Since its launch in 2014, RNAcentral has integrated twelve new resources, taking the total number of collaborating database to 22, and began importing new types of data, such as modified nucleotides from MODOMICS and PDB. We created new species-specific identifiers that refer to unique RNA sequences within a context of single species. The website has been subject to continuous improvements focusing on text and sequence similarity searches as well as genome browsing functionality. All RNAcentral data is provided for free and is available for browsing, bulk downloads, and programmatic access at http://rnacentral.org/.
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19
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Hrabeta-Robinson E, Marcus E, Cozen AE, Phizicky EM, Lowe TM. High-Throughput Small RNA Sequencing Enhanced by AlkB-Facilitated RNA de-Methylation (ARM-Seq). Methods Mol Biol 2017; 1562:231-243. [PMID: 28349464 PMCID: PMC5587177 DOI: 10.1007/978-1-4939-6807-7_15] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/11/2023]
Abstract
N 1-methyladenosine (m1A), N 3-methylcytidine (m3C), and N 1-methylguanosine (m1G) are common in transfer RNA (tRNA) and tRNA-derived fragments. These modifications alter Watson-Crick base-pairing, and cause pauses or stops during reverse transcription required for most high-throughput RNA sequencing protocols, resulting in inefficient detection of methyl-modified RNAs. Here, we describe a procedure to demethylate RNAs containing m1A, m3C, or m1G using the Escherichia coli dealkylating enzyme AlkB, along with instructions for subsequent processing with widely used protocols for small RNA sequencing.
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Affiliation(s)
- Eva Hrabeta-Robinson
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, California, USA
| | - Erin Marcus
- Department of Biochemistry & Biophysics, Center for RNA Biology, University of Rochester School of Medicine, Rochester, NY, 14642
| | - Aaron E. Cozen
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, California, USA
| | - Eric M. Phizicky
- Department of Biochemistry & Biophysics, Center for RNA Biology, University of Rochester School of Medicine, Rochester, NY, 14642
| | - Todd M. Lowe
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, California, USA
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20
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Zhang X, Cozen AE, Liu Y, Chen Q, Lowe TM. Small RNA Modifications: Integral to Function and Disease. Trends Mol Med 2016; 22:1025-1034. [PMID: 27840066 DOI: 10.1016/j.molmed.2016.10.009] [Citation(s) in RCA: 75] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2016] [Accepted: 10/14/2016] [Indexed: 02/07/2023]
Abstract
Small RNAs have the potential to store a secondary layer of labile biological information in the form of modified nucleotides. Emerging evidence has shown that small RNAs including microRNAs (miRNAs), PIWI-interacting RNAs (piRNAs) and tRNA-derived small RNAs (tsRNAs) harbor a diversity of RNA modifications. These findings highlight the importance of RNA modifications in the modulation of basic properties such as RNA stability and other complex physiological processes involved in stress responses, metabolism, immunity, and epigenetic inheritance of environmentally acquired traits, among others. High-resolution, high-throughput methods for detecting, mapping and screening these small RNA modifications now provide opportunities to uncover their diagnostic potential as sensitive disease markers.
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Affiliation(s)
- Xudong Zhang
- Department of Physiology and Cell Biology, University of Nevada, Reno School of Medicine, Reno, NV 89557, USA
| | - Aaron E Cozen
- Department of Biomolecular Engineering, University of California, Santa Cruz, Santa Cruz, CA 95064, USA
| | - Ying Liu
- Department of Physiology and Cell Biology, University of Nevada, Reno School of Medicine, Reno, NV 89557, USA
| | - Qi Chen
- Department of Physiology and Cell Biology, University of Nevada, Reno School of Medicine, Reno, NV 89557, USA.
| | - Todd M Lowe
- Department of Biomolecular Engineering, University of California, Santa Cruz, Santa Cruz, CA 95064, USA.
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21
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Lowe TM, Chan PP. tRNAscan-SE On-line: integrating search and context for analysis of transfer RNA genes. Nucleic Acids Res 2016; 44:W54-7. [PMID: 27174935 PMCID: PMC4987944 DOI: 10.1093/nar/gkw413] [Citation(s) in RCA: 1726] [Impact Index Per Article: 215.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2016] [Accepted: 05/04/2016] [Indexed: 02/07/2023] Open
Abstract
High-throughput genome sequencing continues to grow the need for rapid, accurate genome annotation and tRNA genes constitute the largest family of essential, ever-present non-coding RNA genes. Newly developed tRNAscan-SE 2.0 has advanced the state-of-the-art methodology in tRNA gene detection and functional prediction, captured by rich new content of the companion Genomic tRNA Database. Previously, web-server tRNA detection was isolated from knowledge of existing tRNAs and their annotation. In this update of the tRNAscan-SE On-line resource, we tie together improvements in tRNA classification with greatly enhanced biological context via dynamically generated links between web server search results, the most relevant genes in the GtRNAdb and interactive, rich genome context provided by UCSC genome browsers. The tRNAscan-SE On-line web server can be accessed at http://trna.ucsc.edu/tRNAscan-SE/.
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Affiliation(s)
- Todd M Lowe
- Department of Biomolecular Engineering, University of California Santa Cruz, CA 95064, USA
| | - Patricia P Chan
- Department of Biomolecular Engineering, University of California Santa Cruz, CA 95064, USA
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22
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Chan PP, Lowe TM. GtRNAdb 2.0: an expanded database of transfer RNA genes identified in complete and draft genomes. Nucleic Acids Res 2015; 44:D184-9. [PMID: 26673694 PMCID: PMC4702915 DOI: 10.1093/nar/gkv1309] [Citation(s) in RCA: 566] [Impact Index Per Article: 62.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2015] [Accepted: 11/09/2015] [Indexed: 12/12/2022] Open
Abstract
Transfer RNAs represent the largest, most ubiquitous class of non-protein coding RNA genes found in all living organisms. The tRNAscan-SE search tool has become the de facto standard for annotating tRNA genes in genomes, and the Genomic tRNA Database (GtRNAdb) was created as a portal for interactive exploration of these gene predictions. Since its published description in 2009, the GtRNAdb has steadily grown in content, and remains the most commonly cited web-based source of tRNA gene information. In this update, we describe not only a major increase in the number of tRNA predictions (>367000) and genomes analyzed (>4370), but more importantly, the integration of new analytic and functional data to improve the quality and biological context of tRNA gene predictions. New information drawn from other sources includes tRNA modification data, epigenetic data, single nucleotide polymorphisms, gene expression and evolutionary conservation. A richer set of analytic data is also presented, including better tRNA functional prediction, non-canonical features, predicted structural impacts from sequence variants and minimum free energy structural predictions. Views of tRNA genes in genomic context are provided via direct links to the UCSC genome browsers. The database can be searched by sequence or gene features, and is available at http://gtrnadb.ucsc.edu/.
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Affiliation(s)
- Patricia P Chan
- Department of Biomolecular Engineering, University of California Santa Cruz, CA 95064, USA
| | - Todd M Lowe
- Department of Biomolecular Engineering, University of California Santa Cruz, CA 95064, USA
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23
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Cozen AE, Quartley E, Holmes AD, Hrabeta-Robinson E, Phizicky EM, Lowe TM. ARM-seq: AlkB-facilitated RNA methylation sequencing reveals a complex landscape of modified tRNA fragments. Nat Methods 2015; 12:879-84. [PMID: 26237225 PMCID: PMC4553111 DOI: 10.1038/nmeth.3508] [Citation(s) in RCA: 290] [Impact Index Per Article: 32.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2015] [Accepted: 07/09/2015] [Indexed: 01/02/2023]
Abstract
High throughput RNA sequencing has accelerated discovery of the complex regulatory roles of small RNAs, but RNAs containing modified nucleosides may escape detection when those modifications interfere with reverse transcription during RNA-seq library preparation. Here we describe AlkB-facilitated RNA Methylation sequencing (ARM-Seq) which uses pre-treatment with Escherichia coli AlkB to demethylate 1-methyladenosine, 3-methylcytidine, and 1-methylguanosine, all commonly found in transfer RNAs. Comparative methylation analysis using ARM-Seq provides the first detailed, transcriptome-scale map of these modifications, and reveals an abundance of previously undetected, methylated small RNAs derived from tRNAs. ARM-Seq demonstrates that tRNA-derived small RNAs accurately recapitulate the m1A modification state for well-characterized yeast tRNAs, and generates new predictions for a large number of human tRNAs, including tRNA precursors and mitochondrial tRNAs. Thus, ARM-Seq provides broad utility for identifying previously overlooked methyl-modified RNAs, can efficiently monitor methylation state, and may reveal new roles for tRNA-derived RNAs as biomarkers or signaling molecules.
