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Backofen R, Gorodkin J, Hofacker IL, Stadler PF. Comparative RNA Genomics. Methods Mol Biol 2024; 2802:347-393. [PMID: 38819565 DOI: 10.1007/978-1-0716-3838-5_12] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/01/2024]
Abstract
Over the last quarter of a century it has become clear that RNA is much more than just a boring intermediate in protein expression. Ancient RNAs still appear in the core information metabolism and comprise a surprisingly large component in bacterial gene regulation. A common theme with these types of mostly small RNAs is their reliance of conserved secondary structures. Large-scale sequencing projects, on the other hand, have profoundly changed our understanding of eukaryotic genomes. Pervasively transcribed, they give rise to a plethora of large and evolutionarily extremely flexible non-coding RNAs that exert a vastly diverse array of molecule functions. In this chapter we provide a-necessarily incomplete-overview of the current state of comparative analysis of non-coding RNAs, emphasizing computational approaches as a means to gain a global picture of the modern RNA world.
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Affiliation(s)
- Rolf Backofen
- Bioinformatics Group, Department of Computer Science, University of Freiburg, Freiburg, Germany
- Center for Non-coding RNA in Technology and Health, University of Copenhagen, Frederiksberg, Denmark
| | - Jan Gorodkin
- Center for Non-coding RNA in Technology and Health, Department of Veterinary and Animal Sciences, University of Copenhagen, Frederiksberg, Denmark
| | - Ivo L Hofacker
- Institute for Theoretical Chemistry, University of Vienna, Wien, Austria
- Bioinformatics and Computational Biology research group, University of Vienna, Vienna, Austria
- Center for Non-coding RNA in Technology and Health, University of Copenhagen, Frederiksberg, Denmark
| | - Peter F Stadler
- Bioinformatics Group, Department of Computer Science, University of Leipzig, Leipzig, Germany.
- Interdisciplinary Center for Bioinformatics, University of Leipzig, Leipzig, Germany.
- Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany.
- Universidad National de Colombia, Bogotá, Colombia.
- Institute for Theoretical Chemistry, University of Vienna, Wien, Austria.
- Center for Non-coding RNA in Technology and Health, University of Copenhagen, Frederiksberg, Denmark.
- Santa Fe Institute, Santa Fe, NM, USA.
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2
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Klapproth C, Zötzsche S, Kühnl F, Fallmann J, Stadler P, Findeiß S. Tailored machine learning models for functional RNA detection in genome-wide screens. NAR Genom Bioinform 2023; 5:lqad072. [PMID: 37608800 PMCID: PMC10440787 DOI: 10.1093/nargab/lqad072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 06/28/2023] [Accepted: 07/30/2023] [Indexed: 08/24/2023] Open
Abstract
The in silico prediction of non-coding and protein-coding genetic loci has received considerable attention in comparative genomics aiming in particular at the identification of properties of nucleotide sequences that are informative of their biological role in the cell. We present here a software framework for the alignment-based training, evaluation and application of machine learning models with user-defined parameters. Instead of focusing on the one-size-fits-all approach of pervasive in silico annotation pipelines, we offer a framework for the structured generation and evaluation of models based on arbitrary features and input data, focusing on stable and explainable results. Furthermore, we showcase the usage of our software package in a full-genome screen of Drosophila melanogaster and evaluate our results against the well-known but much less flexible program RNAz.
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Affiliation(s)
- Christopher Klapproth
- Leipzig University, Department of Computer Science and Interdisciplinary Center of Bioinformatics, Bioinformatics Group, Härtelstrasse 16-18, D-04107 Leipzig, Germany
- ScaDS.AI Leipzig (Center for Scalable Data Analytics and Artificial Intelligence), Humboldtstraße 25, D-04105 Leipzig, Germany
| | - Siegfried Zötzsche
- Leipzig University, Department of Computer Science and Interdisciplinary Center of Bioinformatics, Bioinformatics Group, Härtelstrasse 16-18, D-04107 Leipzig, Germany
| | - Felix Kühnl
- Leipzig University, Department of Computer Science and Interdisciplinary Center of Bioinformatics, Bioinformatics Group, Härtelstrasse 16-18, D-04107 Leipzig, Germany
| | - Jörg Fallmann
- Leipzig University, Department of Computer Science and Interdisciplinary Center of Bioinformatics, Bioinformatics Group, Härtelstrasse 16-18, D-04107 Leipzig, Germany
| | - Peter F Stadler
- Leipzig University, Department of Computer Science and Interdisciplinary Center of Bioinformatics, Bioinformatics Group, Härtelstrasse 16-18, D-04107 Leipzig, Germany
- Max Planck Institute for Mathematics in the Science, Inselstraße 22, D-04103 Leipzig, Germany
- University of Vienna, Institute for Theoretical Chemistry, Währingerstraße 17, A-1090 Vienna, Austria
- Santa Fe Institute, 1399 Hyde Park Rd., Santa Fe NM 97501, USA
- Universidad Nacional de Colombia, Facultad de Ciencias, Bogotá, D.C., Colombia
| | - Sven Findeiß
- Leipzig University, Department of Computer Science and Interdisciplinary Center of Bioinformatics, Bioinformatics Group, Härtelstrasse 16-18, D-04107 Leipzig, Germany
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3
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Suksamran R, Saithong T, Thammarongtham C, Kalapanulak S. Genomic and Transcriptomic Analysis Identified Novel Putative Cassava lncRNAs Involved in Cold and Drought Stress. Genes (Basel) 2020; 11:E366. [PMID: 32231066 PMCID: PMC7230406 DOI: 10.3390/genes11040366] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Revised: 03/23/2020] [Accepted: 03/24/2020] [Indexed: 01/09/2023] Open
Abstract
Long non-coding RNAs (lncRNAs) play important roles in the regulation of complex cellular processes, including transcriptional and post-transcriptional regulation of gene expression relevant for development and stress response, among others. Compared to other important crops, there is limited knowledge of cassava lncRNAs and their roles in abiotic stress adaptation. In this study, we performed a genome-wide study of ncRNAs in cassava, integrating genomics- and transcriptomics-based approaches. In total, 56,840 putative ncRNAs were identified, and approximately half the number were verified using expression data or previously known ncRNAs. Among these were 2229 potential novel lncRNA transcripts with unmatched sequences, 250 of which were differentially expressed in cold or drought conditions, relative to controls. We showed that lncRNAs might be involved in post-transcriptional regulation of stress-induced transcription factors (TFs) such as zinc-finger, WRKY, and nuclear factor Y gene families. These findings deepened our knowledge of cassava lncRNAs and shed light on their stress-responsive roles.
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Affiliation(s)
- Rungaroon Suksamran
- Biotechnology Program, School of Bioresources and Technology, King Mongkut's University of Technology Thonburi (Bang KhunThian), Bangkok 10150, Thailand
| | - Treenut Saithong
- Bioinformatics and Systems Biology Program, School of Bioresources and Technology, King Mongkut's University of Technology Thonburi (Bang KhunThian), Bangkok 10150, Thailand
- Center for Agricultural Systems Biology, Systems Biology and Bioinformatics Research Group, Pilot Plant Development and Training Institute, King Mongkut's University of Technology Thonburi (Bang KhunThian), Bangkok 10150, Thailand
| | - Chinae Thammarongtham
- Biochemical Engineering and Systems Biology Research Group, National Center for Genetic Engineering and Biotechnology at King Mongkut's University of Technology Thonburi (Bang KhunThian), Bangkok 10150, Thailand
| | - Saowalak Kalapanulak
- Bioinformatics and Systems Biology Program, School of Bioresources and Technology, King Mongkut's University of Technology Thonburi (Bang KhunThian), Bangkok 10150, Thailand
- Center for Agricultural Systems Biology, Systems Biology and Bioinformatics Research Group, Pilot Plant Development and Training Institute, King Mongkut's University of Technology Thonburi (Bang KhunThian), Bangkok 10150, Thailand
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4
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Kirsch R, Seemann SE, Ruzzo WL, Cohen SM, Stadler PF, Gorodkin J. Identification and characterization of novel conserved RNA structures in Drosophila. BMC Genomics 2018; 19:899. [PMID: 30537930 PMCID: PMC6288889 DOI: 10.1186/s12864-018-5234-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2018] [Accepted: 11/08/2018] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Comparative genomics approaches have facilitated the discovery of many novel non-coding and structured RNAs (ncRNAs). The increasing availability of related genomes now makes it possible to systematically search for compensatory base changes - and thus for conserved secondary structures - even in genomic regions that are poorly alignable in the primary sequence. The wealth of available transcriptome data can add valuable insight into expression and possible function for new ncRNA candidates. Earlier work identifying ncRNAs in Drosophila melanogaster made use of sequence-based alignments and employed a sliding window approach, inevitably biasing identification toward RNAs encoded in the more conserved parts of the genome. RESULTS To search for conserved RNA structures (CRSs) that may not be highly conserved in sequence and to assess the expression of CRSs, we conducted a genome-wide structural alignment screen of 27 insect genomes including D. melanogaster and integrated this with an extensive set of tiling array data. The structural alignment screen revealed ∼30,000 novel candidate CRSs at an estimated false discovery rate of less than 10%. With more than one quarter of all individual CRS motifs showing sequence identities below 60%, the predicted CRSs largely complement the findings of sliding window approaches applied previously. While a sixth of the CRSs were ubiquitously expressed, we found that most were expressed in specific developmental stages or cell lines. Notably, most statistically significant enrichment of CRSs were observed in pupae, mainly in exons of untranslated regions, promotors, enhancers, and long ncRNAs. Interestingly, cell lines were found to express a different set of CRSs than were found in vivo. Only a small fraction of intergenic CRSs were co-expressed with the adjacent protein coding genes, which suggests that most intergenic CRSs are independent genetic units. CONCLUSIONS This study provides a more comprehensive view of the ncRNA transcriptome in fly as well as evidence for differential expression of CRSs during development and in cell lines.
