101
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Marbaniang CN, Vogel J. Emerging roles of RNA modifications in bacteria. Curr Opin Microbiol 2016; 30:50-57. [PMID: 26803287 DOI: 10.1016/j.mib.2016.01.001] [Citation(s) in RCA: 52] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2015] [Revised: 12/24/2015] [Accepted: 01/06/2016] [Indexed: 01/28/2023]
Abstract
RNA modifications are known to abound in stable tRNA and rRNA, where they cluster around functionally important regions. However, RNA-seq based techniques profiling entire transcriptomes are now uncovering an abundance of modified ribonucleotides in mRNAs and noncoding RNAs, too. While most of the recent progress in understanding the regulatory influence of these new RNA modifications stems from eukaryotes, there is growing evidence in bacteria for modified nucleotides beyond the stable RNA species, including modifications of small regulatory RNAs. Given their small genome size, good genetic tractability, and ample knowledge of modification enzymes, bacteria offer excellent model systems to decipher cellular functions of RNA modifications in many diverse physiological contexts. This review highlights how new global approaches combining classic analysis with new sequencing techniques may usher in an era of bacterial epitranscriptomics.
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Affiliation(s)
- Carmelita Nora Marbaniang
- RNA Biology Group, Institute for Molecular Infection Biology, University of Würzburg, Josef-Schneider-Straße 2, D-97080 Würzburg, Germany
| | - Jörg Vogel
- RNA Biology Group, Institute for Molecular Infection Biology, University of Würzburg, Josef-Schneider-Straße 2, D-97080 Würzburg, Germany.
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102
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Silverman IM, Berkowitz ND, Gosai SJ, Gregory BD. Genome-Wide Approaches for RNA Structure Probing. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2016; 907:29-59. [PMID: 27256381 DOI: 10.1007/978-3-319-29073-7_2] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
RNA molecules of all types fold into complex secondary and tertiary structures that are important for their function and regulation. Structural and catalytic RNAs such as ribosomal RNA (rRNA) and transfer RNA (tRNA) are central players in protein synthesis, and only function through their proper folding into intricate three-dimensional structures. Studies of messenger RNA (mRNA) regulation have also revealed that structural elements embedded within these RNA species are important for the proper regulation of their total level in the transcriptome. More recently, the discovery of microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) has shed light on the importance of RNA structure to genome, transcriptome, and proteome regulation. Due to the relatively small number, high conservation, and importance of structural and catalytic RNAs to all life, much early work in RNA structure analysis mapped out a detailed view of these molecules. Computational and physical methods were used in concert with enzymatic and chemical structure probing to create high-resolution models of these fundamental biological molecules. However, the recent expansion in our knowledge of the importance of RNA structure to coding and regulatory RNAs has left the field in need of faster and scalable methods for high-throughput structural analysis. To address this, nuclease and chemical RNA structure probing methodologies have been adapted for genome-wide analysis. These methods have been deployed to globally characterize thousands of RNA structures in a single experiment. Here, we review these experimental methodologies for high-throughput RNA structure determination and discuss the insights gained from each approach.
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Affiliation(s)
- Ian M Silverman
- Department of Biology, University of Pennsylvania, Philadelphia, PA, 19104, USA.,Cell and Molecular Biology Graduate Group, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Nathan D Berkowitz
- Department of Biology, University of Pennsylvania, Philadelphia, PA, 19104, USA.,Genomics and Computational Biology Graduate Group, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Sager J Gosai
- Department of Biology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Brian D Gregory
- Department of Biology, University of Pennsylvania, Philadelphia, PA, 19104, USA. .,Cell and Molecular Biology Graduate Group, University of Pennsylvania, Philadelphia, PA, 19104, USA. .,Genomics and Computational Biology Graduate Group, University of Pennsylvania, Philadelphia, PA, 19104, USA.