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Affiliation(s)
- Aaron E Cozen
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, California, USA
| | - Erin Quartley
- Department of Biochemistry &Biophysics, University of Rochester School of Medicine, Rochester, New York, USA
| | - Andrew D Holmes
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, California, USA
| | - Eva Hrabeta-Robinson
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, California, USA
| | - Eric M Phizicky
- Department of Biochemistry &Biophysics, University of Rochester School of Medicine, Rochester, New York, USA.,Center for RNA Biology, University of Rochester School of Medicine, Rochester, New York, USA
| | - Todd M Lowe
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, California, USA
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24
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Petrov AI, Kay SJE, Gibson R, Kulesha E, Staines D, Bruford EA, Wright MW, Burge S, Finn RD, Kersey PJ, Cochrane G, Bateman A, Griffiths-Jones S, Harrow J, Chan PP, Lowe TM, Zwieb CW, Wower J, Williams KP, Hudson CM, Gutell R, Clark MB, Dinger M, Quek XC, Bujnicki JM, Chua NH, Liu J, Wang H, Skogerbø G, Zhao Y, Chen R, Zhu W, Cole JR, Chai B, Huang HD, Huang HY, Cherry JM, Hatzigeorgiou A, Pruitt KD. RNAcentral: an international database of ncRNA sequences. Nucleic Acids Res 2014; 43:D123-9. [PMID: 25352543 PMCID: PMC4384043 DOI: 10.1093/nar/gku991] [Citation(s) in RCA: 86] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Abstract
The field of non-coding RNA biology has been hampered by the lack of availability of a
comprehensive, up-to-date collection of accessioned RNA sequences. Here we present the
first release of RNAcentral, a database that collates and integrates information from an
international consortium of established RNA sequence databases. The initial release
contains over 8.1 million sequences, including representatives of all major functional
classes. A web portal (http://rnacentral.org) provides free access to data, search functionality,
cross-references, source code and an integrated genome browser for selected species.
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25
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Miller HK, Kwuan L, Schwiesow L, Bernick DL, Mettert E, Ramirez HA, Ragle JM, Chan PP, Kiley PJ, Lowe TM, Auerbuch V. IscR is essential for yersinia pseudotuberculosis type III secretion and virulence. PLoS Pathog 2014; 10:e1004194. [PMID: 24945271 PMCID: PMC4055776 DOI: 10.1371/journal.ppat.1004194] [Citation(s) in RCA: 47] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2013] [Accepted: 05/06/2014] [Indexed: 11/19/2022] Open
Abstract
Type III secretion systems (T3SS) are essential for virulence in dozens of pathogens, but are not required for growth outside the host. Therefore, the T3SS of many bacterial species are under tight regulatory control. To increase our understanding of the molecular mechanisms behind T3SS regulation, we performed a transposon screen to identify genes important for T3SS function in the food-borne pathogen Yersinia pseudotuberculosis. We identified two unique transposon insertions in YPTB2860, a gene that displays 79% identity with the E. coliiron-sulfur cluster regulator, IscR. A Y. pseudotuberculosis iscR in-frame deletion mutant (ΔiscR) was deficient in secretion of Ysc T3SS effector proteins and in targeting macrophages through the T3SS. To determine the mechanism behind IscR control of the Ysc T3SS, we carried out transcriptome and bioinformatic analysis to identify Y. pseudotuberculosis genes regulated by IscR. We discovered a putative IscR binding motif upstream of the Y. pseudotuberculosis yscW-lcrF operon. As LcrF controls transcription of a number of critical T3SS genes in Yersinia, we hypothesized that Yersinia IscR may control the Ysc T3SS through LcrF. Indeed, purified IscR bound to the identified yscW-lcrF promoter motif and mRNA levels of lcrF and 24 other T3SS genes were reduced in Y. pseudotuberculosis in the absence of IscR. Importantly, mice orally infected with the Y. pseudotuberculosis ΔiscR mutant displayed decreased bacterial burden in Peyer's patches, mesenteric lymph nodes, spleens, and livers, indicating an essential role for IscR in Y. pseudotuberculosis virulence. This study presents the first characterization of Yersinia IscR and provides evidence that IscR is critical for virulence and type III secretion through direct regulation of the T3SS master regulator, LcrF. Bacterial pathogens use regulators that sense environmental cues to enhance their fitness. Here, we identify a transcriptional regulator in the human gut pathogen, Yersinia pseudotuberculosis, which controls a specialized secretion system essential for bacterial growth in mammalian tissues. This regulator was shown in other bacterial species to alter its activity in response to changes in iron concentration and oxidative stress, but has never been studied in Yersinia. Importantly, Y. pseudotuberculosis experiences large changes in iron bioavailability upon transit from the gut to deeper tissues and iron is a critical component in Yersinia virulence, as individuals with iron overload disorders have enhanced susceptibility to systemic Yersinia infections. Our work places this iron-modulated transcriptional regulator within the regulatory network that controls virulence gene expression in Y. pseudotuberculosis, identifying it as a potential new target for antimicrobial agents.
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Affiliation(s)
- Halie K. Miller
- Department of Microbiology and Environmental Toxicology, University of California Santa Cruz, Santa Cruz, California, United States of America
| | - Laura Kwuan
- Department of Microbiology and Environmental Toxicology, University of California Santa Cruz, Santa Cruz, California, United States of America
| | - Leah Schwiesow
- Department of Microbiology and Environmental Toxicology, University of California Santa Cruz, Santa Cruz, California, United States of America
| | - David L. Bernick
- Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, California, United States of America
| | - Erin Mettert
- Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Hector A. Ramirez
- Department of Microbiology and Environmental Toxicology, University of California Santa Cruz, Santa Cruz, California, United States of America
| | - James M. Ragle
- Department of Molecular, Cell, and Developmental Biology, University of California Santa Cruz, Santa Cruz, California, United States of America
| | - Patricia P. Chan
- Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, California, United States of America
| | - Patricia J. Kiley
- Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Todd M. Lowe
- Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, California, United States of America
| | - Victoria Auerbuch
- Department of Microbiology and Environmental Toxicology, University of California Santa Cruz, Santa Cruz, California, United States of America
- * E-mail:
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26
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Chan PP, Cozen AE, Lowe TM. Reclassification of
Thermoproteus neutrophilus
Stetter and Zillig 1989 as Pyrobaculum neutrophilum comb. nov. based on phylogenetic analysis. Int J Syst Evol Microbiol 2013; 63:751-754. [DOI: 10.1099/ijs.0.043091-0] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The hyperthermophilic crenarchaeon
Thermoproteus neutrophilus
V24StaT was originally classified before sequence-based phylogenetic analysis became standard for bacterial taxonomy. Subsequent phylogenetic analyses by various groups have shown that strain V24StaT groups more closely with strains of the genus
Pyrobaculum
than with those in the genus
Thermoproteus
. Based on phylogenetic comparison of rRNA gene sequences and ribosomal proteins, we propose that strain V24StaT be reclassified as Pyrobaculum neutrophilum comb. nov., with the type strain V24StaT ( = DSM 2338T = JCM 9278T). An emended description of the genus
Pyrobaculum
is also presented.