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Affiliation(s)
- Rebecca Kirsch
- Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, Frederiksberg C, DK-1870 Denmark
- Department of Veterinary and Animal Science, University of Copenhagen, Grønnegårdsvej 3, Frederiksberg C, DK-1870 Denmark
- Bioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, Universität Leipzig, Härtelstraße 16–18, Leipzig, D-04107 Germany
| | - Stefan E. Seemann
- Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, Frederiksberg C, DK-1870 Denmark
- Department of Veterinary and Animal Science, University of Copenhagen, Grønnegårdsvej 3, Frederiksberg C, DK-1870 Denmark
| | - Walter L. Ruzzo
- Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, Frederiksberg C, DK-1870 Denmark
- School of Computer Science and Engineering, University of Washington, Box 352350, Seattle, 98195-2350 WA USA
- Department of Genome Sciences, University of Washington, Box 355065, Seattle, 98195-5065 WA USA
- Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. N., Seattle, 98109-1024 WA USA
| | - Stephen M. Cohen
- Department of Cellular and Molecular Medicine, University of Copenhagen, Blegdamsvej 3, Copenhagen N, DK-2200 Denmark
| | - Peter F. Stadler
- Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, Frederiksberg C, DK-1870 Denmark
- Bioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, Universität Leipzig, Härtelstraße 16–18, Leipzig, D-04107 Germany
- Max Planck Institute for Mathematics in the Sciences, Inselstraße 22, Leipzig, D-04103 Germany
- Faculdad de Ciencias, Universidad Nacional de Colombia, Sede Bogotá, Ciudad Universitaria, Bogotá, COL-111321 D.C. Colombia
- Department of Theoretical Chemistry, University of Vienna, Währinger Straße 17, Vienna, A-1090 Austria
- Santa Fe Institute, 1399 Hyde Park Rd., Santa Fe, NM87501 USA
| | - Jan Gorodkin
- Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, Frederiksberg C, DK-1870 Denmark
- Department of Veterinary and Animal Science, University of Copenhagen, Grønnegårdsvej 3, Frederiksberg C, DK-1870 Denmark
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5
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Abstract
Over the last two decades it has become clear that RNA is much more than just a boring intermediate in protein expression. Ancient RNAs still appear in the core information metabolism and comprise a surprisingly large component in bacterial gene regulation. A common theme with these types of mostly small RNAs is their reliance of conserved secondary structures. Large scale sequencing projects, on the other hand, have profoundly changed our understanding of eukaryotic genomes. Pervasively transcribed, they give rise to a plethora of large and evolutionarily extremely flexible noncoding RNAs that exert a vastly diverse array of molecule functions. In this chapter we provide a-necessarily incomplete-overview of the current state of comparative analysis of noncoding RNAs, emphasizing computational approaches as a means to gain a global picture of the modern RNA world.
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Affiliation(s)
- Rolf Backofen
- Bioinformatics Group, Department of Computer Science, University of Freiburg, Georges-Köhler-Allee 106, D-79110 Freiburg, Germany.,Center for non-coding RNA in Technology and Health, Department of Veterinary and Animal Sciences, University of Copenhagen, Grønnegårdsvej 3, DK-1870 Frederiksberg C, Denmark
| | - Jan Gorodkin
- Center for non-coding RNA in Technology and Health, Department of Veterinary and Animal Sciences, University of Copenhagen, Grønnegårdsvej 3, DK-1870 Frederiksberg C, Denmark
| | - Ivo L Hofacker
- Center for non-coding RNA in Technology and Health, Department of Veterinary and Animal Sciences, University of Copenhagen, Grønnegårdsvej 3, DK-1870 Frederiksberg C, Denmark.,Institute for Theoretical Chemistry, University of Vienna, Währingerstraße 17, A-1090 Wien, Austria.,Bioinformatics and Computational Biology Research Group, University of Vienna, Währingerstraße 17, A-1090 Vienna, Austria
| | - Peter F Stadler
- Center for non-coding RNA in Technology and Health, Department of Veterinary and Animal Sciences, University of Copenhagen, Grønnegårdsvej 3, DK-1870 Frederiksberg C, Denmark. .,Institute for Theoretical Chemistry, University of Vienna, Währingerstraße 17, A-1090 Wien, Austria. .,Bioinformatics Group, Department of Computer Science, Interdisciplinary Center for Bioinformatics, University of Leipzig, Härtelstraße 16-18, D-04107 Leipzig, Germany. .,Max Planck Institute for Mathematics in the Sciences, Inselstraße 22, D-04103 Leipzig, Germany. .,Fraunhofer Institute for Cell Therapy and Immunology, Perlickstraße 1, D-04103 Leipzig, Germany. .,Santa Fe Institute, 1399 Hyde Park Rd, Santa Fe, NM 87501, USA.
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6
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Nitsche A, Stadler PF. Evolutionary clues in lncRNAs. WILEY INTERDISCIPLINARY REVIEWS-RNA 2016; 8. [PMID: 27436689 DOI: 10.1002/wrna.1376] [Citation(s) in RCA: 43] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/24/2016] [Revised: 06/06/2016] [Accepted: 06/09/2016] [Indexed: 12/13/2022]
Abstract
The diversity of long non-coding RNAs (lncRNAs) in the human transcriptome is in stark contrast to the sparse exploration of their functions concomitant with their conservation and evolution. The pervasive transcription of the largely non-coding human genome makes the evolutionary age and conservation patterns of lncRNAs to a topic of interest. Yet it is a fairly unexplored field and not that easy to determine as for protein-coding genes. Although there are a few experimentally studied cases, which are conserved at the sequence level, most lncRNAs exhibit weak or untraceable primary sequence conservation. Recent studies shed light on the interspecies conservation of secondary structures among lncRNA homologs by using diverse computational methods. This highlights the importance of structure on functionality of lncRNAs as opposed to the poor impact of primary sequence changes. Further clues in the evolution of lncRNAs are given by selective constraints on non-coding gene structures (e.g., promoters or splice sites) as well as the conservation of prevalent spatio-temporal expression patterns. However, a rapid evolutionary turnover is observable throughout the heterogeneous group of lncRNAs. This still gives rise to questions about its functional meaning. WIREs RNA 2017, 8:e1376. doi: 10.1002/wrna.1376 For further resources related to this article, please visit the WIREs website.
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Affiliation(s)
- Anne Nitsche
- Bioinformatics Group, Department of Computer Science, University Leipzig, Leipzig, Germany.,Institute de Biologie Moléculaire et Cellulaire, Université de Strasbourg, Cedex, France
| | - Peter F Stadler
- Bioinformatics Group, Department of Computer Science, University Leipzig, Leipzig, Germany.,Interdisciplinary Center for Bioinformatics, University Leipzig, Leipzig, Germany.,Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany.,Department of Diagnostics, Fraunhofer Institute for Cell Therapy and Immunology - IZI, Leipzig, Germany.,Center for Non-Coding RNA in Technology and Health, University of Copenhagen, Frederiksberg, Denmark.,Department of Theoretical Chemistry, University of Vienna, Wien, Austria.,Santa Fe Institute, Santa Fe, NM, USA
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7
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Hecker N, Christensen-Dalsgaard M, Seemann SE, Havgaard JH, Stadler PF, Hofacker IL, Nielsen H, Gorodkin J. Optimizing RNA structures by sequence extensions using RNAcop. Nucleic Acids Res 2015; 43:8135-45. [PMID: 26283181 PMCID: PMC4787817 DOI: 10.1093/nar/gkv813] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2015] [Revised: 07/28/2015] [Accepted: 07/30/2015] [Indexed: 12/26/2022] Open
Abstract
A key aspect of RNA secondary structure prediction is the identification of novel functional elements. This is a challenging task because these elements typically are embedded in longer transcripts where the borders between the element and flanking regions have to be defined. The flanking sequences impact the folding of the functional elements both at the level of computational analyses and when the element is extracted as a transcript for experimental analysis. Here, we analyze how different flanking region lengths impact folding into a constrained structure by computing probabilities of folding for different sizes of flanking regions. Our method, RNAcop (RNA context optimization by probability), is tested on known and de novo predicted structures. In vitro experiments support the computational analysis and suggest that for a number of structures, choosing proper lengths of flanking regions is critical. RNAcop is available as web server and stand-alone software via http://rth.dk/resources/rnacop.