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103
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RNA Polymerase III Output Is Functionally Linked to tRNA Dimethyl-G26 Modification. PLoS Genet 2015; 11:e1005671. [PMID: 26720005 PMCID: PMC4697793 DOI: 10.1371/journal.pgen.1005671] [Citation(s) in RCA: 70] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2015] [Accepted: 10/26/2015] [Indexed: 11/19/2022] Open
Abstract
Control of the differential abundance or activity of tRNAs can be important determinants of gene regulation. RNA polymerase (RNAP) III synthesizes all tRNAs in eukaryotes and it derepression is associated with cancer. Maf1 is a conserved general repressor of RNAP III under the control of the target of rapamycin (TOR) that acts to integrate transcriptional output and protein synthetic demand toward metabolic economy. Studies in budding yeast have indicated that the global tRNA gene activation that occurs with derepression of RNAP III via maf1-deletion is accompanied by a paradoxical loss of tRNA-mediated nonsense suppressor activity, manifested as an antisuppression phenotype, by an unknown mechanism. We show that maf1-antisuppression also occurs in the fission yeast S. pombe amidst general activation of RNAP III. We used tRNA-HydroSeq to document that little changes occurred in the relative levels of different tRNAs in maf1Δ cells. By contrast, the efficiency of N2,N2-dimethyl G26 (m(2)2G26) modification on certain tRNAs was decreased in response to maf1-deletion and associated with antisuppression, and was validated by other methods. Over-expression of Trm1, which produces m(2)2G26, reversed maf1-antisuppression. A model that emerges is that competition by increased tRNA levels in maf1Δ cells leads to m(2)2G26 hypomodification due to limiting Trm1, reducing the activity of suppressor-tRNASerUCA and accounting for antisuppression. Consistent with this, we show that RNAP III mutations associated with hypomyelinating leukodystrophy decrease tRNA transcription, increase m(2)2G26 efficiency and reverse antisuppression. Extending this more broadly, we show that a decrease in tRNA synthesis by treatment with rapamycin leads to increased m(2)2G26 modification and that this response is conserved among highly divergent yeasts and human cells.
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104
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Abstract
Our knowledge of the variety and abundances of RNA base modifications is rapidly increasing. Modified bases have critical roles in tRNAs, rRNAs, translation, splicing, RNA interference, and other RNA processes, and are now increasingly detected in all types of transcripts. Can new biological principles associated with this diversity of RNA modifications, particularly in mRNAs and long non-coding RNAs, be identified? This review will explore this question by focusing primarily on adenosine to inosine (A-to-I) RNA editing by the adenine deaminase acting on RNA (ADAR) enzymes that have been intensively studied for the past 20 years and have a wide range of effects. Over 100 million adenosine to inosine editing sites have been identified in the human transcriptome, mostly in embedded Alu sequences that form potentially innate immune-stimulating dsRNA hairpins in transcripts. Recent research has demonstrated that inosine in the epitranscriptome and ADAR1 protein establish innate immune tolerance for host dsRNA formed by endogenous sequences. Innate immune sensors that detect viral nucleic acids are among the readers of epitranscriptome RNA modifications, though this does preclude a wide range of other modification effects.
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Affiliation(s)
- Mary A. O’Connell
- CEITEC Masaryk University, Brno, Czech Republic
- * E-mail: (MAO); (LPK)
| | - Niamh M. Mannion
- Paul O’Gorman Leukaemia Research Centre, Institute of Cancer Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom
| | - Liam P. Keegan
- CEITEC Masaryk University, Brno, Czech Republic
- * E-mail: (MAO); (LPK)
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105
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Leung YY, Kuksa PP, Amlie-Wolf A, Valladares O, Ungar LH, Kannan S, Gregory BD, Wang LS. DASHR: database of small human noncoding RNAs. Nucleic Acids Res 2015; 44:D216-22. [PMID: 26553799 PMCID: PMC4702848 DOI: 10.1093/nar/gkv1188] [Citation(s) in RCA: 59] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2015] [Accepted: 10/25/2015] [Indexed: 11/20/2022] Open
Abstract
Small non-coding RNAs (sncRNAs) are highly abundant RNAs, typically <100 nucleotides long, that act as key regulators of diverse cellular processes. Although thousands of sncRNA genes are known to exist in the human genome, no single database provides searchable, unified annotation, and expression information for full sncRNA transcripts and mature RNA products derived from these larger RNAs. Here, we present the Database of small human noncoding RNAs (DASHR). DASHR contains the most comprehensive information to date on human sncRNA genes and mature sncRNA products. DASHR provides a simple user interface for researchers to view sequence and secondary structure, compare expression levels, and evidence of specific processing across all sncRNA genes and mature sncRNA products in various human tissues. DASHR annotation and expression data covers all major classes of sncRNAs including microRNAs (miRNAs), Piwi-interacting (piRNAs), small nuclear, nucleolar, cytoplasmic (sn-, sno-, scRNAs, respectively), transfer (tRNAs), and ribosomal RNAs (rRNAs). Currently, DASHR (v1.0) integrates 187 smRNA high-throughput sequencing (smRNA-seq) datasets with over 2.5 billion reads and annotation data from multiple public sources. DASHR contains annotations for ∼48 000 human sncRNA genes and mature sncRNA products, 82% of which are expressed in one or more of the curated tissues. DASHR is available at http://lisanwanglab.org/DASHR.