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Affiliation(s)
- Patricia P. Chan
- Department of Biomolecular Engineering, University of California, Santa Cruz, 1156 High Street, SOE-2, Santa Cruz, CA 95064, USA
| | - Aaron E. Cozen
- Department of Biomolecular Engineering, University of California, Santa Cruz, 1156 High Street, SOE-2, Santa Cruz, CA 95064, USA
| | - Todd M. Lowe
- Department of Biomolecular Engineering, University of California, Santa Cruz, 1156 High Street, SOE-2, Santa Cruz, CA 95064, USA
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27
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Robb FT, Lowe TM, Kelman Z. The modern "3G" age of archaeal molecular biology. Front Microbiol 2012; 3:430. [PMID: 23267357 PMCID: PMC3527003 DOI: 10.3389/fmicb.2012.00430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2012] [Accepted: 12/06/2012] [Indexed: 11/13/2022] Open
Affiliation(s)
- Frank T Robb
- Institute of Marine and Environmental Technology Baltimore, MD, USA ; University of Maryland School of Medicine Baltimore, MD, USA
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28
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Abstract
The RNA component of the RNase P complex is found throughout most branches of the tree of life and is principally responsible for removing the 5' leader sequence from pre-tRNA transcripts during tRNA maturation. RNase P RNA has a number of universal core features, however variations in sequence and structure found in homologs across the tree of life require multiple Rfam covariance search models to detect accurately. We describe a new Rfam search model to enable efficient detection of the diminutive archaeal Type T RNase P RNAs, which are missed by existing Rfam models. Using the new model, we establish effective score detection thresholds, and detect four new RNase P RNA genes in recently completed genomes from the crenarchaeal family Thermoproteaceae.
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Affiliation(s)
- Patricia P Chan
- Department of Biomolecular Engineering, University of California Santa Cruz, CA, USA
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29
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Abstract
Pyrobaculum oguniense TE7 is an aerobic hyperthermophilic crenarchaeon isolated from a hot spring in Japan. Here we describe its main chromosome of 2,436,033 bp, with three large-scale inversions and an extra-chromosomal element of 16,887 bp. We have annotated 2,800 protein-coding genes and 145 RNA genes in this genome, including nine H/ACA-like small RNA, 83 predicted C/D box small RNA, and 47 transfer RNA genes. Comparative analyses with the closest known relative, the anaerobe Pyrobaculum arsenaticum from Italy, reveals unexpectedly high synteny and nucleotide identity between these two geographically distant species. Deep sequencing of a mixture of genomic DNA from multiple cells has illuminated some of the genome dynamics potentially shared with other species in this genus.
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Affiliation(s)
- David L Bernick
- Biomolecular Engineering, University of California., Santa Cruz, California, USA
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30
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Bernick DL, Cox CL, Dennis PP, Lowe TM. Comparative genomic and transcriptional analyses of CRISPR systems across the genus Pyrobaculum. Front Microbiol 2012; 3:251. [PMID: 22811677 PMCID: PMC3396285 DOI: 10.3389/fmicb.2012.00251] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2012] [Accepted: 06/24/2012] [Indexed: 11/29/2022] Open
Abstract
Within the domain Archaea, the CRISPR immune system appears to be nearly ubiquitous based on computational genome analyses. Initial studies in bacteria demonstrated that the CRISPR system targets invading plasmid and viral DNA. Recent experiments in the model archaeon Pyrococcus furiosus have uncovered a novel RNA-targeting variant of the CRISPR system. Because our understanding of CRISPR system evolution in other archaea is limited, we have taken a comparative genomic and transcriptomic view of the CRISPR arrays across six diverse species within the crenarchaeal genus Pyrobaculum. We present transcriptional data from each of four species in the genus (P. aerophilum, P. islandicum, P. calidifontis, P. arsenaticum), analyzing mature CRISPR-associated small RNA abundance from over 20 arrays. Within the genus, there is remarkable conservation of CRISPR array structure, as well as unique features that are have not been studied in other archaeal systems. These unique features include: a nearly invariant CRISPR promoter, conservation of direct repeat families, the 5′ polarity of CRISPR-associated small RNA abundance, and a novel CRISPR-specific association with homologues of nurA and herA. These analyses provide a genus-level evolutionary perspective on archaeal CRISPR systems, broadening our understanding beyond existing non-comparative model systems.
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Affiliation(s)
- David L Bernick
- Department of Biomolecular Engineering, University of California, Santa Cruz CA, USA
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31
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Bernick DL, Dennis PP, Lui LM, Lowe TM. Diversity of Antisense and Other Non-Coding RNAs in Archaea Revealed by Comparative Small RNA Sequencing in Four Pyrobaculum Species. Front Microbiol 2012; 3:231. [PMID: 22783241 PMCID: PMC3388794 DOI: 10.3389/fmicb.2012.00231] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2012] [Accepted: 06/06/2012] [Indexed: 12/04/2022] Open
Abstract
A great diversity of small, non-coding RNA (ncRNA) molecules with roles in gene regulation and RNA processing have been intensely studied in eukaryotic and bacterial model organisms, yet our knowledge of possible parallel roles for small RNAs (sRNA) in archaea is limited. We employed RNA-seq to identify novel sRNA across multiple species of the hyperthermophilic genus Pyrobaculum, known for unusual RNA gene characteristics. By comparing transcriptional data collected in parallel among four species, we were able to identify conserved RNA genes fitting into known and novel families. Among our findings, we highlight three novel cis-antisense sRNAs encoded opposite to key regulatory (ferric uptake regulator), metabolic (triose-phosphate isomerase), and core transcriptional apparatus genes (transcription factor B). We also found a large increase in the number of conserved C/D box sRNA genes over what had been previously recognized; many of these genes are encoded antisense to protein coding genes. The conserved opposition to orthologous genes across the Pyrobaculum genus suggests similarities to other cis-antisense regulatory systems. Furthermore, the genus-specific nature of these sRNAs indicates they are relatively recent, stable adaptations.
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Affiliation(s)
- David L Bernick
- Department of Biomolecular Engineering, University of California Santa Cruz, CA, USA
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32
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Ochs SM, Thumann S, Richau R, Weirauch MT, Lowe TM, Thomm M, Hausner W. Activation of archaeal transcription mediated by recruitment of transcription factor B. J Biol Chem 2012; 287:18863-71. [PMID: 22496454 DOI: 10.1074/jbc.m112.365742] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
Archaeal promoters consist of a TATA box and a purine-rich adjacent upstream sequence (transcription factor B (TFB)-responsive element (BRE)), which are bound by the transcription factors TATA box-binding protein (TBP) and TFB. Currently, only a few activators of archaeal transcription have been experimentally characterized. The best studied activator, Ptr2, mediates activation by recruitment of TBP. Here, we present a detailed biochemical analysis of an archaeal transcriptional activator, PF1088, which was identified in Pyrococcus furiosus by a bioinformatic approach. Operon predictions suggested that an upstream gene, pf1089, is polycistronically transcribed with pf1088. We demonstrate that PF1088 stimulates in vitro transcription by up to 7-fold when the pf1089 promoter is used as a template. By DNase I and hydroxyl radical footprinting experiments, we show that the binding site of PF1088 is located directly upstream of the BRE of pf1089. Mutational analysis indicated that activation requires the presence of the binding site for PF1088. Furthermore, we show that activation of transcription by PF1088 is dependent upon the presence of an imperfect BRE and is abolished when the pf1089 BRE is replaced with a BRE from a strong archaeal promoter. Gel shift experiments showed that TFB recruitment to the pf1089 operon is stimulated by PF1088, and TFB seems to stabilize PF1088 operator binding even in the absence of TBP. Taken together, these results represent the first biochemical evidence for a transcriptional activator working as a TFB recruitment factor in Archaea, for which the designation TFB-RF1 is suggested.