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Affiliation(s)
- Nikolai Hecker
- Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark Department of Veterinary Clinical and Animal Science, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark
| | - Mikkel Christensen-Dalsgaard
- Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark Department of Cellular and Molecular Medicine, Panum Institute, University of Copenhagen, Bledgamsvej 3, 2200 Copenhagen N, Denmark
| | - Stefan E Seemann
- Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark Department of Veterinary Clinical and Animal Science, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark
| | - Jakob H Havgaard
- Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark Department of Veterinary Clinical and Animal Science, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark
| | - Peter F Stadler
- Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark Bioinformatics Group, Department of Computer Science & IZBI-Interdisciplinary Center for Bioinformatics & LIFE-Leipzig Research Center for Civilization Diseases, University Leipzig, Härtelstraße 16-18, 04107 Leipzig, Germany Institute for Theoretical Chemistry, University of Vienna, Währingerstraße 17, 1090 Wien, Austria Max Planck Institute for Mathematics in the Sciences, Inselstraße 22, 04103 Leipzig, Germany Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USA
| | - Ivo L Hofacker
- Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark Institute for Theoretical Chemistry, University of Vienna, Währingerstraße 17, 1090 Wien, Austria
| | - Henrik Nielsen
- Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark Department of Cellular and Molecular Medicine, Panum Institute, University of Copenhagen, Bledgamsvej 3, 2200 Copenhagen N, Denmark
| | - Jan Gorodkin
- Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark Department of Veterinary Clinical and Animal Science, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark
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8
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Lange SJ, Alkhnbashi OS, Rose D, Will S, Backofen R. CRISPRmap: an automated classification of repeat conservation in prokaryotic adaptive immune systems. Nucleic Acids Res 2013; 41:8034-44. [PMID: 23863837 PMCID: PMC3783184 DOI: 10.1093/nar/gkt606] [Citation(s) in RCA: 116] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Central to Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)-Cas systems are repeated RNA sequences that serve as Cas-protein-binding templates. Classification is based on the architectural composition of associated Cas proteins, considering repeat evolution is essential to complete the picture. We compiled the largest data set of CRISPRs to date, performed comprehensive, independent clustering analyses and identified a novel set of 40 conserved sequence families and 33 potential structure motifs for Cas-endoribonucleases with some distinct conservation patterns. Evolutionary relationships are presented as a hierarchical map of sequence and structure similarities for both a quick and detailed insight into the diversity of CRISPR-Cas systems. In a comparison with Cas-subtypes, I-C, I-E, I-F and type II were strongly coupled and the remaining type I and type III subtypes were loosely coupled to repeat and Cas1 evolution, respectively. Subtypes with a strong link to CRISPR evolution were almost exclusive to bacteria; nevertheless, we identified rare examples of potential horizontal transfer of I-C and I-E systems into archaeal organisms. Our easy-to-use web server provides an automated assignment of newly sequenced CRISPRs to our classification system and enables more informed choices on future hypotheses in CRISPR-Cas research: http://rna.informatik.uni-freiburg.de/CRISPRmap.
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Affiliation(s)
- Sita J Lange
- Bioinformatics Group, Department of Computer Science, Albert-Ludwigs-University Freiburg, Georges-Köhler-Allee 106, 79110 Freiburg, Germany, ZBSA Centre for Biological Systems Analysis, Albert-Ludwigs-University Freiburg, Habsburgerstr. 49, 79104 Freiburg, Germany, BIOSS Centre for Biological Signalling Studies, Cluster of Excellence, Albert-Ludwigs-University Freiburg, Germany and Center for non-coding RNA in Technology and Health, University of Copenhagen, Gronnegardsvej 3, DK-1870 Frederiksberg C, Denmark
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9
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Heyne S, Costa F, Rose D, Backofen R. GraphClust: alignment-free structural clustering of local RNA secondary structures. ACTA ACUST UNITED AC 2013; 28:i224-32. [PMID: 22689765 PMCID: PMC3371856 DOI: 10.1093/bioinformatics/bts224] [Citation(s) in RCA: 62] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Motivation: Clustering according to sequence–structure similarity has now become a generally accepted scheme for ncRNA annotation. Its application to complete genomic sequences as well as whole transcriptomes is therefore desirable but hindered by extremely high computational costs. Results: We present a novel linear-time, alignment-free method for comparing and clustering RNAs according to sequence and structure. The approach scales to datasets of hundreds of thousands of sequences. The quality of the retrieved clusters has been benchmarked against known ncRNA datasets and is comparable to state-of-the-art sequence–structure methods although achieving speedups of several orders of magnitude. A selection of applications aiming at the detection of novel structural ncRNAs are presented. Exemplarily, we predicted local structural elements specific to lincRNAs likely functionally associating involved transcripts to vital processes of the human nervous system. In total, we predicted 349 local structural RNA elements. Availability: The GraphClust pipeline is available on request. Contact:backofen@informatik.uni-freiburg.de Supplementary information:Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Steffen Heyne
- Bioinformatics Group, Department of Computer Science, University of Freiburg,Georges-Köhler-Allee 106, D-79110 Freiburg, Germany
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10
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Abstract
Recent genome-wide computational screens that search for conservation of RNA secondary structure in whole-genome alignments (WGAs) have predicted thousands of structural noncoding RNAs (ncRNAs). The sensitivity of such approaches, however, is limited, due to their reliance on sequence-based whole-genome aligners, which regularly misalign structural ncRNAs. This suggests that many more structural ncRNAs may remain undetected. Structure-based alignment, which could increase the sensitivity, has been prohibitive for genome-wide screens due to its extreme computational costs. Breaking this barrier, we present the pipeline REAPR (RE-Alignment for Prediction of structural ncRNA), which efficiently realigns whole genomes based on RNA sequence and structure, thus allowing us to boost the performance of de novo ncRNA predictors, such as RNAz. Key to the pipeline's efficiency is the development of a novel banding technique for multiple RNA alignment. REAPR significantly outperforms the widely used predictors RNAz and EvoFold in genome-wide screens; in direct comparison to the most recent RNAz screen on D. melanogaster, REAPR predicts twice as many high-confidence ncRNA candidates. Moreover, modENCODE RNA-seq experiments confirm a substantial number of its predictions as transcripts. REAPR's advancement of de novo structural characterization of ncRNAs complements the identification of transcripts from rapidly accumulating RNA-seq data.
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Affiliation(s)
- Sebastian Will
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
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11
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Will S, Joshi T, Hofacker IL, Stadler PF, Backofen R. LocARNA-P: accurate boundary prediction and improved detection of structural RNAs. RNA (NEW YORK, N.Y.) 2012; 18:900-14. [PMID: 22450757 PMCID: PMC3334699 DOI: 10.1261/rna.029041.111] [Citation(s) in RCA: 261] [Impact Index Per Article: 21.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2011] [Accepted: 01/18/2012] [Indexed: 05/18/2023]
Abstract
Current genomic screens for noncoding RNAs (ncRNAs) predict a large number of genomic regions containing potential structural ncRNAs. The analysis of these data requires highly accurate prediction of ncRNA boundaries and discrimination of promising candidate ncRNAs from weak predictions. Existing methods struggle with these goals because they rely on sequence-based multiple sequence alignments, which regularly misalign RNA structure and therefore do not support identification of structural similarities. To overcome this limitation, we compute columnwise and global reliabilities of alignments based on sequence and structure similarity; we refer to these structure-based alignment reliabilities as STARs. The columnwise STARs of alignments, or STAR profiles, provide a versatile tool for the manual and automatic analysis of ncRNAs. In particular, we improve the boundary prediction of the widely used ncRNA gene finder RNAz by a factor of 3 from a median deviation of 47 to 13 nt. Post-processing RNAz predictions, LocARNA-P's STAR score allows much stronger discrimination between true- and false-positive predictions than RNAz's own evaluation. The improved accuracy, in this scenario increased from AUC 0.71 to AUC 0.87, significantly reduces the cost of successive analysis steps. The ready-to-use software tool LocARNA-P produces structure-based multiple RNA alignments with associated columnwise STARs and predicts ncRNA boundaries. We provide additional results, a web server for LocARNA/LocARNA-P, and the software package, including documentation and a pipeline for refining screens for structural ncRNA, at http://www.bioinf.uni-freiburg.de/Supplements/LocARNA-P/.