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Affiliation(s)
- Yuk Yee Leung
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA Penn Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Pavel P Kuksa
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA Penn Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Alexandre Amlie-Wolf
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA Genomics and Computational Biology Graduate Group, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Otto Valladares
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Lyle H Ungar
- Penn Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA Genomics and Computational Biology Graduate Group, University of Pennsylvania, Philadelphia, PA 19104, USA Department of Computer and Information Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sampath Kannan
- Penn Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA Department of Computer and Information Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Brian D Gregory
- Genomics and Computational Biology Graduate Group, University of Pennsylvania, Philadelphia, PA 19104, USA Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Li-San Wang
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA Penn Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA Genomics and Computational Biology Graduate Group, University of Pennsylvania, Philadelphia, PA 19104, USA Institute on Aging, University of Pennsylvania, Philadelphia, PA 19104, USA
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106
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Selitsky SR, Sethupathy P. tDRmapper: challenges and solutions to mapping, naming, and quantifying tRNA-derived RNAs from human small RNA-sequencing data. BMC Bioinformatics 2015; 16:354. [PMID: 26530785 PMCID: PMC4632369 DOI: 10.1186/s12859-015-0800-0] [Citation(s) in RCA: 62] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2015] [Accepted: 10/23/2015] [Indexed: 11/29/2022] Open
Abstract
Background Small RNA-sequencing has revealed the diversity and high abundance of small RNAs derived from tRNAs, referred to as tRNA-derived RNAs. However, at present, there is no standardized nomenclature and there are no methods for accurate annotation and quantification of these small RNAs. tRNA-derived RNAs have unique features that limit the utility of conventional alignment tools and quantification methods. Results We describe here the challenges of mapping, naming, and quantifying tRNA-derived RNAs and present a novel method that addresses them, called tDRmapper. We then use tDRmapper to perform a comparative analysis of tRNA-derived RNA profiles across different human cell types and diseases. We found that (1) tRNA-derived RNA profiles can differ dramatically across different cell types and disease states, (2) that positions and types of chemical modifications of tRNA-derived RNAs vary by cell type and disease, and (3) that entirely different tRNA-derived RNA species can be produced from the same parental tRNA depending on the cell type. Conclusion tDRmappernot only provides a standardized nomenclature and quantification scheme, but also includes graphical visualization that facilitates the discovery of novel tRNA and tRNA-derived RNA biology.
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Affiliation(s)
- Sara R Selitsky
- Bioinformatics and Computational Biology Curriculum, University of North Carolina, Chapel Hill, NC, USA. .,Departments of Genetics, University of North Carolina, Chapel Hill, NC, USA. .,Microbiology & Immunology, University of North Carolina, Chapel Hill, NC, USA.
| | - Praveen Sethupathy
- Bioinformatics and Computational Biology Curriculum, University of North Carolina, Chapel Hill, NC, USA. .,Departments of Genetics, University of North Carolina, Chapel Hill, NC, USA. .,Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, USA.
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107
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Abstract
Plant genomes encode various small RNAs that function in distinct, yet overlapping, genetic and epigenetic silencing pathways. However, the abundance and diversity of small-RNA classes varies among plant species, suggesting coevolution between environmental adaptations and gene-silencing mechanisms. Biogenesis of small RNAs in plants is well understood, but we are just beginning to uncover their intricate regulation and activity. Here, we discuss the biogenesis of plant small RNAs, such as microRNAs, secondary siRNAs and heterochromatic siRNAs, and their diverse cellular and developmental functions, including in reproductive transitions, genomic imprinting and paramutation. We also discuss the diversification of small-RNA-directed silencing pathways through the expansion of RNA-dependent RNA polymerases, DICER proteins and ARGONAUTE proteins.
