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      Detection of 224 candidate structured RNAs by comparative analysis of specific subsets of intergenic regions

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          Abstract

          The discovery of structured non-coding RNAs (ncRNAs) in bacteria can reveal new facets of biology and biochemistry. Comparative genomics analyses executed by powerful computer algorithms have successfully been used to uncover many novel bacterial ncRNA classes in recent years. However, this general search strategy favors the discovery of more common ncRNA classes, whereas progressively rarer classes are correspondingly more difficult to identify. In the current study, we confront this problem by devising several methods to select subsets of intergenic regions that can concentrate these rare RNA classes, thereby increasing the probability that comparative sequence analysis approaches will reveal their existence. By implementing these methods, we discovered 224 novel ncRNA classes, which include ROOL RNA, an RNA class averaging 581 nt and present in multiple phyla, several highly conserved and widespread ncRNA classes with properties that suggest sophisticated biochemical functions and a multitude of putative cis-regulatory RNA classes involved in a variety of biological processes. We expect that further research on these newly found RNA classes will reveal additional aspects of novel biology, and allow for greater insights into the biochemistry performed by ncRNAs.

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          Most cited references51

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          LIBSVM: A library for support vector machines

          LIBSVM is a library for Support Vector Machines (SVMs). We have been actively developing this package since the year 2000. The goal is to help users to easily apply SVM to their applications. LIBSVM has gained wide popularity in machine learning and many other areas. In this article, we present all implementation details of LIBSVM. Issues such as solving SVM optimization problems theoretical convergence multiclass classification probability estimates and parameter selection are discussed in detail.
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            Fast and reliable prediction of noncoding RNAs.

            We report an efficient method for detecting functional RNAs. The approach, which combines comparative sequence analysis and structure prediction, already has yielded excellent results for a small number of aligned sequences and is suitable for large-scale genomic screens. It consists of two basic components: (i) a measure for RNA secondary structure conservation based on computing a consensus secondary structure, and (ii) a measure for thermodynamic stability, which, in the spirit of a z score, is normalized with respect to both sequence length and base composition but can be calculated without sampling from shuffled sequences. Functional RNA secondary structures can be identified in multiple sequence alignments with high sensitivity and high specificity. We demonstrate that this approach is not only much more accurate than previous methods but also significantly faster. The method is implemented in the program rnaz, which can be downloaded from www.tbi.univie.ac.at/~wash/RNAz. We screened all alignments of length n > or = 50 in the Comparative Regulatory Genomics database, which compiles conserved noncoding elements in upstream regions of orthologous genes from human, mouse, rat, Fugu, and zebrafish. We recovered all of the known noncoding RNAs and cis-acting elements with high significance and found compelling evidence for many other conserved RNA secondary structures not described so far to our knowledge.
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              INTEGRALL: a database and search engine for integrons, integrases and gene cassettes.

              INTEGRALL is a freely available, text-based search system developed with the aim of collecting and organizing information on integrons in a single database. The current release (1.2) contains more than 4800 integron sequences and provides a public genetic repository for sequence data and nomenclature, offering scientists an easy and interactive access to integron's DNA sequences, their molecular arrangements as well as their genetic contexts.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                13 October 2017
                10 August 2017
                10 August 2017
                : 45
                : 18
                : 10811-10823
                Affiliations
                [1 ]HHMI, Yale University, Box 208103, New Haven, CT 06520-8103, USA
                [2 ]Department of Molecular, Cellular and Developmental Biology, Yale University, Box 208103, New Haven, CT 06520-8103, USA
                [3 ]Department of Molecular Biophysics and Biochemistry, Yale University, Box 208103, New Haven, CT 06520-8103, USA
                Author notes
                [* ]To whom correspondence should be addressed. Tel: +49 341 97 16657; Fax: +49 341 97 16679; Email: zasha@ 123456bioinf.uni-leipzig.de . Correspondence may also be addressed to Ronald R. Breaker. Tel: +1 203 432 9389; Fax: +1 203 432 6161; Email: ronald.breaker@ 123456yale.edu
                Author information
                http://orcid.org/0000-0002-6681-3624
                Article
                gkx699
                10.1093/nar/gkx699
                5737381
                28977401
                bd84df5b-7e0f-4455-80d1-ed7c1b9ece34
                © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@ 123456oup.com

                History
                : 02 August 2017
                : 26 July 2017
                : 11 April 2017
                Page count
                Pages: 13
                Categories
                RNA and RNA-protein complexes

                Genetics
                Genetics

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