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Affiliation(s)
- Simon M Ochs
- Lehrstuhl für Mikrobiologie, Universität Regensburg, Regensburg, Germany
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33
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Zargar K, Conrad A, Bernick DL, Lowe TM, Stolc V, Hoeft S, Oremland RS, Stolz J, Saltikov CW. ArxA, a new clade of arsenite oxidase within the DMSO reductase family of molybdenum oxidoreductases. Environ Microbiol 2012; 14:1635-45. [DOI: 10.1111/j.1462-2920.2012.02722.x] [Citation(s) in RCA: 104] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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34
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Bernick DL, Dennis PP, Höchsmann M, Lowe TM. Discovery of Pyrobaculum small RNA families with atypical pseudouridine guide RNA features. RNA 2012; 18:402-11. [PMID: 22282340 PMCID: PMC3285929 DOI: 10.1261/rna.031385.111] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2011] [Accepted: 11/18/2011] [Indexed: 05/31/2023]
Abstract
In the Eukarya and Archaea, small RNA-guided pseudouridine modification is believed to be an essential step in ribosomal RNA maturation. While readily modeled and identified by computational methods in eukaryotic species, these guide RNAs have not been found in most archaeal genomes. Using high-throughput transcriptome sequencing and comparative genomics, we have identified ten novel small RNA families that appear to function as H/ACA pseudouridylation guide sRNAs, yet surprisingly lack several expected canonical features. The new RNA genes are transcribed and highly conserved across at least six species in the archaeal hyperthermophilic genus Pyrobaculum. The sRNAs exhibit a single hairpin structure interrupted by a conserved kink-turn motif, yet only two of ten families contain the complete canonical structure found in all other H/ACA sRNAs. Half of the sRNAs lack the conserved 3'-terminal ACA sequence, and many contain only a single 3' guide region rather than the canonical 5' and 3' bipartite guides. The predicted sRNA structures contain guide sequences that exhibit strong complementarity to ribosomal RNA or transfer RNA. Most of the predicted targets of pseudouridine modification are structurally equivalent to those known in other species. One sRNA appears capable of guiding pseudouridine modification at positions U54 and U55 in most or all Pyrobaculum tRNAs. We experimentally tested seven predicted pseudouridine modifications in ribosomal RNA, and all but one was confirmed. The structural insights provided by this new set of Pyrobaculum sRNAs will augment existing models and may facilitate the identification and characterization of new guide sRNAs in other archaeal species.
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Affiliation(s)
- David L. Bernick
- Department of Biomolecular Engineering, University of California, Santa Cruz, California 95064, USA
| | - Patrick P. Dennis
- Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia 20147, USA
| | - Matthias Höchsmann
- Department of Biomolecular Engineering, University of California, Santa Cruz, California 95064, USA
| | - Todd M. Lowe
- Department of Biomolecular Engineering, University of California, Santa Cruz, California 95064, USA
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35
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Abstract
The UCSC Archaeal Genome Browser (http://archaea.ucsc.edu) offers a graphical web-based resource for exploration and discovery within archaeal and other selected microbial genomes. By bringing together existing gene annotations, gene expression data, multiple-genome alignments, pre-computed sequence comparisons and other specialized analysis tracks, the genome browser is a powerful aggregator of varied genomic information. The genome browser environment maintains the current look-and-feel of the vertebrate UCSC Genome Browser, but also integrates archaeal and bacterial-specific tracks with a few graphic display enhancements. The browser currently contains 115 archaeal genomes, plus 31 genomes of viruses known to infect archaea. Some of the recently developed or enhanced tracks visualize data from published high-throughput RNA-sequencing studies, the NCBI Conserved Domain Database, sequences from pre-genome sequencing studies, predicted gene boundaries from three different protein gene prediction algorithms, tRNAscan-SE gene predictions with RNA secondary structures and CRISPR locus predictions. We have also developed a companion resource, the Archaeal COG Browser, to provide better search and display of arCOG gene function classifications, including their phylogenetic distribution among available archaeal genomes.
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Affiliation(s)
- Patricia P Chan
- Department of Biomolecular Engineering, University of California, Santa Cruz, 1156 High Street, SOE-2, Santa Cruz, CA 95064, USA
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36
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Bateman A, Agrawal S, Birney E, Bruford EA, Bujnicki JM, Cochrane G, Cole JR, Dinger ME, Enright AJ, Gardner PP, Gautheret D, Griffiths-Jones S, Harrow J, Herrero J, Holmes IH, Huang HD, Kelly KA, Kersey P, Kozomara A, Lowe TM, Marz M, Moxon S, Pruitt KD, Samuelsson T, Stadler PF, Vilella AJ, Vogel JH, Williams KP, Wright MW, Zwieb C. RNAcentral: A vision for an international database of RNA sequences. RNA 2011; 17:1941-6. [PMID: 21940779 PMCID: PMC3198587 DOI: 10.1261/rna.2750811] [Citation(s) in RCA: 55] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/07/2023]
Abstract
During the last decade there has been a great increase in the number of noncoding RNA genes identified, including new classes such as microRNAs and piRNAs. There is also a large growth in the amount of experimental characterization of these RNA components. Despite this growth in information, it is still difficult for researchers to access RNA data, because key data resources for noncoding RNAs have not yet been created. The most pressing omission is the lack of a comprehensive RNA sequence database, much like UniProt, which provides a comprehensive set of protein knowledge. In this article we propose the creation of a new open public resource that we term RNAcentral, which will contain a comprehensive collection of RNA sequences and fill an important gap in the provision of biomedical databases. We envision RNA researchers from all over the world joining a federated RNAcentral network, contributing specialized knowledge and databases. RNAcentral would centralize key data that are currently held across a variety of databases, allowing researchers instant access to a single, unified resource. This resource would facilitate the next generation of RNA research and help drive further discoveries, including those that improve food production and human and animal health. We encourage additional RNA database resources and research groups to join this effort. We aim to obtain international network funding to further this endeavor.
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Affiliation(s)
- Alex Bateman
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SA, United Kingdom
- Corresponding author.E-mail .
| | - Shipra Agrawal
- Institute of Bioinformatics and Applied Biotechnology (IBAB), Bangalore 560 100, India
- BioCOS Life Sciences Private Limited, Bangalore 560 100, India
| | - Ewan Birney
- European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, United Kingdom
| | - Elspeth A. Bruford
- European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, United Kingdom
| | - Janusz M. Bujnicki
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Trojdena 4, 02-109 Warsaw, Poland
- Laboratory of Bioinformatics, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Umultowska 89, 61-614 Poznan, Poland
| | - Guy Cochrane
- European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, United Kingdom
| | - James R. Cole
- Microbial Ecology Center, Michigan State University, East Lansing, Michigan 48824-1319, USA
| | - Marcel E. Dinger
- Institute for Molecular Bioscience, The University of Queensland, St Lucia QLD 4072, Australia
| | - Anton J. Enright
- European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, United Kingdom
| | - Paul P. Gardner
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SA, United Kingdom
| | - Daniel Gautheret
- Institut de Génétique et Microbiologie–UMR CNRS 8621, Université Paris-Sud–Bâtiment 400, 91405 Orsay Cedex, France
| | - Sam Griffiths-Jones
- Faculty of Life Sciences, University of Manchester, Michael Smith Building, Manchester, M13 9PT, United Kingdom
| | - Jen Harrow
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SA, United Kingdom
| | - Javier Herrero
- European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, United Kingdom
| | - Ian H. Holmes
- Department of Bioengineering, University of California, Berkeley, California 94720-1762, USA
| | - Hsien-Da Huang
- Institute of Bioinformatics and Systems Biology, National Chiao Tung University, HsinChu, 30050, Taiwan
| | - Krystyna A. Kelly
- Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, United Kingdom
| | - Paul Kersey
- European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, United Kingdom
| | - Ana Kozomara
- Faculty of Life Sciences, University of Manchester, Michael Smith Building, Manchester, M13 9PT, United Kingdom
| | - Todd M. Lowe
- Department of Biomolecular Engineering, University of California, Santa Cruz, California 95064, USA
| | - Manja Marz
- RNA Bioinformatics Group, Institute of Pharmaceutical Chemistry, Marbacher Weg 6, 35037 Marburg, Germany
| | - Simon Moxon
- University of East Anglia, Norwich, NR4 7TJ, United Kingdom
| | - Kim D. Pruitt
- National Center for Biotechnology Information, National Library of Medicine, Bethesda, Maryland 20894, USA
| | - Tore Samuelsson
- Department of Medical Biochemistry, University of Goteborg, Medicinareg. 9A, S-405 30 Goteborg, Sweden
| | - Peter F. Stadler
- Bioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, University of Leipzig, 04009 Leipzig, Germany
| | - Albert J. Vilella
- European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, United Kingdom
| | - Jan-Hinnerk Vogel
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SA, United Kingdom
| | - Kelly P. Williams
- Sandia National Laboratories, MS 9291, Livermore, California 94551-0969, USA
| | - Mathew W. Wright
- European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, United Kingdom
| | - Christian Zwieb
- Department of Biochemistry, University of Texas Health Science Center at San Antonio, San Antonio, Texas 78229-3901, USA
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37
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Chan PP, Cozen AE, Lowe TM. Discovery of permuted and recently split transfer RNAs in Archaea. Genome Biol 2011; 12:R38. [PMID: 21489296 PMCID: PMC3218864 DOI: 10.1186/gb-2011-12-4-r38] [Citation(s) in RCA: 50] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2010] [Revised: 03/30/2011] [Accepted: 04/13/2011] [Indexed: 01/19/2023] Open
Abstract
Background As in eukaryotes, precursor transfer RNAs in Archaea often contain introns that are removed in tRNA maturation. Two unrelated archaeal species display unique pre-tRNA processing complexity in the form of split tRNA genes, in which two to three segments of tRNAs are transcribed from different loci, then trans-spliced to form a mature tRNA. Another rare type of pre-tRNA, found only in eukaryotic algae, is permuted, where the 3' half is encoded upstream of the 5' half, and must be processed to be functional. Results Using an improved version of the gene-finding program tRNAscan-SE, comparative analyses and experimental verifications, we have now identified four novel trans-spliced tRNA genes, each in a different species of the Desulfurococcales branch of the Archaea: tRNAAsp(GUC) in Aeropyrum pernix and Thermosphaera aggregans, and tRNALys(CUU) in Staphylothermus hellenicus and Staphylothermus marinus. Each of these includes features surprisingly similar to previously studied split tRNAs, yet comparative genomic context analysis and phylogenetic distribution suggest several independent, relatively recent splitting events. Additionally, we identified the first examples of permuted tRNA genes in Archaea: tRNAiMet(CAU) and tRNATyr(GUA) in Thermofilum pendens, which appear to be permuted in the same arrangement seen previously in red alga. Conclusions Our findings illustrate that split tRNAs are sporadically spread across a major branch of the Archaea, and that permuted tRNAs are a new shared characteristic between archaeal and eukaryotic species. The split tRNA discoveries also provide new clues to their evolutionary history, supporting hypotheses for recent acquisition via viral or other mobile elements.