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Affiliation(s)
- Sebastian Will
- Chair for Bioinformatics, Institute of Computer Science, Albert-Ludwigs-Universität, D-79110 Freiburg, Germany
- Computation and Biology Group, CSAIL and Mathematics Department, MIT, Cambridge, Massachusetts 02139, USA
| | - Tejal Joshi
- Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, DK-2800 Kongens Lyngby, Denmark
| | - Ivo L. Hofacker
- Department of Theoretical Chemistry, University of Vienna, A-1090 Wien, Austria
| | - Peter F. Stadler
- Department of Theoretical Chemistry, University of Vienna, A-1090 Wien, Austria
- Bioinformatics Group, Department of Computer Science, Interdisciplinary Center of Bioinformatics, University of Leipzig, D-04107 Leipzig, Germany
- Max-Planck-Institute for Mathematics in the Sciences, D-04103 Leipzig, Germany
- Fraunhofer Institute for Cell Therapy and Immunology, D-04103 Leipzig, Germany
- Santa Fe Institute, Santa Fe, New Mexico 87501, USA
| | - Rolf Backofen
- Chair for Bioinformatics, Institute of Computer Science, Albert-Ludwigs-Universität, D-79110 Freiburg, Germany
- Center for Biological Signaling Studies (BIOSS), University of Freiburg, D-79104 Freiburg, Germany
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12
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Pervouchine DD, Khrameeva EE, Pichugina MY, Nikolaienko OV, Gelfand MS, Rubtsov PM, Mironov AA. Evidence for widespread association of mammalian splicing and conserved long-range RNA structures. RNA (NEW YORK, N.Y.) 2012; 18:1-15. [PMID: 22128342 PMCID: PMC3261731 DOI: 10.1261/rna.029249.111] [Citation(s) in RCA: 50] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/07/2023]
Abstract
Pre-mRNA structure impacts many cellular processes, including splicing in genes associated with disease. The contemporary paradigm of RNA structure prediction is biased toward secondary structures that occur within short ranges of pre-mRNA, although long-range base-pairings are known to be at least as important. Recently, we developed an efficient method for detecting conserved RNA structures on the genome-wide scale, one that does not require multiple sequence alignments and works equally well for the detection of local and long-range base-pairings. Using an enhanced method that detects base-pairings at all possible combinations of splice sites within each gene, we now report RNA structures that could be involved in the regulation of splicing in mammals. Statistically, we demonstrate strong association between the occurrence of conserved RNA structures and alternative splicing, where local RNA structures are generally more frequent at alternative donor splice sites, while long-range structures are more associated with weak alternative acceptor splice sites. As an example, we validated the RNA structure in the human SF1 gene using minigenes in the HEK293 cell line. Point mutations that disrupted the base-pairing of two complementary boxes between exons 9 and 10 of this gene altered the splicing pattern, while the compensatory mutations that reestablished the base-pairing reverted splicing to that of the wild-type. There is statistical evidence for a Dscam-like class of mammalian genes, in which mutually exclusive RNA structures control mutually exclusive alternative splicing. In sum, we propose that long-range base-pairings carry an important, yet unconsidered part of the splicing code, and that, even by modest estimates, there must be thousands of such potentially regulatory structures conserved throughout the evolutionary history of mammals.
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Affiliation(s)
- Dmitri D Pervouchine
- Department of Bioengineering and Bioinformatics, Moscow State University, Moscow, 119992, GSP-2 Russia.
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13
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Rose D, Stadler PF. Molecular evolution of the non-coding eosinophil granule ontogeny transcript. Front Genet 2011; 2:69. [PMID: 22303364 PMCID: PMC3268622 DOI: 10.3389/fgene.2011.00069] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2011] [Accepted: 09/16/2011] [Indexed: 01/22/2023] Open
Abstract
Eukaryotic genomes are pervasively transcribed. A large fraction of the transcriptional output consists of long, mRNA-like, non-protein-coding transcripts (mlncRNAs). The evolutionary history of mlncRNAs is still largely uncharted territory. In this contribution, we explore in detail the evolutionary traces of the eosinophil granule ontogeny transcript (EGOT), an experimentally confirmed representative of an abundant class of totally intronic non-coding transcripts (TINs). EGOT is located antisense to an intron of the ITPR1 gene. We computationally identify putative EGOT orthologs in the genomes of 32 different amniotes, including orthologs from primates, rodents, ungulates, carnivores, afrotherians, and xenarthrans, as well as putative candidates from basal amniotes, such as opossum or platypus. We investigate the EGOT gene phylogeny, analyze patterns of sequence conservation, and the evolutionary conservation of the EGOT gene structure. We show that EGO-B, the spliced isoform, may be present throughout the placental mammals, but most likely dates back even further. We demonstrate here for the first time that the whole EGOT locus is highly structured, containing several evolutionary conserved, and thermodynamic stable secondary structures. Our analyses allow us to postulate novel functional roles of a hitherto poorly understood region at the intron of EGO-B which is highly conserved at the sequence level. The region contains a novel ITPR1 exon and also conserved RNA secondary structures together with a conserved TATA-like element, which putatively acts as a promoter of an independent regulatory element.
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Affiliation(s)
- Dominic Rose
- Bioinformatics Group, Department of Computer Science, University of Freiburg Freiburg, Germany
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14
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Findeiss S, Engelhardt J, Prohaska SJ, Stadler PF. Protein-coding structured RNAs: A computational survey of conserved RNA secondary structures overlapping coding regions in drosophilids. Biochimie 2011; 93:2019-23. [PMID: 21835221 DOI: 10.1016/j.biochi.2011.07.023] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2011] [Accepted: 07/19/2011] [Indexed: 11/15/2022]
Abstract
Functional RNA elements can be embedded also within exonic sequences coding for functional proteins. While not uncommon in viruses, only a few examples of this type have been described in some detail for eukaryotic genomes. Here we use RNAz and RNAcode, two comparative genomics methods that measure signatures of stabilizing selection acting on RNA secondary structure and peptide sequence, resp., to survey the fruit fly genomes. We estimate that there might be on the order of 1000 loci that are subject to dual selection pressure. The used genome-wide screens also expose the limitations of the currently available methods.
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Affiliation(s)
- Sven Findeiss
- Department of Theoretical Chemistry, University of Vienna, Währingerstraße 17, A-1090 Wien, Austria.
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15
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Abstract
Rapid improvements in high-throughput experimental technologies make it nowadays possible to study the expression, as well as changes in expression, of whole transcriptomes under different environmental conditions in a detailed view. We describe current approaches to identify genome-wide functional RNA transcripts (experimentally as well as computationally), and focus on computational methods that may be utilized to disclose their function. While genome databases offer a wealth of information about known and putative functions for protein-coding genes, functional information for novel non-coding RNA genes is almost nonexistent. This is mainly explained by the lack of established software tools to efficiently reveal the function and evolutionary origin of non-coding RNA genes. Here, we describe in detail computational approaches one may follow to annotate and classify an RNA transcript.
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Affiliation(s)
- Kristin Reiche
- Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany
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16
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miRNA Prediction Using Computational Approach. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2011; 696:75-82. [DOI: 10.1007/978-1-4419-7046-6_8] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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17
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Doniger T, Katz R, Wachtel C, Michaeli S, Unger R. A comparative genome-wide study of ncRNAs in trypanosomatids. BMC Genomics 2010; 11:615. [PMID: 21050447 PMCID: PMC3091756 DOI: 10.1186/1471-2164-11-615] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2010] [Accepted: 11/04/2010] [Indexed: 01/18/2023] Open
Abstract
Background Recent studies have provided extensive evidence for multitudes of non-coding RNA (ncRNA) transcripts in a wide range of eukaryotic genomes. ncRNAs are emerging as key players in multiple layers of cellular regulation. With the availability of many whole genome sequences, comparative analysis has become a powerful tool to identify ncRNA molecules. In this study, we performed a systematic genome-wide in silico screen to search for novel small ncRNAs in the genome of Trypanosoma brucei using techniques of comparative genomics. Results In this study, we identified by comparative genomics, and validated by experimental analysis several novel ncRNAs that are conserved across multiple trypanosomatid genomes. When tested on known ncRNAs, our procedure was capable of finding almost half of the known repertoire through homology over six genomes, and about two-thirds of the known sequences were found in at least four genomes. After filtering, 72 conserved unannotated sequences in at least four genomes were found, 29 of which, ranging in size from 30 to 392 nts, were conserved in all six genomes. Fifty of the 72 candidates in the final set were chosen for experimental validation. Eighteen of the 50 (36%) were shown to be expressed, and for 11 of them a distinct expression product was detected, suggesting that they are short ncRNAs. Using functional experimental assays, five of the candidates were shown to be novel H/ACA and C/D snoRNAs; these included three sequences that appear as singletons in the genome, unlike previously identified snoRNA molecules that are found in clusters. The other candidates appear to be novel ncRNA molecules, and their function is, as yet, unknown. Conclusions Using comparative genomic techniques, we predicted 72 sequences as ncRNA candidates in T. brucei. The expression of 50 candidates was tested in laboratory experiments. This resulted in the discovery of 11 novel short ncRNAs in procyclic stage T. brucei, which have homologues in the other trypansomatids. A few of these molecules are snoRNAs, but most of them are novel ncRNA molecules. Based on this study, our analysis suggests that the total number of ncRNAs in trypanosomatids is in the range of several hundred.