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108
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Lockhart J. Revealing the Elusive Plant Epitranscriptome. THE PLANT CELL 2015; 27:3019-3020. [PMID: 26561560 PMCID: PMC4682309 DOI: 10.1105/tpc.15.00908] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
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109
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Vandivier LE, Campos R, Kuksa PP, Silverman IM, Wang LS, Gregory BD. Chemical Modifications Mark Alternatively Spliced and Uncapped Messenger RNAs in Arabidopsis. THE PLANT CELL 2015; 27:3024-37. [PMID: 26561561 PMCID: PMC4682304 DOI: 10.1105/tpc.15.00591] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2015] [Accepted: 10/22/2015] [Indexed: 05/03/2023]
Abstract
Posttranscriptional chemical modification of RNA bases is a widespread and physiologically relevant regulator of RNA maturation, stability, and function. While modifications are best characterized in short, noncoding RNAs such as tRNAs, growing evidence indicates that mRNAs and long noncoding RNAs (lncRNAs) are likewise modified. Here, we apply our high-throughput annotation of modified ribonucleotides (HAMR) pipeline to identify and classify modifications that affect Watson-Crick base pairing at three different levels of the Arabidopsis thaliana transcriptome (polyadenylated, small, and degrading RNAs). We find this type of modifications primarily within uncapped, degrading mRNAs and lncRNAs, suggesting they are the cause or consequence of RNA turnover. Additionally, modifications within stable mRNAs tend to occur in alternatively spliced introns, suggesting they regulate splicing. Furthermore, these modifications target mRNAs with coherent functions, including stress responses. Thus, our comprehensive analysis across multiple RNA classes yields insights into the functions of covalent RNA modifications in plant transcriptomes.
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Affiliation(s)
- Lee E Vandivier
- Department of Biology, University of Pennsylvania, Philadelphia, Pennsylvania 19104 Cell and Molecular Biology Graduate Program, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Rafael Campos
- Department of Biology, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Pavel P Kuksa
- Institute for Biomedical Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania 19104 Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania 19104
| | - Ian M Silverman
- Department of Biology, University of Pennsylvania, Philadelphia, Pennsylvania 19104 Cell and Molecular Biology Graduate Program, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Li-San Wang
- Institute for Biomedical Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania 19104 Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania 19104
| | - Brian D Gregory
- Department of Biology, University of Pennsylvania, Philadelphia, Pennsylvania 19104 Cell and Molecular Biology Graduate Program, University of Pennsylvania, Philadelphia, Pennsylvania 19104
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110
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Fray RG, Simpson GG. The Arabidopsis epitranscriptome. CURRENT OPINION IN PLANT BIOLOGY 2015; 27:17-21. [PMID: 26048078 DOI: 10.1016/j.pbi.2015.05.015] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2015] [Revised: 05/14/2015] [Accepted: 05/15/2015] [Indexed: 06/04/2023]
Abstract
The most prevalent internal modification of plant messenger RNAs, N(6)-methyladenosine (m(6)A), was first discovered in the 1970s, then largely forgotten. However, the impact of modifications to eukaryote mRNA, collectively known as the epitranscriptome, has recently attracted renewed attention. mRNA methylation is required for normal Arabidopsis development and the first methylation maps reveal that thousands of Arabidopsis mRNAs are methylated. Arabidopsis is likely to be a model of wide utility in understanding the biological impacts of the epitranscriptome. We review recent progress and look ahead with questions awaiting answers to reveal an entire layer of gene regulation that has until recently been overlooked.
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Affiliation(s)
- Rupert G Fray
- School of Biosciences, University of Nottingham, Sutton Bonington Campus, Loughborough, Leicestershire LE12 5RD, UK.
| | - Gordon G Simpson
- Division of Plant Sciences, College of Life Sciences, University of Dundee, Cell and Molecular Sciences, James Hutton Institute, Invergowrie DD2 5DA, Scotland, UK.
