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      • Record: found
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      Transient RNA structure features are evolutionarily conserved and can be computationally predicted

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          Abstract

          Functional RNA structures tend to be conserved during evolution. This finding is, for example, exploited by comparative methods for RNA secondary structure prediction that currently provide the state-of-art in terms of prediction accuracy. We here provide strong evidence that homologous RNA genes not only fold into similar final RNA structures, but that their folding pathways also share common transient structural features that have been evolutionarily conserved. For this, we compile and investigate a non-redundant data set of 32 sequences with known transient and final RNA secondary structures and devise a dedicated computational analysis pipeline.

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          Most cited references72

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          Database resources of the National Center for Biotechnology Information

          Eric Sayers, Tanya Barrett, Dennis A Benson … (2011)
          In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI Website. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central (PMC), Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Primer-BLAST, COBALT, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, dbVar, Epigenomics, Genome and related tools, the Map Viewer, Model Maker, Evidence Viewer, Trace Archive, Sequence Read Archive, BioProject, BioSample, Retroviral Genotyping Tools, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus (GEO), Probe, Online Mendelian Inheritance in Animals (OMIA), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD), the Conserved Domain Architecture Retrieval Tool (CDART), Biosystems, Protein Clusters and the PubChem suite of small molecule databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of these resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov.
          Article 0 comments Cited 236 times – based on 0 reviews     Review now
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            The eukaryotic genome as an RNA machine.

            Paulo P. Amaral, Marcel E Dinger, Tim Mercer … (2008)
            The past few years have revealed that the genomes of all studied eukaryotes are almost entirely transcribed, generating an enormous number of non-protein-coding RNAs (ncRNAs). In parallel, it is increasingly evident that many of these RNAs have regulatory functions. Here, we highlight recent advances that illustrate the diversity of ncRNA control of genome dynamics, cell biology, and developmental programming.
            Article 0 comments Cited 200 times – based on 0 reviews     Review now
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              A statistical sampling algorithm for RNA secondary structure prediction.

              Y. Ding (2003)
              An RNA molecule, particularly a long-chain mRNA, may exist as a population of structures. Further more, multiple structures have been demonstrated to play important functional roles. Thus, a representation of the ensemble of probable structures is of interest. We present a statistical algorithm to sample rigorously and exactly from the Boltzmann ensemble of secondary structures. The forward step of the algorithm computes the equilibrium partition functions of RNA secondary structures with recent thermodynamic parameters. Using conditional probabilities computed with the partition functions in a recursive sampling process, the backward step of the algorithm quickly generates a statistically representative sample of structures. With cubic run time for the forward step, quadratic run time in the worst case for the sampling step, and quadratic storage, the algorithm is efficient for broad applicability. We demonstrate that, by classifying sampled structures, the algorithm enables a statistical delineation and representation of the Boltzmann ensemble. Applications of the algorithm show that alternative biological structures are revealed through sampling. Statistical sampling provides a means to estimate the probability of any structural motif, with or without constraints. For example, the algorithm enables probability profiling of single-stranded regions in RNA secondary structure. Probability profiling for specific loop types is also illustrated. By overlaying probability profiles, a mutual accessibility plot can be displayed for predicting RNA:RNA interactions. Boltzmann probability-weighted density of states and free energy distributions of sampled structures can be readily computed. We show that a sample of moderate size from the ensemble of an enormous number of possible structures is sufficient to guarantee statistical reproducibility in the estimates of typical sampling statistics. Our applications suggest that the sampling algorithm may be well suited to prediction of mRNA structure and target accessibility. The algorithm is applicable to the rational design of small interfering RNAs (siRNAs), antisense oligonucleotides, and trans-cleaving ribozymes in gene knock-down studies.
              Article 0 comments Cited 191 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Journal ID (nlm-ta): Nucleic Acids Res
                Journal ID (iso-abbrev): Nucleic Acids Res
                Journal ID (publisher-id): nar
                Journal ID (hwp): nar
                Title: Nucleic Acids Research
                Publisher: Oxford University Press
                ISSN (Print): 0305-1048
                ISSN (Electronic): 1362-4962
                Publication date (Print): July 2013
                Publication date (Electronic): 26 April 2013
                Publication date PMC-release: 26 April 2013
                Volume: 41
                Issue: 12
                Pages: 6273-6285
                Affiliations
                1Centre for High-Throughput Biology, University of British Columbia, 2125 East Mall, Vancouver, British Columbia V6T 1Z4, Canada, 2Department of Computer Science, University of British Columbia, 2125 East Mall, Vancouver, British Columbia V6T 1Z4, Canada and 3Department of Medical Genetics, University of British Columbia, 2125 East Mall, Vancouver, British Columbia V6T 1Z4, Canada
                Author notes
                *To whom correspondence should be addressed. Tel: +1 604 827 4232; Fax: +1 604 822 9126; Email: irmtraud.meyer@ 123456cantab.net

                The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors.

                Article
                Publisher ID: gkt319
                DOI: 10.1093/nar/gkt319
                PMC ID: 3695514
                PubMed ID: 23625966
                SO-VID: eff70334-01e3-4937-bdf1-e2dfaf02e43c
                Copyright © © The Author(s) 2013. Published by Oxford University Press.
                License:

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/3.0/), 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@oup.com

                History
                Date received : 30 November 2012
                Date revision received : 25 March 2013
                Date accepted : 5 April 2013
                Page count
                Pages: 13
                Categories
                Subject: RNA
                Custom metadata
                cover-date 8 July 2013

                ScienceOpen disciplines: Genetics
                Data availability:
                ScienceOpen disciplines: Genetics

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