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Affiliation(s)
- Tirza Doniger
- The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan 52900, Israel
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18
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Smith C, Heyne S, Richter AS, Will S, Backofen R. Freiburg RNA Tools: a web server integrating INTARNA, EXPARNA and LOCARNA. Nucleic Acids Res 2010; 38:W373-7. [PMID: 20444875 PMCID: PMC2896085 DOI: 10.1093/nar/gkq316] [Citation(s) in RCA: 184] [Impact Index Per Article: 13.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2010] [Revised: 03/31/2010] [Accepted: 04/17/2010] [Indexed: 12/05/2022] Open
Abstract
The Freiburg RNA tools web server integrates three tools for the advanced analysis of RNA in a common web-based user interface. The tools IntaRNA, ExpaRNA and LocARNA support the prediction of RNA-RNA interaction, exact RNA matching and alignment of RNA, respectively. The Freiburg RNA tools web server and the software packages of the stand-alone tools are freely accessible at http://rna.informatik.uni-freiburg.de.
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Affiliation(s)
- Cameron Smith
- Bioinformatics Group, University of Freiburg, Freiburg 79110, Germany and Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Steffen Heyne
- Bioinformatics Group, University of Freiburg, Freiburg 79110, Germany and Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Andreas S. Richter
- Bioinformatics Group, University of Freiburg, Freiburg 79110, Germany and Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Sebastian Will
- Bioinformatics Group, University of Freiburg, Freiburg 79110, Germany and Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Rolf Backofen
- Bioinformatics Group, University of Freiburg, Freiburg 79110, Germany and Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
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19
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Jung CH, Makunin IV, Mattick JS. Identification of conserved Drosophila-specific euchromatin-restricted non-coding sequence motifs. Genomics 2010; 96:154-66. [PMID: 20595017 DOI: 10.1016/j.ygeno.2010.05.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2010] [Revised: 05/25/2010] [Accepted: 05/26/2010] [Indexed: 01/19/2023]
Abstract
Non-protein-coding DNA comprises the majority of animal genomes but its functions are largely unknown. We identified over 17,000 different tetranucleotide pairs in the Drosophila melanogaster genome that are over-represented at distances up to 100nt in conserved non-exonic sequences. Those exhibiting the highest information content in surrounding nucleotides were classified into five groups: tRNAs, motifs associated with histone genes, Suppressor-of-Hairy-wing binding sites, and two sets of previously unrecognized motifs (DLM3 and DLM4). There are hundreds to thousands of copies of DLM3 and DLM4, respectively, in the genome, located almost exclusively in non-coding regions. They have similar copy numbers among drosophilids, but are largely absent in other insects. DLM3 is likely a cis-regulatory element, whereas DLM4 sequences are capable of forming a short hairpin structure and are expressed as approximately 80nt RNAs. This work reports the existence of Drosophila genus-specific sequence motifs, and suggests that many more novel functional elements may be discovered in genomes using the general approach outlined herein.
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Affiliation(s)
- Chol-Hee Jung
- Institute for Molecular Bioscience, The University of Queensland, St Lucia QLD, Australia
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20
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Menzel P, Gorodkin J, Stadler PF. The tedious task of finding homologous noncoding RNA genes. RNA (NEW YORK, N.Y.) 2009; 15:2075-82. [PMID: 19861422 PMCID: PMC2779685 DOI: 10.1261/rna.1556009] [Citation(s) in RCA: 38] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/28/2023]
Abstract
User-driven in silico RNA homology search is still a nontrivial task. In part, this is the consequence of a limited precision of the computational tools in spite of recent exciting progress in this area, and to a certain extent, computational costs are still problematic in practice. An important, and as we argue here, dominating issue is the dependence on good curated (secondary) structural alignments of the RNAs. These are often hard to obtain, not so much because of an inherent limitation in the available data, but because they require substantial manual curation, an effort that is rarely acknowledged. Here, we qualitatively describe a realistic scenario for what a "regular user" (i.e., a nonexpert in a particular RNA family) can do in practice, and what kind of results are likely to be achieved. Despite the indisputable advances in computational RNA biology, the conclusion is discouraging: BLAST still works better or equally good as other methods unless extensive expert knowledge on the RNA family is included. However, when good curated data are available the recent development yields further improvements in finding remote homologs. Homology search beyond the reach of BLAST hence is not at all a routine task.
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Affiliation(s)
- Peter Menzel
- Section for Genetics and Bioinformatics, IBHV, and Center for Applied Bioinformatics, University of Copenhagen, DK-1870 Frederiksberg, Denmark
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21
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Copeland CS, Marz M, Rose D, Hertel J, Brindley PJ, Santana CB, Kehr S, Attolini CSO, Stadler PF. Homology-based annotation of non-coding RNAs in the genomes of Schistosoma mansoni and Schistosoma japonicum. BMC Genomics 2009; 10:464. [PMID: 19814823 PMCID: PMC2770079 DOI: 10.1186/1471-2164-10-464] [Citation(s) in RCA: 48] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2009] [Accepted: 10/08/2009] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND Schistosomes are trematode parasites of the phylum Platyhelminthes. They are considered the most important of the human helminth parasites in terms of morbidity and mortality. Draft genome sequences are now available for Schistosoma mansoni and Schistosoma japonicum. Non-coding RNA (ncRNA) plays a crucial role in gene expression regulation, cellular function and defense, homeostasis, and pathogenesis. The genome-wide annotation of ncRNAs is a non-trivial task unless well-annotated genomes of closely related species are already available. RESULTS A homology search for structured ncRNA in the genome of S. mansoni resulted in 23 types of ncRNAs with conserved primary and secondary structure. Among these, we identified rRNA, snRNA, SL RNA, SRP, tRNAs and RNase P, and also possibly MRP and 7SK RNAs. In addition, we confirmed five miRNAs that have recently been reported in S. japonicum and found two additional homologs of known miRNAs. The tRNA complement of S. mansoni is comparable to that of the free-living planarian Schmidtea mediterranea, although for some amino acids differences of more than a factor of two are observed: Leu, Ser, and His are overrepresented, while Cys, Meth, and Ile are underrepresented in S. mansoni. On the other hand, the number of tRNAs in the genome of S. japonicum is reduced by more than a factor of four. Both schistosomes have a complete set of minor spliceosomal snRNAs. Several ncRNAs that are expected to exist in the S. mansoni genome were not found, among them the telomerase RNA, vault RNAs, and Y RNAs. CONCLUSION The ncRNA sequences and structures presented here represent the most complete dataset of ncRNA from any lophotrochozoan reported so far. This data set provides an important reference for further analysis of the genomes of schistosomes and indeed eukaryotic genomes at large.
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Affiliation(s)
- Claudia S Copeland
- Bioinformatics Group, Department of Computer Science and Interdisciplinary Center for Bioinformatics, University of Leipzig, Härtelstrasse 16-18, D-04107 Leipzig, Germany.
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22
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Bradley RK, Uzilov AV, Skinner ME, Bendaña YR, Barquist L, Holmes I. Evolutionary modeling and prediction of non-coding RNAs in Drosophila. PLoS One 2009; 4:e6478. [PMID: 19668382 PMCID: PMC2721679 DOI: 10.1371/journal.pone.0006478] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2009] [Accepted: 06/30/2009] [Indexed: 12/19/2022] Open
Abstract
We performed benchmarks of phylogenetic grammar-based ncRNA gene prediction, experimenting with eight different models of structural evolution and two different programs for genome alignment. We evaluated our models using alignments of twelve Drosophila genomes. We find that ncRNA prediction performance can vary greatly between different gene predictors and subfamilies of ncRNA gene. Our estimates for false positive rates are based on simulations which preserve local islands of conservation; using these simulations, we predict a higher rate of false positives than previous computational ncRNA screens have reported. Using one of the tested prediction grammars, we provide an updated set of ncRNA predictions for D. melanogaster and compare them to previously-published predictions and experimental data. Many of our predictions show correlations with protein-coding genes. We found significant depletion of intergenic predictions near the 3' end of coding regions and furthermore depletion of predictions in the first intron of protein-coding genes. Some of our predictions are colocated with larger putative unannotated genes: for example, 17 of our predictions showing homology to the RFAM family snoR28 appear in a tandem array on the X chromosome; the 4.5 Kbp spanned by the predicted tandem array is contained within a FlyBase-annotated cDNA.