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111
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Foley SW, Vandivier LE, Kuksa PP, Gregory BD. Transcriptome-wide measurement of plant RNA secondary structure. CURRENT OPINION IN PLANT BIOLOGY 2015; 27:36-43. [PMID: 26119389 PMCID: PMC5096376 DOI: 10.1016/j.pbi.2015.05.021] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2015] [Revised: 05/15/2015] [Accepted: 05/18/2015] [Indexed: 05/19/2023]
Abstract
RNAs fold into intricate and precise secondary structures. These structural patterns regulate multiple steps of the RNA lifecycle, while also conferring catalytic and scaffolding functions to certain transcripts. Therefore, a full understanding of RNA posttranscriptional regulation requires a comprehensive picture of secondary structure. Here, we review several high throughput sequencing-based methods to globally survey plant RNA secondary structure. These methods are more accurate than computational prediction, and more scalable than physical techniques such as crystallography. We note hurdles to reliably measuring secondary structure, including RNA-binding proteins, RNA base modifications, and intramolecular duplexes. Finally, we survey the functional knowledge that has been gleaned from each of these methods, and identify some unanswered questions that remain.
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Affiliation(s)
- Shawn W Foley
- Department of Biology, University of Pennsylvania School of Arts and Sciences, Philadelphia, PA 19104, USA; Cell and Molecular Biology Graduate Program, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Lee E Vandivier
- Department of Biology, University of Pennsylvania School of Arts and Sciences, Philadelphia, PA 19104, USA; Cell and Molecular Biology Graduate Program, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Pavel P Kuksa
- Institute for Biomedical Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Brian D Gregory
- Department of Biology, University of Pennsylvania School of Arts and Sciences, Philadelphia, PA 19104, USA; Cell and Molecular Biology Graduate Program, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA.
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112
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Guo Y, Bosompem A, Mohan S, Erdogan B, Ye F, Vickers KC, Sheng Q, Zhao S, Li CI, Su PF, Jagasia M, Strickland SA, Griffiths EA, Kim AS. Transfer RNA detection by small RNA deep sequencing and disease association with myelodysplastic syndromes. BMC Genomics 2015; 16:727. [PMID: 26400237 PMCID: PMC4581457 DOI: 10.1186/s12864-015-1929-y] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2015] [Accepted: 09/16/2015] [Indexed: 11/10/2022] Open
Abstract
Background Although advances in sequencing technologies have popularized the use of microRNA (miRNA) sequencing (miRNA-seq) for the quantification of miRNA expression, questions remain concerning the optimal methodologies for analysis and utilization of the data. The construction of a miRNA sequencing library selects RNA by length rather than type. However, as we have previously described, miRNAs represent only a subset of the species obtained by size selection. Consequently, the libraries obtained for miRNA sequencing also contain a variety of additional species of small RNAs. This study looks at the prevalence of these other species obtained from bone marrow aspirate specimens and explores the predictive value of these small RNAs in the determination of response to therapy in myelodysplastic syndromes (MDS). Methods Paired pre and post treatment bone marrow aspirate specimens were obtained from patients with MDS who were treated with either azacytidine or decitabine (24 pre-treatment specimens, 23 post-treatment specimens) with 22 additional non-MDS control specimens. Total RNA was extracted from these specimens and submitted for next generation sequencing after an additional size exclusion step to enrich for small RNAs. The species of small RNAs were enumerated, single nucleotide variants (SNVs) identified, and finally the differential expression of tRNA-derived species (tDRs) in the specimens correlated with diseasestatus and response to therapy. Results Using miRNA sequencing data generated from bone marrow aspirate samples of patients with known MDS (N = 47) and controls (N = 23), we demonstrated that transfer RNA (tRNA) fragments (specifically tRNA halves, tRHs) are one of the most common species of small RNA isolated from size selection. Using tRNA expression values extracted from miRNA sequencing data, we identified six tRNA fragments that are differentially expressed between MDS and normal samples. Using the elastic net method, we identified four tRNAs-derived small RNAs (tDRs) that together can explain 67 % of the variation in treatment response for MDS patients. Similar analysis of specifically mitochondrial tDRs (mt-tDRs) identified 13 mt-tDRs which distinguished disease status in the samples and a single mt-tDR which predited response. Finally, 14 SNVs within the tDRs were found in at least 20 % of the MDS samples and were not observed in any of the control specimens. Discussion This study highlights the prevalence of tDRs in RNA-seq studies focused on small RNAs. The potential etiologies of these species, both technical and biologic, are discussed as well as important challenges in the interpretation of tDR data. Conclusions Our analysis results suggest that tRNA fragments can be accurately detected through miRNA sequencing data and that the expression of these species may be useful in the diagnosis of MDS and the prediction of response to therapy. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1929-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Yan Guo
- Department of Cancer Biology, Vanderbilt University Medical Center, Nashville, TN, USA.