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Affiliation(s)
- Patricia P Chan
- Department of Biomolecular Engineering, University of California Santa Cruz, 1156 High Street, Santa Cruz, CA 95064, USA
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38
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Underwood JG, Uzilov AV, Katzman S, Onodera CS, Mainzer JE, Mathews DH, Lowe TM, Salama SR, Haussler D. FragSeq: transcriptome-wide RNA structure probing using high-throughput sequencing. Nat Methods 2010; 7:995-1001. [PMID: 21057495 PMCID: PMC3247016 DOI: 10.1038/nmeth.1529] [Citation(s) in RCA: 239] [Impact Index Per Article: 17.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2010] [Accepted: 10/13/2010] [Indexed: 01/07/2023]
Abstract
Previous efforts to determine structures of non-coding RNA (ncRNA) probed only one RNA at a time with enzymes and chemicals, using gel electrophoresis to identify reactive positions. To accelerate RNA structure inference, we have developed FragSeq, a high-throughput RNA structure probing method that uses high-throughput RNA sequencing on fragments generated by nuclease P1, which specifically cleaves single stranded nucleic acids. In experiments probing the entire mouse nuclear transcriptome, we show that we can accurately and simultaneously map single-stranded regions (ssRNA) in multiple ncRNAs with known structure. We carried out probing in two cell types to demonstrate reproducibility. We also identified and experimentally validated structured regions in ncRNAs never previously probed.
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Affiliation(s)
- Jason G Underwood
- Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, California, USA
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39
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Hartman AL, Norais C, Badger JH, Delmas S, Haldenby S, Madupu R, Robinson J, Khouri H, Ren Q, Lowe TM, Maupin-Furlow J, Pohlschroder M, Daniels C, Pfeiffer F, Allers T, Eisen JA. The complete genome sequence of Haloferax volcanii DS2, a model archaeon. PLoS One 2010; 5:e9605. [PMID: 20333302 PMCID: PMC2841640 DOI: 10.1371/journal.pone.0009605] [Citation(s) in RCA: 195] [Impact Index Per Article: 13.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2009] [Accepted: 02/11/2010] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND Haloferax volcanii is an easily culturable moderate halophile that grows on simple defined media, is readily transformable, and has a relatively stable genome. This, in combination with its biochemical and genetic tractability, has made Hfx. volcanii a key model organism, not only for the study of halophilicity, but also for archaeal biology in general. METHODOLOGY/PRINCIPAL FINDINGS We report here the sequencing and analysis of the genome of Hfx. volcanii DS2, the type strain of this species. The genome contains a main 2.848 Mb chromosome, three smaller chromosomes pHV1, 3, 4 (85, 438, 636 kb, respectively) and the pHV2 plasmid (6.4 kb). CONCLUSIONS/SIGNIFICANCE The completed genome sequence, presented here, provides an invaluable tool for further in vivo and in vitro studies of Hfx. volcanii.
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Affiliation(s)
- Amber L. Hartman
- Department of Biology, Johns Hopkins University, Baltimore, Maryland, United States of America
- The Institute for Genomic Research (J. Craig Venter Institute), Rockville, Maryland, United States of America
- UC Davis Genome Center, University of California Davis, Davis, California, United States of America
| | - Cédric Norais
- Institut de Génétique et Microbiologie, Université Paris-Sud, Paris, France
- Department of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Jonathan H. Badger
- The Institute for Genomic Research (J. Craig Venter Institute), Rockville, Maryland, United States of America
| | - Stéphane Delmas
- Institute of Genetics, University of Nottingham, Nottingham, United Kingdom
| | - Sam Haldenby
- Institute of Genetics, University of Nottingham, Nottingham, United Kingdom
| | - Ramana Madupu
- The Institute for Genomic Research (J. Craig Venter Institute), Rockville, Maryland, United States of America
| | - Jeffrey Robinson
- The Institute for Genomic Research (J. Craig Venter Institute), Rockville, Maryland, United States of America
| | - Hoda Khouri
- The Institute for Genomic Research (J. Craig Venter Institute), Rockville, Maryland, United States of America
| | - Qinghu Ren
- The Institute for Genomic Research (J. Craig Venter Institute), Rockville, Maryland, United States of America
| | - Todd M. Lowe
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, California, United States of America
| | - Julie Maupin-Furlow
- Department of Microbiology and Cell Science, University of Florida, Gainesville, Florida, United States of America
| | - Mecky Pohlschroder
- Department of Biology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Charles Daniels
- Department of Microbiology, Ohio State University, Columbus, Ohio, United States of America
| | - Friedhelm Pfeiffer
- Department of Membrane Biochemistry, Max-Planck-Institute of Biochemistry, Martinsried, Germany
| | - Thorsten Allers
- Institute of Genetics, University of Nottingham, Nottingham, United Kingdom
| | - Jonathan A. Eisen
- The Institute for Genomic Research (J. Craig Venter Institute), Rockville, Maryland, United States of America
- UC Davis Genome Center, University of California Davis, Davis, California, United States of America
- Department of Medical Microbiology and Immunology, University of California Davis, Davis, California, United States of America
- Department of Evolution and Ecology, University of California Davis, Davis, California, United States of America
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40
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Abstract
Transfer RNAs (tRNAs) represent the single largest, best-understood class of non-protein coding RNA genes found in all living organisms. By far, the major source of new tRNAs is computational identification of genes within newly sequenced genomes. To organize the rapidly growing collection and enable systematic analyses, we created the Genomic tRNA Database (GtRNAdb), currently including over 74 000 tRNA genes predicted from 740 species. The web resource provides overview statistics of tRNA genes within each analyzed genome, including information by isotype and genetic locus, easily downloadable primary sequences, graphical secondary structures and multiple sequence alignments. Direct links for each gene to UCSC eukaryotic and microbial genome browsers provide graphical display of tRNA genes in the context of all other local genetic information. The database can be searched by primary sequence similarity, tRNA characteristics or phylogenetic group. The database is publicly available at http://gtrnadb.ucsc.edu.