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Affiliation(s)
- Robert K. Bradley
- Biophysics Graduate Group, University of California, Berkeley, California, United States of America
| | - Andrew V. Uzilov
- Department of Bioengineering, University of California, Berkeley, California, United States of America
| | - Mitchell E. Skinner
- Department of Bioengineering, University of California, Berkeley, California, United States of America
| | - Yuri R. Bendaña
- Department of Bioengineering, University of California, Berkeley, California, United States of America
| | - Lars Barquist
- Department of Bioengineering, University of California, Berkeley, California, United States of America
| | - Ian Holmes
- Biophysics Graduate Group, University of California, Berkeley, California, United States of America
- Department of Bioengineering, University of California, Berkeley, California, United States of America
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23
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Hertel J, de Jong D, Marz M, Rose D, Tafer H, Tanzer A, Schierwater B, Stadler PF. Non-coding RNA annotation of the genome of Trichoplax adhaerens. Nucleic Acids Res 2009; 37:1602-15. [PMID: 19151082 PMCID: PMC2655684 DOI: 10.1093/nar/gkn1084] [Citation(s) in RCA: 49] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2008] [Revised: 12/22/2008] [Accepted: 12/23/2008] [Indexed: 02/06/2023] Open
Abstract
A detailed annotation of non-protein coding RNAs is typically missing in initial releases of newly sequenced genomes. Here we report on a comprehensive ncRNA annotation of the genome of Trichoplax adhaerens, the presumably most basal metazoan whose genome has been published to-date. Since blast identified only a small fraction of the best-conserved ncRNAs--in particular rRNAs, tRNAs and some snRNAs--we developed a semi-global dynamic programming tool, GotohScan, to increase the sensitivity of the homology search. It successfully identified the full complement of major and minor spliceosomal snRNAs, the genes for RNase P and MRP RNAs, the SRP RNA, as well as several small nucleolar RNAs. We did not find any microRNA candidates homologous to known eumetazoan sequences. Interestingly, most ncRNAs, including the pol-III transcripts, appear as single-copy genes or with very small copy numbers in the Trichoplax genome.
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Affiliation(s)
- Jana Hertel
- Bioinformatics Group, Department of Computer Science, Interdisciplinary Center for Bioinformatics, University of Leipzig, Härtelstraβe 16-18, D-04107 Leipzig, Division of Ecology and Evolution, Institut für Tierökologie und Zellbiologie, Tierärztliche Hochschule Hannover, Bünteweg 17d, D-30559 Hannover, Germany, Department of Theoretical Chemistry, University of Vienna, Währingerstraβe 17, A-1090 Wien, Austria, Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT 06520, USA, RNomics Group, Fraunhofer Institut für Zelltherapie und Immunologie, Deutscher Platz 5e, D-04103 Leipzig, Germany and Santa Fe Institute, 1399 Hyde Park Rd., Santa Fe, NM 87501, USA
| | - Danielle de Jong
- Bioinformatics Group, Department of Computer Science, Interdisciplinary Center for Bioinformatics, University of Leipzig, Härtelstraβe 16-18, D-04107 Leipzig, Division of Ecology and Evolution, Institut für Tierökologie und Zellbiologie, Tierärztliche Hochschule Hannover, Bünteweg 17d, D-30559 Hannover, Germany, Department of Theoretical Chemistry, University of Vienna, Währingerstraβe 17, A-1090 Wien, Austria, Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT 06520, USA, RNomics Group, Fraunhofer Institut für Zelltherapie und Immunologie, Deutscher Platz 5e, D-04103 Leipzig, Germany and Santa Fe Institute, 1399 Hyde Park Rd., Santa Fe, NM 87501, USA
| | - Manja Marz
- Bioinformatics Group, Department of Computer Science, Interdisciplinary Center for Bioinformatics, University of Leipzig, Härtelstraβe 16-18, D-04107 Leipzig, Division of Ecology and Evolution, Institut für Tierökologie und Zellbiologie, Tierärztliche Hochschule Hannover, Bünteweg 17d, D-30559 Hannover, Germany, Department of Theoretical Chemistry, University of Vienna, Währingerstraβe 17, A-1090 Wien, Austria, Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT 06520, USA, RNomics Group, Fraunhofer Institut für Zelltherapie und Immunologie, Deutscher Platz 5e, D-04103 Leipzig, Germany and Santa Fe Institute, 1399 Hyde Park Rd., Santa Fe, NM 87501, USA
| | - Dominic Rose
- Bioinformatics Group, Department of Computer Science, Interdisciplinary Center for Bioinformatics, University of Leipzig, Härtelstraβe 16-18, D-04107 Leipzig, Division of Ecology and Evolution, Institut für Tierökologie und Zellbiologie, Tierärztliche Hochschule Hannover, Bünteweg 17d, D-30559 Hannover, Germany, Department of Theoretical Chemistry, University of Vienna, Währingerstraβe 17, A-1090 Wien, Austria, Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT 06520, USA, RNomics Group, Fraunhofer Institut für Zelltherapie und Immunologie, Deutscher Platz 5e, D-04103 Leipzig, Germany and Santa Fe Institute, 1399 Hyde Park Rd., Santa Fe, NM 87501, USA
| | - Hakim Tafer
- Bioinformatics Group, Department of Computer Science, Interdisciplinary Center for Bioinformatics, University of Leipzig, Härtelstraβe 16-18, D-04107 Leipzig, Division of Ecology and Evolution, Institut für Tierökologie und Zellbiologie, Tierärztliche Hochschule Hannover, Bünteweg 17d, D-30559 Hannover, Germany, Department of Theoretical Chemistry, University of Vienna, Währingerstraβe 17, A-1090 Wien, Austria, Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT 06520, USA, RNomics Group, Fraunhofer Institut für Zelltherapie und Immunologie, Deutscher Platz 5e, D-04103 Leipzig, Germany and Santa Fe Institute, 1399 Hyde Park Rd., Santa Fe, NM 87501, USA
| | - Andrea Tanzer
- Bioinformatics Group, Department of Computer Science, Interdisciplinary Center for Bioinformatics, University of Leipzig, Härtelstraβe 16-18, D-04107 Leipzig, Division of Ecology and Evolution, Institut für Tierökologie und Zellbiologie, Tierärztliche Hochschule Hannover, Bünteweg 17d, D-30559 Hannover, Germany, Department of Theoretical Chemistry, University of Vienna, Währingerstraβe 17, A-1090 Wien, Austria, Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT 06520, USA, RNomics Group, Fraunhofer Institut für Zelltherapie und Immunologie, Deutscher Platz 5e, D-04103 Leipzig, Germany and Santa Fe Institute, 1399 Hyde Park Rd., Santa Fe, NM 87501, USA
| | - Bernd Schierwater
- Bioinformatics Group, Department of Computer Science, Interdisciplinary Center for Bioinformatics, University of Leipzig, Härtelstraβe 16-18, D-04107 Leipzig, Division of Ecology and Evolution, Institut für Tierökologie und Zellbiologie, Tierärztliche Hochschule Hannover, Bünteweg 17d, D-30559 Hannover, Germany, Department of Theoretical Chemistry, University of Vienna, Währingerstraβe 17, A-1090 Wien, Austria, Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT 06520, USA, RNomics Group, Fraunhofer Institut für Zelltherapie und Immunologie, Deutscher Platz 5e, D-04103 Leipzig, Germany and Santa Fe Institute, 1399 Hyde Park Rd., Santa Fe, NM 87501, USA
| | - Peter F. Stadler
- Bioinformatics Group, Department of Computer Science, Interdisciplinary Center for Bioinformatics, University of Leipzig, Härtelstraβe 16-18, D-04107 Leipzig, Division of Ecology and Evolution, Institut für Tierökologie und Zellbiologie, Tierärztliche Hochschule Hannover, Bünteweg 17d, D-30559 Hannover, Germany, Department of Theoretical Chemistry, University of Vienna, Währingerstraβe 17, A-1090 Wien, Austria, Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT 06520, USA, RNomics Group, Fraunhofer Institut für Zelltherapie und Immunologie, Deutscher Platz 5e, D-04103 Leipzig, Germany and Santa Fe Institute, 1399 Hyde Park Rd., Santa Fe, NM 87501, USA
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Rose D, Jöris J, Hackermüller J, Reiche K, Li Q, Stadler PF. Duplicated RNA genes in teleost fish genomes. J Bioinform Comput Biol 2009; 6:1157-75. [PMID: 19090022 DOI: 10.1142/s0219720008003886] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2007] [Revised: 06/17/2008] [Accepted: 06/18/2008] [Indexed: 12/29/2022]
Abstract
Teleost fishes share a duplication of their entire genomes. We report here on a computational survey of structured non-coding RNAs (ncRNAs) in teleost genomes, focusing on the fate of fish-specific duplicates. As in other metazoan groups, we find evidence of a large number (11,543) of structured RNAs, most of which (~86%) are clade-specific or evolve so fast that their tetrapod homologs cannot be detected. In surprising contrast to protein-coding genes, the fish-specific genome duplication did not lead to a large number of paralogous ncRNAs: only 188 candidates, mostly microRNAs, appear in a larger copy number in teleosts than in tetrapods, suggesting that large-scale gene duplications do not play a major role in the expansion of the vertebrate ncRNA inventory.