| | - Amma Bosompem
- Department of Pathology, Immunology, and Microbiology, Vanderbilt University Medical Center, Nashville, TN, USA.
| | - Sanjay Mohan
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
| | - Begum Erdogan
- Department of Pathology, Immunology, and Microbiology, Vanderbilt University Medical Center, Nashville, TN, USA.
| | - Fei Ye
- Department of Biostatistics, Vanderbilt University, Nashville, TN, USA.
| | - Kasey C Vickers
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
| | - Quanhu Sheng
- Department of Cancer Biology, Vanderbilt University Medical Center, Nashville, TN, USA.
| | - Shilin Zhao
- Department of Cancer Biology, Vanderbilt University Medical Center, Nashville, TN, USA.
| | - Chung-I Li
- Department of Applied Mathematics, National Chiayi University, Chiayi City, Taiwan.
| | - Pei-Fang Su
- Department of Statistics, National Cheng Kung University, Tainan City, Taiwan.
| | - Madan Jagasia
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
| | - Stephen A Strickland
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
| | | | - Annette S Kim
- Department of Pathology, Immunology, and Microbiology, Vanderbilt University Medical Center, Nashville, TN, USA. .,Present address: Brigham and Women's Hospital, 75 Francis Street, Boston, MA, 02115, USA.
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113
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Hauenschild R, Tserovski L, Schmid K, Thüring K, Winz ML, Sharma S, Entian KD, Wacheul L, Lafontaine DLJ, Anderson J, Alfonzo J, Hildebrandt A, Jäschke A, Motorin Y, Helm M. The reverse transcription signature of N-1-methyladenosine in RNA-Seq is sequence dependent. Nucleic Acids Res 2015; 43:9950-64. [PMID: 26365242 PMCID: PMC4787781 DOI: 10.1093/nar/gkv895] [Citation(s) in RCA: 117] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2015] [Accepted: 08/27/2015] [Indexed: 12/26/2022] Open
Abstract
The combination of Reverse Transcription (RT) and high-throughput sequencing has emerged as a powerful combination to detect modified nucleotides in RNA via analysis of either abortive RT-products or of the incorporation of mismatched dNTPs into cDNA. Here we simultaneously analyze both parameters in detail with respect to the occurrence of N-1-methyladenosine (m1A) in the template RNA. This naturally occurring modification is associated with structural effects, but it is also known as a mediator of antibiotic resistance in ribosomal RNA. In structural probing experiments with dimethylsulfate, m1A is routinely detected by RT-arrest. A specifically developed RNA-Seq protocol was tailored to the simultaneous analysis of RT-arrest and misincorporation patterns. By application to a variety of native and synthetic RNA preparations, we found a characteristic signature of m1A, which, in addition to an arrest rate, features misincorporation as a significant component. Detailed analysis suggests that the signature depends on RNA structure and on the nature of the nucleotide 3′ of m1A in the template RNA, meaning it is sequence dependent. The RT-signature of m1A was used for inspection and confirmation of suspected modification sites and resulted in the identification of hitherto unknown m1A residues in trypanosomal tRNA.