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Affiliation(s)
- Patricia P Chan
- Department of Biomolecular Engineering, University of California, Santa Cruz, 1156 High Street, SOE-2, Santa Cruz, CA 95064, USA
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41
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Birney E, Stamatoyannopoulos JA, Dutta A, Guigó R, Gingeras TR, Margulies EH, Weng Z, Snyder M, Dermitzakis ET, Thurman RE, Kuehn MS, Taylor CM, Neph S, Koch CM, Asthana S, Malhotra A, Adzhubei I, Greenbaum JA, Andrews RM, Flicek P, Boyle PJ, Cao H, Carter NP, Clelland GK, Davis S, Day N, Dhami P, Dillon SC, Dorschner MO, Fiegler H, Giresi PG, Goldy J, Hawrylycz M, Haydock A, Humbert R, James KD, Johnson BE, Johnson EM, Frum TT, Rosenzweig ER, Karnani N, Lee K, Lefebvre GC, Navas PA, Neri F, Parker SCJ, Sabo PJ, Sandstrom R, Shafer A, Vetrie D, Weaver M, Wilcox S, Yu M, Collins FS, Dekker J, Lieb JD, Tullius TD, Crawford GE, Sunyaev S, Noble WS, Dunham I, Denoeud F, Reymond A, Kapranov P, Rozowsky J, Zheng D, Castelo R, Frankish A, Harrow J, Ghosh S, Sandelin A, Hofacker IL, Baertsch R, Keefe D, Dike S, Cheng J, Hirsch HA, Sekinger EA, Lagarde J, Abril JF, Shahab A, Flamm C, Fried C, Hackermüller J, Hertel J, Lindemeyer M, Missal K, Tanzer A, Washietl S, Korbel J, Emanuelsson O, Pedersen JS, Holroyd N, Taylor R, Swarbreck D, Matthews N, Dickson MC, Thomas DJ, Weirauch MT, Gilbert J, Drenkow J, Bell I, Zhao X, Srinivasan KG, Sung WK, Ooi HS, Chiu KP, Foissac S, Alioto T, Brent M, Pachter L, Tress ML, Valencia A, Choo SW, Choo CY, Ucla C, Manzano C, Wyss C, Cheung E, Clark TG, Brown JB, Ganesh M, Patel S, Tammana H, Chrast J, Henrichsen CN, Kai C, Kawai J, Nagalakshmi U, Wu J, Lian Z, Lian J, Newburger P, Zhang X, Bickel P, Mattick JS, Carninci P, Hayashizaki Y, Weissman S, Hubbard T, Myers RM, Rogers J, Stadler PF, Lowe TM, Wei CL, Ruan Y, Struhl K, Gerstein M, Antonarakis SE, Fu Y, Green ED, Karaöz U, Siepel A, Taylor J, Liefer LA, Wetterstrand KA, Good PJ, Feingold EA, Guyer MS, Cooper GM, Asimenos G, Dewey CN, Hou M, Nikolaev S, Montoya-Burgos JI, Löytynoja A, Whelan S, Pardi F, Massingham T, Huang H, Zhang NR, Holmes I, Mullikin JC, Ureta-Vidal A, Paten B, Seringhaus M, Church D, Rosenbloom K, Kent WJ, Stone EA, Batzoglou S, Goldman N, Hardison RC, Haussler D, Miller W, Sidow A, Trinklein ND, Zhang ZD, Barrera L, Stuart R, King DC, Ameur A, Enroth S, Bieda MC, Kim J, Bhinge AA, Jiang N, Liu J, Yao F, Vega VB, Lee CWH, Ng P, Shahab A, Yang A, Moqtaderi Z, Zhu Z, Xu X, Squazzo S, Oberley MJ, Inman D, Singer MA, Richmond TA, Munn KJ, Rada-Iglesias A, Wallerman O, Komorowski J, Fowler JC, Couttet P, Bruce AW, Dovey OM, Ellis PD, Langford CF, Nix DA, Euskirchen G, Hartman S, Urban AE, Kraus P, Van Calcar S, Heintzman N, Kim TH, Wang K, Qu C, Hon G, Luna R, Glass CK, Rosenfeld MG, Aldred SF, Cooper SJ, Halees A, Lin JM, Shulha HP, Zhang X, Xu M, Haidar JNS, Yu Y, Ruan Y, Iyer VR, Green RD, Wadelius C, Farnham PJ, Ren B, Harte RA, Hinrichs AS, Trumbower H, Clawson H, Hillman-Jackson J, Zweig AS, Smith K, Thakkapallayil A, Barber G, Kuhn RM, Karolchik D, Armengol L, Bird CP, de Bakker PIW, Kern AD, Lopez-Bigas N, Martin JD, Stranger BE, Woodroffe A, Davydov E, Dimas A, Eyras E, Hallgrímsdóttir IB, Huppert J, Zody MC, Abecasis GR, Estivill X, Bouffard GG, Guan X, Hansen NF, Idol JR, Maduro VVB, Maskeri B, McDowell JC, Park M, Thomas PJ, Young AC, Blakesley RW, Muzny DM, Sodergren E, Wheeler DA, Worley KC, Jiang H, Weinstock GM, Gibbs RA, Graves T, Fulton R, Mardis ER, Wilson RK, Clamp M, Cuff J, Gnerre S, Jaffe DB, Chang JL, Lindblad-Toh K, Lander ES, Koriabine M, Nefedov M, Osoegawa K, Yoshinaga Y, Zhu B, de Jong PJ. Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project. Nature 2007; 447:799-816. [PMID: 17571346 PMCID: PMC2212820 DOI: 10.1038/nature05874] [Citation(s) in RCA: 3782] [Impact Index Per Article: 222.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
We report the generation and analysis of functional data from multiple, diverse experiments performed on a targeted 1% of the human genome as part of the pilot phase of the ENCODE Project. These data have been further integrated and augmented by a number of evolutionary and computational analyses. Together, our results advance the collective knowledge about human genome function in several major areas. First, our studies provide convincing evidence that the genome is pervasively transcribed, such that the majority of its bases can be found in primary transcripts, including non-protein-coding transcripts, and those that extensively overlap one another. Second, systematic examination of transcriptional regulation has yielded new understanding about transcription start sites, including their relationship to specific regulatory sequences and features of chromatin accessibility and histone modification. Third, a more sophisticated view of chromatin structure has emerged, including its inter-relationship with DNA replication and transcriptional regulation. Finally, integration of these new sources of information, in particular with respect to mammalian evolution based on inter- and intra-species sequence comparisons, has yielded new mechanistic and evolutionary insights concerning the functional landscape of the human genome. Together, these studies are defining a path for pursuit of a more comprehensive characterization of human genome function.
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Williams E, Lowe TM, Savas J, DiRuggiero J. Microarray analysis of the hyperthermophilic archaeon Pyrococcus furiosus exposed to gamma irradiation. Extremophiles 2006; 11:19-29. [PMID: 16896524 DOI: 10.1007/s00792-006-0002-9] [Citation(s) in RCA: 62] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2006] [Accepted: 05/16/2006] [Indexed: 12/15/2022]
Abstract
The remarkable survival of the hyperthermophilic archaeon Pyrococcus furiosus to ionizing radiation was previously demonstrated. Using a time course study and whole-genome microarray analyses of mRNA transcript levels, the genes and regulatory pathways involved in the repair of lesions produced by ionizing irradiation (oxidative damage and DNA strand breaks) in P. furiosus were investigated. Data analyses showed that radA, encoding the archaeal homolog of the RecA/Rad51 recombinase, was moderately up regulated by irradiation and that a putative DNA-repair gene cluster was specifically induced by exposure to ionizing radiation. This novel repair system appears to be unique to thermophilic archaea and bacteria and is suspected to be involved in translesion synthesis. Genes that encode for a putative Dps-like iron-chelating protein and two membrane-bound oxidoreductases were differentially expressed following gamma irradiation, potentially in response to oxidative stress. Surprisingly, the many systems involved in oxygen detoxification and redox homeostasis appeared to be constitutively expressed. Finally, we identified several transcriptional regulators and protein kinases highly regulated in response to gamma irradiation.