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Affiliation(s)
- Dominic Rose
- Bioinformatics Group, Department of Computer Science, Interdisciplinary Center for Bioinformatics, University of Leipzig, Leipzig, Germany.
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25
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Mendes ND, Freitas AT, Sagot MF. Current tools for the identification of miRNA genes and their targets. Nucleic Acids Res 2009; 37:2419-33. [PMID: 19295136 PMCID: PMC2677885 DOI: 10.1093/nar/gkp145] [Citation(s) in RCA: 160] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
The discovery of microRNAs (miRNAs), almost 10 years ago, changed dramatically our perspective on eukaryotic gene expression regulation. However, the broad and important functions of these regulators are only now becoming apparent. The expansion of our catalogue of miRNA genes and the identification of the genes they regulate owe much to the development of sophisticated computational tools that have helped either to focus or interpret experimental assays. In this article, we review the methods for miRNA gene finding and target identification that have been proposed in the last few years. We identify some problems that current approaches have not yet been able to overcome and we offer some perspectives on the next generation of computational methods.
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Affiliation(s)
- N D Mendes
- Equipe BAOBAB, Laboratoire de Biométrie et Biologie Evolutive (UMR 5558), CNRS, Univ. Lyon 1, 43 bd du 11 nov 1918, 69622, Villeurbanne Cedex, France.
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26
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Taneda A. An efficient genetic algorithm for structural RNA pairwise alignment and its application to non-coding RNA discovery in yeast. BMC Bioinformatics 2008; 9:521. [PMID: 19061486 PMCID: PMC2630964 DOI: 10.1186/1471-2105-9-521] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2008] [Accepted: 12/05/2008] [Indexed: 11/30/2022] Open
Abstract
Background Aligning RNA sequences with low sequence identity has been a challenging problem since such a computation essentially needs an algorithm with high complexities for taking structural conservation into account. Although many sophisticated algorithms for the purpose have been proposed to date, further improvement in efficiency is necessary to accelerate its large-scale applications including non-coding RNA (ncRNA) discovery. Results We developed a new genetic algorithm, Cofolga2, for simultaneously computing pairwise RNA sequence alignment and consensus folding, and benchmarked it using BRAliBase 2.1. The benchmark results showed that our new algorithm is accurate and efficient in both time and memory usage. Then, combining with the originally trained SVM, we applied the new algorithm to novel ncRNA discovery where we compared S. cerevisiae genome with six related genomes in a pairwise manner. By focusing our search to the relatively short regions (50 bp to 2,000 bp) sandwiched by conserved sequences, we successfully predict 714 intergenic and 1,311 sense or antisense ncRNA candidates, which were found in the pairwise alignments with stable consensus secondary structure and low sequence identity (≤ 50%). By comparing with the previous predictions, we found that > 92% of the candidates is novel candidates. The estimated rate of false positives in the predicted candidates is 51%. Twenty-five percent of the intergenic candidates has supports for expression in cell, i.e. their genomic positions overlap those of the experimentally determined transcripts in literature. By manual inspection of the results, moreover, we obtained four multiple alignments with low sequence identity which reveal consensus structures shared by three species/sequences. Conclusion The present method gives an efficient tool complementary to sequence-alignment-based ncRNA finders.
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Affiliation(s)
- Akito Taneda
- Graduate School of Science and Technology, Hirosaki University, Hirosaki, Japan.
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Bradley RK, Pachter L, Holmes I. Specific alignment of structured RNA: stochastic grammars and sequence annealing. ACTA ACUST UNITED AC 2008; 24:2677-83. [PMID: 18796475 DOI: 10.1093/bioinformatics/btn495] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
MOTIVATION Whole-genome screens suggest that eukaryotic genomes are dense with non-coding RNAs (ncRNAs). We introduce a novel approach to RNA multiple alignment which couples a generative probabilistic model of sequence and structure with an efficient sequence annealing approach for exploring the space of multiple alignments. This leads to a new software program, Stemloc-AMA, that is both accurate and specific in the alignment of multiple related RNA sequences. RESULTS When tested on the benchmark datasets BRalibase II and BRalibase 2.1, Stemloc-AMA has comparable sensitivity to and better specificity than the best competing methods. We use a large-scale random sequence experiment to show that while most alignment programs maximize sensitivity at the expense of specificity, even to the point of giving complete alignments of non-homologous sequences, Stemloc-AMA aligns only sequences with detectable homology and leaves unrelated sequences largely unaligned. Such accurate and specific alignments are crucial for comparative-genomics analysis, from inferring phylogeny to estimating substitution rates across different lineages. AVAILABILITY Stemloc-AMA is available from http://biowiki.org/StemLocAMA as part of the dart software package for sequence analysis.
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Affiliation(s)
- Robert K Bradley
- Biophysics Graduate Group, Department of Mathematics and Department of Bioengineering, University of California, Berkeley, CA 94720, USA
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28
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Gruber AR, Kilgus C, Mosig A, Hofacker IL, Hennig W, Stadler PF. Arthropod 7SK RNA. Mol Biol Evol 2008; 25:1923-30. [PMID: 18566019 DOI: 10.1093/molbev/msn140] [Citation(s) in RCA: 37] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
The 7SK small nuclear RNA (snRNA) is a key player in the regulation of polymerase (pol) II transcription. The 7SK RNA was long believed to be specific to vertebrates where it is highly conserved. Homologs in basal deuterostomes and a few lophotrochozoan species were only recently reported. On longer timescales, 7SK evolves rapidly with only few conserved sequence and structure motifs. Previous attempts to identify the Drosophila homolog thus have remained unsuccessful despite considerable efforts. Here we report on the discovery of arthropod 7SK RNAs using a novel search strategy based on pol III promoters, as well as the subsequent verification of its expression. Our results demonstrate that a 7SK snRNA featuring 2 highly structured conserved domains was present already in the bilaterian ancestor.
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Affiliation(s)
- Andreas R Gruber
- Institute for Theoretical Chemistry, University of Vienna, Vienna, Austria.
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29
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Rose D, Hertel J, Reiche K, Stadler PF, Hackermüller J. NcDNAlign: plausible multiple alignments of non-protein-coding genomic sequences. Genomics 2008; 92:65-74. [PMID: 18511233 DOI: 10.1016/j.ygeno.2008.04.003] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2007] [Revised: 04/09/2008] [Accepted: 04/09/2008] [Indexed: 10/22/2022]
Abstract
Genome-wide multiple sequence alignments (MSAs) are a necessary prerequisite for an increasingly diverse collection of comparative genomic approaches. Here we present a versatile method that generates high-quality MSAs for non-protein-coding sequences. The NcDNAlign pipeline combines pairwise BLAST alignments to create initial MSAs, which are then locally improved and trimmed. The program is optimized for speed and hence is particulary well-suited to pilot studies. We demonstrate the practical use of NcDNAlign in three case studies: the search for ncRNAs in gammaproteobacteria and the analysis of conserved noncoding DNA in nematodes and teleost fish, in the latter case focusing on the fate of duplicated ultra-conserved regions. Compared to the currently widely used genome-wide alignment program TBA, our program results in a 20- to 30-fold reduction of CPU time necessary to generate gammaproteobacterial alignments. A showcase application of bacterial ncRNA prediction based on alignments of both algorithms results in similar sensitivity, false discovery rates, and up to 100 putatively novel ncRNA structures. Similar findings hold for our application of NcDNAlign to the identification of ultra-conserved regions in nematodes and teleosts. Both approaches yield conserved sequences of unknown function, result in novel evolutionary insights into conservation patterns among these genomes, and manifest the benefits of an efficient and reliable genome-wide alignment package. The software is available under the GNU Public License at http://www.bioinf.uni-leipzig.de/Software/NcDNAlign/.