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Affiliation(s)
- Ralf Hauenschild
- Institute of Pharmacy and Biochemistry, Johannes Gutenberg University Mainz, Staudingerweg 5, 55128 Mainz, Germany
| | - Lyudmil Tserovski
- Institute of Pharmacy and Biochemistry, Johannes Gutenberg University Mainz, Staudingerweg 5, 55128 Mainz, Germany
| | - Katharina Schmid
- Institute of Pharmacy and Biochemistry, Johannes Gutenberg University Mainz, Staudingerweg 5, 55128 Mainz, Germany
| | - Kathrin Thüring
- Institute of Pharmacy and Biochemistry, Johannes Gutenberg University Mainz, Staudingerweg 5, 55128 Mainz, Germany
| | - Marie-Luise Winz
- Institute of Pharmacy and Molecular Biotechnology (IPMB), Heidelberg University, Im Neuenheimer Feld 364, 69120 Heidelberg, Germany
| | - Sunny Sharma
- Institute of Molecular Biosciences: Goethe University Frankfurt, Max-von-Laue Street 9, 60438 Frankfurt/M, Germany
| | - Karl-Dieter Entian
- Institute of Molecular Biosciences: Goethe University Frankfurt, Max-von-Laue Street 9, 60438 Frankfurt/M, Germany
| | - Ludivine Wacheul
- RNA Molecular Biology, Université Libre de Bruxelles, Rue Profs Jeener & Brachet, 12, B-6041 Charleroi-Gosselies, Belgium
| | - Denis L J Lafontaine
- RNA Molecular Biology, Université Libre de Bruxelles, Rue Profs Jeener & Brachet, 12, B-6041 Charleroi-Gosselies, Belgium
| | - James Anderson
- Department of Biological Sciences, Marquette University, 53201-1881, Milwaukee, WI, USA
| | - Juan Alfonzo
- Department of Microbiology, The Ohio State University, 43210, Columbus, OH, USA
| | - Andreas Hildebrandt
- Institute for Computer Sciences, Johannes Gutenberg University Mainz, Staudingerweg 9, 55128 Mainz, Germany
| | - Andres Jäschke
- Institute of Pharmacy and Molecular Biotechnology (IPMB), Heidelberg University, Im Neuenheimer Feld 364, 69120 Heidelberg, Germany
| | - Yuri Motorin
- IMoPA UMR7365 CNRS-UL, BioPole de l'Université de Lorraine, 9 avenue de la Foret de Haye, 54505 Vandoeuvre-les-Nancy, France
| | - Mark Helm
- Institute of Pharmacy and Biochemistry, Johannes Gutenberg University Mainz, Staudingerweg 5, 55128 Mainz, Germany
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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: 350] [Impact Index Per Article: 35.0] [Reference Citation Analysis] [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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115
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Single-nucleotide-resolution mapping of m6A and m6Am throughout the transcriptome. Nat Methods 2015; 12:767-72. [PMID: 26121403 PMCID: PMC4487409 DOI: 10.1038/nmeth.3453] [Citation(s) in RCA: 1135] [Impact Index Per Article: 113.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2014] [Accepted: 05/28/2015] [Indexed: 12/27/2022]
Abstract
N6-methyladenosine (m6A) is the most abundant modified base in eukaryotic mRNA and has been linked to diverse effects on mRNA fate. Current m6A mapping approaches localize m6A residues to 100–200 nt-long regions of transcripts. The precise position of m6A in mRNAs cannot be identified on a transcriptome-wide level because there are no chemical methods to distinguish between m6A and adenosine. Here we show that anti-m6A antibodies can induce specific mutational signatures at m6A residues after ultraviolet light-induced antibody-RNA crosslinking and reverse transcription. We find these antibodies similarly induce mutational signatures at N6,2′-O-dimethyladenosine (m6Am), a nucleotide found at the first encoded position of certain mRNAs. Using these mutational signatures, we map m6A and m6Am at single-nucleotide resolution in human and mouse mRNA and identify snoRNAs as a novel class of m6A-containing ncRNAs.
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116
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Torres AG, Piñeyro D, Rodríguez-Escribà M, Camacho N, Reina O, Saint-Léger A, Filonava L, Batlle E, Ribas de Pouplana L. Inosine modifications in human tRNAs are incorporated at the precursor tRNA level. Nucleic Acids Res 2015; 43:5145-57. [PMID: 25916855 PMCID: PMC4446420 DOI: 10.1093/nar/gkv277] [Citation(s) in RCA: 85] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2015] [Accepted: 03/20/2015] [Indexed: 11/12/2022] Open
Abstract
Transfer RNAs (tRNAs) are key adaptor molecules of the genetic code that are heavily modified post-transcriptionally. Inosine at the first residue of the anticodon (position 34; I34) is an essential widespread tRNA modification that has been poorly studied thus far. The modification in eukaryotes results from a deamination reaction of adenine that is catalyzed by the heterodimeric enzyme adenosine deaminase acting on tRNA (hetADAT), composed of two subunits: ADAT2 and ADAT3. Using high-throughput small RNA sequencing (RNAseq), we show that this modification is incorporated to human tRNAs at the precursor tRNA level and during maturation. We also functionally validated the human genes encoding for hetADAT and show that the subunits of this enzyme co-localize in nucleus in an ADAT2-dependent manner. Finally, by knocking down HsADAT2, we demonstrate that variations in the cellular levels of hetADAT will result in changes in the levels of I34 modification in all its potential substrates. Altogether, we present RNAseq as a powerful tool to study post-transcriptional tRNA modifications at the precursor tRNA level and give the first insights on the biology of I34 tRNA modification in metazoans.