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Affiliation(s)
- Ernest Williams
- Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, MD 20742, USA
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43
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Abstract
As more archaeal genomes are sequenced, effective research and analysis tools are needed to integrate the diverse information available for any given locus. The feature-rich UCSC Genome Browser, created originally to annotate the human genome, can be applied to any sequenced organism. We have created a UCSC Archaeal Genome Browser, available at , currently with 26 archaeal genomes. It displays G/C content, gene and operon annotation from multiple sources, sequence motifs (promoters and Shine-Dalgarno), microarray data, multi-genome alignments and protein conservation across phylogenetic and habitat categories. We encourage submission of new experimental and bioinformatic analysis from contributors. The purpose of this tool is to aid biological discovery and facilitate greater collaboration within the archaeal research community.
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Affiliation(s)
| | | | | | | | - Todd M. Lowe
- To whom correspondence should be addressed. Tel: +1 831 459 1511; Fax: +1 831 459 4829;
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44
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Abstract
The box H/ACA RNA gene family is one of the largest non-protein-coding gene families in eukaryotes and archaea. Recently, we developed snoGPS, a computational screening program for H/ACA snoRNAs, and applied it to Saccharomyces cerevisiae. We report here results of extending our method to screen for H/ACA RNAs in multiple large genomes of related species, and apply it to the human, mouse, and rat genomes. Because of the 250-fold larger search space compared to S. cerevisiae, significant enhancements to our algorithms were required. Complementing extensive cloning experiments performed by others, our findings include the detection and experimental verification of seven new mammalian H/ACA RNAs and the prediction of 23 new H/ACA RNA pseudouridine guide assignments. These assignments include four for H/ACA RNAs previously classified as orphan H/ACA RNAs with no known targets. We also determined systematic syntenic conservation among human and mouse H/ACA RNAs. With this work, 82 of 97 ribosomal RNA pseudouridines and 18 of 32 spliceosomal RNA pseudouridines in mammals have been linked to H/ACA guide RNAs.
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Affiliation(s)
- Peter Schattner
- Department of Biomolecular Engineering, UCSC RNA Center, University of California-Santa Cruz, 1156 High St., Santa Cruz, Santa Cruz, CA 95064, USA.
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45
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Abstract
Transfer RNAs (tRNAs) and small nucleolar RNAs (snoRNAs) are two of the largest classes of non-protein-coding RNAs. Conventional gene finders that detect protein-coding genes do not find tRNA and snoRNA genes because they lack the codon structure and statistical signatures of protein-coding genes. Previously, we developed tRNAscan-SE, snoscan and snoGPS for the detection of tRNAs, methylation-guide snoRNAs and pseudouridylation-guide snoRNAs, respectively. tRNAscan-SE is routinely applied to completed genomes, resulting in the identification of thousands of tRNA genes. Snoscan has successfully detected methylation-guide snoRNAs in a variety of eukaryotes and archaea, and snoGPS has identified novel pseudouridylation-guide snoRNAs in yeast and mammals. Although these programs have been quite successful at RNA gene detection, their use has been limited by the need to install and configure the software packages on UNIX workstations. Here, we describe online implementations of these RNA detection tools that make these programs accessible to a wider range of research biologists. The tRNAscan-SE, snoscan and snoGPS servers are available at http://lowelab.ucsc.edu/tRNAscan-SE/, http://lowelab.ucsc.edu/snoscan/ and http://lowelab.ucsc.edu/snoGPS/, respectively.
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Affiliation(s)
- Peter Schattner
- Department of Biomolecular Engineering and the UCSC RNA Center, University of California Santa Cruz, 1156 High Street, Santa Cruz, CA 95064, USA.
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46
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Schattner P, Decatur WA, Davis CA, Ares M, Fournier MJ, Lowe TM. Genome-wide searching for pseudouridylation guide snoRNAs: analysis of the Saccharomyces cerevisiae genome. Nucleic Acids Res 2004; 32:4281-96. [PMID: 15306656 PMCID: PMC514388 DOI: 10.1093/nar/gkh768] [Citation(s) in RCA: 131] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2004] [Revised: 07/15/2004] [Accepted: 07/26/2004] [Indexed: 12/21/2022] Open
Abstract
One of the largest families of small RNAs in eukaryotes is the H/ACA small nucleolar RNAs (snoRNAs), most of which guide RNA pseudouridine formation. So far, an effective computational method specifically for identifying H/ACA snoRNA gene sequences has not been established. We have developed snoGPS, a program for computationally screening genomic sequences for H/ACA guide snoRNAs. The program implements a deterministic screening algorithm combined with a probabilistic model to score gene candidates. We report here the results of testing snoGPS on the budding yeast Saccharomyces cerevisiae. Six candidate snoRNAs were verified as novel RNA transcripts, and five of these were verified as guides for pseudouridine formation at specific sites in ribosomal RNA. We also predicted 14 new base-pairings between snoRNAs and known pseudouridine sites in S.cerevisiae rRNA, 12 of which were verified by gene disruption and loss of the cognate pseudouridine site. Our findings include the first prediction and verification of snoRNAs that guide pseudouridine modification at more than two sites. With this work, 41 of the 44 known pseudouridine modifications in S.cerevisiae rRNA have been linked with a verified snoRNA, providing the most complete accounting of the H/ACA snoRNAs that guide pseudouridylation in any species.
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MESH Headings
- Algorithms
- Base Sequence
- Computational Biology/methods
- Genome, Fungal
- Genomics/methods
- Molecular Sequence Data
- Phylogeny
- Pseudouridine/chemistry
- Pseudouridine/metabolism
- RNA, Fungal/chemistry
- RNA, Fungal/genetics
- RNA, Fungal/metabolism
- RNA, Ribosomal/chemistry
- RNA, Ribosomal/metabolism
- RNA, Small Nucleolar/chemistry
- RNA, Small Nucleolar/genetics
- RNA, Small Nucleolar/physiology
- Saccharomyces cerevisiae/genetics
- Saccharomyces cerevisiae/metabolism
- Software
- RNA, Small Untranslated
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Affiliation(s)
- Peter Schattner
- Department of Biomolecular Engineering, University of California, Santa Cruz, 1156 High Street, Santa Cruz, CA 95064, USA
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47
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Brown JWS, Echeverria M, Qu LH, Lowe TM, Bachellerie JP, Hüttenhofer A, Kastenmayer JP, Green PJ, Shaw P, Marshall DF. Plant snoRNA database. Nucleic Acids Res 2003; 31:432-5. [PMID: 12520043 PMCID: PMC165456 DOI: 10.1093/nar/gkg009] [Citation(s) in RCA: 77] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The Plant snoRNA database (http://www.scri.sari.ac.uk/plant_snoRNA/) provides information on small nucleolar RNAs from Arabidopsis and eighteen other plant species. Information includes sequences, expression data, methylation and pseudouridylation target modification sites, initial gene organization (polycistronic, single gene and intronic) and the number of gene variants. The Arabidopsis information is divided into box C/D and box H/ACA snoRNAs, and within each of these groups, by target sites in rRNA, snRNA or unknown. Alignments of orthologous genes and gene variants from different plant species are available for many snoRNA genes. Plant snoRNA genes have been given a standard nomenclature, designed wherever possible, to provide a consistent identity with yeast and human orthologues.
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Affiliation(s)
- John W S Brown
- Gene Expression Programme, Scottish Crop Research Institute, Invergowrie, Dundee DD2 5DA, UK.