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Affiliation(s)
- Dominic Rose
- Bioinformatics Group, Department of Computer Science, University of Leipzig, Härtelstrasse 16-18, D-04107 Leipzig, Germany
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30
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Gesell T, Washietl S. Dinucleotide controlled null models for comparative RNA gene prediction. BMC Bioinformatics 2008; 9:248. [PMID: 18505553 PMCID: PMC2453142 DOI: 10.1186/1471-2105-9-248] [Citation(s) in RCA: 47] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2008] [Accepted: 05/27/2008] [Indexed: 11/15/2022] Open
Abstract
Background Comparative prediction of RNA structures can be used to identify functional noncoding RNAs in genomic screens. It was shown recently by Babak et al. [BMC Bioinformatics. 8:33] that RNA gene prediction programs can be biased by the genomic dinucleotide content, in particular those programs using a thermodynamic folding model including stacking energies. As a consequence, there is need for dinucleotide-preserving control strategies to assess the significance of such predictions. While there have been randomization algorithms for single sequences for many years, the problem has remained challenging for multiple alignments and there is currently no algorithm available. Results We present a program called SISSIz that simulates multiple alignments of a given average dinucleotide content. Meeting additional requirements of an accurate null model, the randomized alignments are on average of the same sequence diversity and preserve local conservation and gap patterns. We make use of a phylogenetic substitution model that includes overlapping dependencies and site-specific rates. Using fast heuristics and a distance based approach, a tree is estimated under this model which is used to guide the simulations. The new algorithm is tested on vertebrate genomic alignments and the effect on RNA structure predictions is studied. In addition, we directly combined the new null model with the RNAalifold consensus folding algorithm giving a new variant of a thermodynamic structure based RNA gene finding program that is not biased by the dinucleotide content. Conclusion SISSIz implements an efficient algorithm to randomize multiple alignments preserving dinucleotide content. It can be used to get more accurate estimates of false positive rates of existing programs, to produce negative controls for the training of machine learning based programs, or as standalone RNA gene finding program. Other applications in comparative genomics that require randomization of multiple alignments can be considered. Availability SISSIz is available as open source C code that can be compiled for every major platform and downloaded here: .
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Affiliation(s)
- Tanja Gesell
- Center for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, Dr. Bohr-Gasse 9, A-1030 Vienna, Austria.
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31
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Gruber AR, Bernhart SH, Hofacker IL, Washietl S. Strategies for measuring evolutionary conservation of RNA secondary structures. BMC Bioinformatics 2008; 9:122. [PMID: 18302738 PMCID: PMC2335298 DOI: 10.1186/1471-2105-9-122] [Citation(s) in RCA: 50] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2007] [Accepted: 02/26/2008] [Indexed: 02/01/2023] Open
Abstract
Background Evolutionary conservation of RNA secondary structure is a typical feature of many functional non-coding RNAs. Since almost all of the available methods used for prediction and annotation of non-coding RNA genes rely on this evolutionary signature, accurate measures for structural conservation are essential. Results We systematically assessed the ability of various measures to detect conserved RNA structures in multiple sequence alignments. We tested three existing and eight novel strategies that are based on metrics of folding energies, metrics of single optimal structure predictions, and metrics of structure ensembles. We find that the folding energy based SCI score used in the RNAz program and a simple base-pair distance metric are by far the most accurate. The use of more complex metrics like for example tree editing does not improve performance. A variant of the SCI performed particularly well on highly conserved alignments and is thus a viable alternative when only little evolutionary information is available. Surprisingly, ensemble based methods that, in principle, could benefit from the additional information contained in sub-optimal structures, perform particularly poorly. As a general trend, we observed that methods that include a consensus structure prediction outperformed equivalent methods that only consider pairwise comparisons. Conclusion Structural conservation can be measured accurately with relatively simple and intuitive metrics. They have the potential to form the basis of future RNA gene finders, that face new challenges like finding lineage specific structures or detecting mis-aligned sequences.
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Affiliation(s)
- Andreas R Gruber
- Institute for Theoretical Chemistry, University of Vienna, Währingerstrasse 17, 1090 Wien, Austria.
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Seemann SE, Gilchrist MJ, Hofacker IL, Stadler PF, Gorodkin J. Detection of RNA structures in porcine EST data and related mammals. BMC Genomics 2007; 8:316. [PMID: 17845718 PMCID: PMC2072958 DOI: 10.1186/1471-2164-8-316] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2007] [Accepted: 09/10/2007] [Indexed: 11/18/2022] Open
Abstract
Background Non-coding RNAs (ncRNAs) are involved in a wide spectrum of regulatory functions. Within recent years, there have been increasing reports of observed polyadenylated ncRNAs and mRNA like ncRNAs in eukaryotes. To investigate this further, we examined the large data set in the Sino-Danish PigEST resource which also contains expression information distributed on 97 non-normalized cDNA libraries. Results We constructed a pipeline, EST2ncRNA, to search for known and novel ncRNAs. The pipeline utilises sequence similarity to ncRNA databases (blast), structure similarity to Rfam (RaveNnA) as well as multiple alignments to predict conserved novel putative RNA structures (RNAz). EST2ncRNA was fed with 48,000 contigs and 73,000 singletons available from the PigEST resource. Using the pipeline we identified known RNA structures in 137 contigs and single reads (conreads), and predicted high confidence RNA structures in non-protein coding regions of additional 1,262 conreads. Of these, structures in 270 conreads overlap with existing predictions in human. To sum up, the PigEST resource comprises trans-acting elements (ncRNAs) in 715 contigs and 340 singletons as well as cis-acting elements (inside UTRs) in 311 contigs and 51 singletons, of which 18 conreads contain both predictions of trans- and cis-acting elements. The predicted RNAz candidates were compared with the PigEST expression information and we identify 114 contigs with an RNAz prediction and expression in at least ten of the non-normalised cDNA libraries. We conclude that the contigs with RNAz and known predictions are in general expressed at a much lower level than protein coding transcripts. In addition, we also observe that our ncRNA candidates constitute about one to two percent of the genes expressed in the cDNA libraries. Intriguingly, the cDNA libraries from developmental (brain) tissues contain the highest amount of ncRNA candidates, about two percent. These observations are related to existing knowledge and hypotheses about the role of ncRNAs in higher organisms. Furthermore, about 80% porcine coding transcripts (of 18,600 identified) as well as less than one-third ORF-free transcripts are conserved at least in the closely related bovine genome. Approximately one percent of the coding and 10% of the remaining matches are unique between the PigEST data and cow genome. Based on the pig-cow alignments, we searched for similarities to 16 other organisms by UCSC available alignments, which resulted in a 87% coverage by the human genome for instance. Conclusion Besides recovering several of the already annotated functional RNA structures, we predicted a large number of high confidence conserved secondary structures in polyadenylated porcine transcripts. Our observations of relatively low expression levels of predicted ncRNA candidates together with the observations of higher relative amount in cDNA libraries from developmental stages are in agreement with the current paradigm of ncRNA roles in higher organisms and supports the idea of polyadenylated ncRNAs.
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Affiliation(s)
- Stefan E Seemann
- Division of Genetics and Bioinformatics, IBHV, University of Copenhagen, Grønnegårdsvej 3, DK-1870 Frederiksberg, Denmark
- Bioinformatics Group, Department of Computer Science, University of Leipzig, Germany
| | - Michael J Gilchrist
- The Wellcome Trust/Cancer Research UK Gurdon Institute, Cambridge, CB2 1QN, UK
| | - Ivo L Hofacker
- Institute for Theoretical Chemistry and Structural Biology, University of Vienna, Austria
| | - Peter F Stadler
- Bioinformatics Group, Department of Computer Science, University of Leipzig, Germany
- Institute for Theoretical Chemistry and Structural Biology, University of Vienna, Austria
| | - Jan Gorodkin
- Division of Genetics and Bioinformatics, IBHV, University of Copenhagen, Grønnegårdsvej 3, DK-1870 Frederiksberg, Denmark
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Reiche K, Stadler PF. RNAstrand: reading direction of structured RNAs in multiple sequence alignments. Algorithms Mol Biol 2007; 2:6. [PMID: 17540014 PMCID: PMC1892782 DOI: 10.1186/1748-7188-2-6] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2007] [Accepted: 05/31/2007] [Indexed: 11/10/2022] Open
Abstract
MOTIVATION Genome-wide screens for structured ncRNA genes in mammals, urochordates, and nematodes have predicted thousands of putative ncRNA genes and other structured RNA motifs. A prerequisite for their functional annotation is to determine the reading direction with high precision. RESULTS While folding energies of an RNA and its reverse complement are similar, the differences are sufficient at least in conjunction with substitution patterns to discriminate between structured RNAs and their complements. We present here a support vector machine that reliably classifies the reading direction of a structured RNA from a multiple sequence alignment and provides a considerable improvement in classification accuracy over previous approaches. SOFTWARE RNAstrand is freely available as a stand-alone tool from http://www.bioinf.uni-leipzig.de/Software/RNAstrand and is also included in the latest release of RNAz, a part of the Vienna RNA Package.
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Affiliation(s)
- Kristin Reiche
- Bioinformatics Group, Dept. of Computer Science, and Interdisciplinary Center for Bioinformatics, University of Leipzig, Härtelstraße 16-18, D-04107 Leipzig, Germany
| | - Peter F Stadler
- Bioinformatics Group, Dept. of Computer Science, and Interdisciplinary Center for Bioinformatics, University of Leipzig, Härtelstraße 16-18, D-04107 Leipzig, Germany
- Institute for Theoretical Chemistry, University of Vienna, Währingerstraße 17, A-1090 Wien, Austria
- Santa Fe Institute, 1399 Hyde Park Rd., Santa Fe, NM 87501, USA
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