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Affiliation(s)
- Adrian Gabriel Torres
- Institute for Research in Biomedicine (IRB Barcelona), C/Baldiri Reixac 10, Barcelona, 08028 Catalonia, Spain
| | - David Piñeyro
- Institute for Research in Biomedicine (IRB Barcelona), C/Baldiri Reixac 10, Barcelona, 08028 Catalonia, Spain
| | - Marta Rodríguez-Escribà
- Institute for Research in Biomedicine (IRB Barcelona), C/Baldiri Reixac 10, Barcelona, 08028 Catalonia, Spain
| | - Noelia Camacho
- Institute for Research in Biomedicine (IRB Barcelona), C/Baldiri Reixac 10, Barcelona, 08028 Catalonia, Spain
| | - Oscar Reina
- Institute for Research in Biomedicine (IRB Barcelona), C/Baldiri Reixac 10, Barcelona, 08028 Catalonia, Spain
| | - Adélaïde Saint-Léger
- Institute for Research in Biomedicine (IRB Barcelona), C/Baldiri Reixac 10, Barcelona, 08028 Catalonia, Spain
| | - Liudmila Filonava
- Institute for Research in Biomedicine (IRB Barcelona), C/Baldiri Reixac 10, Barcelona, 08028 Catalonia, Spain
| | - Eduard Batlle
- Institute for Research in Biomedicine (IRB Barcelona), C/Baldiri Reixac 10, Barcelona, 08028 Catalonia, Spain Catalan Institution for Research and Advanced Studies (ICREA), P/Lluis Companys 23, Barcelona, 08010 Catalonia, Spain
| | - Lluís Ribas de Pouplana
- Institute for Research in Biomedicine (IRB Barcelona), C/Baldiri Reixac 10, Barcelona, 08028 Catalonia, Spain Catalan Institution for Research and Advanced Studies (ICREA), P/Lluis Companys 23, Barcelona, 08010 Catalonia, Spain
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117
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Pang YLJ, Abo R, Levine SS, Dedon PC. Diverse cell stresses induce unique patterns of tRNA up- and down-regulation: tRNA-seq for quantifying changes in tRNA copy number. Nucleic Acids Res 2014; 42:e170. [PMID: 25348403 PMCID: PMC4267671 DOI: 10.1093/nar/gku945] [Citation(s) in RCA: 98] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Emerging evidence points to roles for tRNA modifications and tRNA abundance in cellular stress responses. While isolated instances of stress-induced tRNA degradation have been reported, we sought to assess the effects of stress on tRNA levels at a systems level. To this end, we developed a next-generation sequencing method that exploits the paucity of ribonucleoside modifications at the 3′-end of tRNAs to quantify changes in all cellular tRNA molecules. Application of this tRNA-seq method to Saccharomyces cerevisiae identified all 76 expressed unique tRNA species out of 295 coded in the yeast genome, including all isoacceptor variants, with highly precise relative (fold-change) quantification of tRNAs. In studies of stress-induced changes in tRNA levels, we found that oxidation (H2O2) and alkylation (methylmethane sulfonate, MMS) stresses induced nearly identical patterns of up- and down-regulation for 58 tRNAs. However, 18 tRNAs showed opposing changes for the stresses, which parallels our observation of signature reprogramming of tRNA modifications caused by H2O2 and MMS. Further, stress-induced degradation was limited to only a small proportion of a few tRNA species. With tRNA-seq applicable to any organism, these results suggest that translational control of stress response involves a contribution from tRNA abundance.
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Affiliation(s)
- Yan Ling Joy Pang
- Department of Biological Engineering and Infectious Diseases Interdisciplinary Research Group, Singapore-MIT Alliance for Research & Technology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Ryan Abo
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Stuart S Levine
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Peter C Dedon
- Department of Biological Engineering and Infectious Diseases Interdisciplinary Research Group, Singapore-MIT Alliance for Research & Technology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
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