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48
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Abstract
In eukaryotes, many Box C/D small nucleolar RNAs base pair with ribosomal RNA through short complementary guide sequences, thereby marking up to 100 individual nucleotides of ribosomal RNA for 2'-O-methylation. Function of the eukaryotic Box C/D RNAs depends upon interaction with at least six known proteins. Box C/D RNAs are not known to exist in Bacteria but were recently identified in Archaea by biochemical analysis and computational genomic screens and have likely evolved independently in Archaea and Eukarya for more than 2000 million years. We have microinjected Box C/D RNAs from Pyrococcus furiosus, a hyperthermophilic archaeon, into the nuclei of oocytes from the aquatic frog Xenopus laevis. Our results show that Box C/D RNAs derived from this prokaryote are retained in the nucleus, localize to nucleoli, and interact with the X. laevis Box C/D RNA binding proteins fibrillarin, Nop56, and Nop58. Furthermore, we have demonstrated the ability of archaeal Box C/D RNAs to direct site-specific 2'-O-methylation of ribosomal RNA. Our studies have revealed the remarkable ability of archaeal Box C/D RNAs to assemble into functional RNA-protein complexes in the eukaryotic nucleus.
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Affiliation(s)
- Wayne A Speckmann
- Department of Biochemistry and Molecular Biology, University of Georgia, Athens, GA 30602, USA
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49
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Abstract
In addition to directing transcription initiation, core promoters integrate input from distal regulatory elements. Except for rare exceptions, it has been generally found that eukaryotic tRNA and rRNA genes do not contain TATA promoter elements and instead use protein-protein interactions to bring the TATA-binding protein (TBP), to the core promoter. Genomewide analysis revealed TATA elements in the core promoters of tRNA and 5S rRNA (Pol III), U1 to U5 snRNA (Pol II), and 37S rRNA (Pol I) genes in Schizosaccharomyces pombe. Using tRNA-dependent suppression and other in vivo assays, as well as in vitro transcription, we demonstrated an obligatory requirement for upstream TATA elements for tRNA and 5S rRNA expression in S. pombe. The Pol III initiation factor Brf is found in complexes with TFIIIC and Pol III in S. pombe, while TBP is not, consistent with independent recruitment of TBP by TATA. Template commitment assays are consistent with this and confirm that the mechanisms of transcription complex assembly and initiation by Pol III in S. pombe differ substantially from those in other model organisms. The results were extended to large-rRNA synthesis, as mutation of the TATA element in the Pol I promoter also abolishes rRNA expression in fission yeast. A survey of other organisms' genomes reveals that a substantial number of eukaryotes may use widespread TATAs for transcription. These results indicate the presence of TATA-unified transcription systems in contemporary eukaryotes and provide insight into the residual need for TBP by all three Pols in other eukaryotes despite a lack of TATA elements in their promoters.
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MESH Headings
- Amino Acid Motifs
- Amino Acid Sequence
- Base Sequence
- Conserved Sequence
- DNA-Binding Proteins/genetics
- DNA-Binding Proteins/metabolism
- Evolution, Molecular
- Genome, Fungal
- Immunoblotting
- Molecular Sequence Data
- Promoter Regions, Genetic
- RNA Polymerase I/genetics
- RNA Polymerase I/metabolism
- RNA Polymerase II/genetics
- RNA Polymerase II/metabolism
- RNA Polymerase III/genetics
- RNA Polymerase III/metabolism
- RNA, Ribosomal/metabolism
- RNA, Ribosomal, 5S/genetics
- RNA, Transfer/metabolism
- Schizosaccharomyces/metabolism
- Sequence Homology, Amino Acid
- Sequence Homology, Nucleic Acid
- TATA-Box Binding Protein
- Transcription Factors/genetics
- Transcription Factors/metabolism
- Transcription, Genetic
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Affiliation(s)
- M Hamada
- Laboratory of Molecular Growth Regulation, National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland 20892-2753, USA
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50
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Lander ES, Linton LM, Birren B, Nusbaum C, Zody MC, Baldwin J, Devon K, Dewar K, Doyle M, FitzHugh W, Funke R, Gage D, Harris K, Heaford A, Howland J, Kann L, Lehoczky J, LeVine R, McEwan P, McKernan K, Meldrim J, Mesirov JP, Miranda C, Morris W, Naylor J, Raymond C, Rosetti M, Santos R, Sheridan A, Sougnez C, Stange-Thomann Y, Stojanovic N, Subramanian A, Wyman D, Rogers J, Sulston J, Ainscough R, Beck S, Bentley D, Burton J, Clee C, Carter N, Coulson A, Deadman R, Deloukas P, Dunham A, Dunham I, Durbin R, French L, Grafham D, Gregory S, Hubbard T, Humphray S, Hunt A, Jones M, Lloyd C, McMurray A, Matthews L, Mercer S, Milne S, Mullikin JC, Mungall A, Plumb R, Ross M, Shownkeen R, Sims S, Waterston RH, Wilson RK, Hillier LW, McPherson JD, Marra MA, Mardis ER, Fulton LA, Chinwalla AT, Pepin KH, Gish WR, Chissoe SL, Wendl MC, Delehaunty KD, Miner TL, Delehaunty A, Kramer JB, Cook LL, Fulton RS, Johnson DL, Minx PJ, Clifton SW, Hawkins T, Branscomb E, Predki P, Richardson P, Wenning S, Slezak T, Doggett N, Cheng JF, Olsen A, Lucas S, Elkin C, Uberbacher E, Frazier M, Gibbs RA, Muzny DM, Scherer SE, Bouck JB, Sodergren EJ, Worley KC, Rives CM, Gorrell JH, Metzker ML, Naylor SL, Kucherlapati RS, Nelson DL, Weinstock GM, Sakaki Y, Fujiyama A, Hattori M, Yada T, Toyoda A, Itoh T, Kawagoe C, Watanabe H, Totoki Y, Taylor T, Weissenbach J, Heilig R, Saurin W, Artiguenave F, Brottier P, Bruls T, Pelletier E, Robert C, Wincker P, Smith DR, Doucette-Stamm L, Rubenfield M, Weinstock K, Lee HM, Dubois J, Rosenthal A, Platzer M, Nyakatura G, Taudien S, Rump A, Yang H, Yu J, Wang J, Huang G, Gu J, Hood L, Rowen L, Madan A, Qin S, Davis RW, Federspiel NA, Abola AP, Proctor MJ, Myers RM, Schmutz J, Dickson M, Grimwood J, Cox DR, Olson MV, Kaul R, Raymond C, Shimizu N, Kawasaki K, Minoshima S, Evans GA, Athanasiou M, Schultz R, Roe BA, Chen F, Pan H, Ramser J, Lehrach H, Reinhardt R, McCombie WR, de la Bastide M, Dedhia N, Blöcker H, Hornischer K, Nordsiek G, Agarwala R, Aravind L, Bailey JA, Bateman A, Batzoglou S, Birney E, Bork P, Brown DG, Burge CB, Cerutti L, Chen HC, Church D, Clamp M, Copley RR, Doerks T, Eddy SR, Eichler EE, Furey TS, Galagan J, Gilbert JG, Harmon C, Hayashizaki Y, Haussler D, Hermjakob H, Hokamp K, Jang W, Johnson LS, Jones TA, Kasif S, Kaspryzk A, Kennedy S, Kent WJ, Kitts P, Koonin EV, Korf I, Kulp D, Lancet D, Lowe TM, McLysaght A, Mikkelsen T, Moran JV, Mulder N, Pollara VJ, Ponting CP, Schuler G, Schultz J, Slater G, Smit AF, Stupka E, Szustakowki J, Thierry-Mieg D, Thierry-Mieg J, Wagner L, Wallis J, Wheeler R, Williams A, Wolf YI, Wolfe KH, Yang SP, Yeh RF, Collins F, Guyer MS, Peterson J, Felsenfeld A, Wetterstrand KA, Patrinos A, Morgan MJ, de Jong P, Catanese JJ, Osoegawa K, Shizuya H, Choi S, Chen YJ, Szustakowki J. Initial sequencing and analysis of the human genome. Nature 2001; 409:860-921. [PMID: 11237011 DOI: 10.1038/35057062] [Citation(s) in RCA: 14499] [Impact Index Per Article: 630.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
The human genome holds an extraordinary trove of information about human development, physiology, medicine and evolution. Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome. We also present an initial analysis of the data, describing some of the insights that can be gleaned from the sequence.
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Affiliation(s)
- E S Lander
- Whitehead Institute for Biomedical Research, Center for Genome Research, Cambridge, MA 02142, USA.
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