1
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Voß B. Classified Dynamic Programming in RNA Structure Analysis. Methods Mol Biol 2024; 2726:125-141. [PMID: 38780730 DOI: 10.1007/978-1-0716-3519-3_6] [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: 05/25/2024]
Abstract
Analysis of the folding space of RNA generally suffers from its exponential size. With classified Dynamic Programming algorithms, it is possible to alleviate this burden and to analyse the folding space of RNA in great depth. Key to classified DP is that the search space is partitioned into classes based on an on-the-fly computed feature. A class-wise evaluation is then used to compute class-wide properties, such as the lowest free energy structure for each class, or aggregate properties, such as the class' probability. In this paper we describe the well-known shape and hishape abstraction of RNA structures, their power to help better understand RNA function and related methods that are based on these abstractions.
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Affiliation(s)
- Björn Voß
- RNA Biology and Bioinformatics, Institute of Biomedical Genetics, University of Stuttgart, Stuttgart, Germany
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2
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Dykeman EC. Modelling ribosome kinetics and translational control on dynamic mRNA. PLoS Comput Biol 2023; 19:e1010870. [PMID: 36689464 PMCID: PMC9894550 DOI: 10.1371/journal.pcbi.1010870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 02/02/2023] [Accepted: 01/10/2023] [Indexed: 01/24/2023] Open
Abstract
The control of protein synthesis and the overall levels of various proteins in the cell is critical for achieving homoeostasis. Regulation of protein levels can occur at the transcriptional level, where the total number of messenger RNAs in the overall transcriptome are controlled, or at the translational level, where interactions of proteins and ribosomes with the messenger RNA determine protein translational efficiency. Although transcriptional control of mRNA levels is the most commonly used regulatory control mechanism in cells, positive-sense single-stranded RNA viruses often utilise translational control mechanisms to regulate their proteins in the host cell. Here I detail a computational method for stochastically simulating protein synthesis on a dynamic messenger RNA using the Gillespie algorithm, where the mRNA is allowed to co-translationally fold in response to ribosome movement. Applying the model to the test case of the bacteriophage MS2 virus, I show that the models ability to accurately reproduce experimental measurements of coat protein production and translational repression of the viral RNA dependant RNA polymerase at high coat protein concentrations. The computational techniques reported here open up the potential to examine the infection dynamics of a ssRNA virus in a host cell at the level of the genomic RNA, as well as examine general translation control mechanisms present in polycistronic mRNAs.
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Affiliation(s)
- Eric C. Dykeman
- Department of Mathematics, University of York, York, United Kingdom
- * E-mail:
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3
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Badelt S, Lorenz R, Hofacker IL. DrTransformer: heuristic cotranscriptional RNA folding using the nearest neighbor energy model. Bioinformatics 2023; 39:6992659. [PMID: 36655786 PMCID: PMC9889959 DOI: 10.1093/bioinformatics/btad034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 12/16/2022] [Accepted: 01/17/2023] [Indexed: 01/20/2023] Open
Abstract
MOTIVATION Folding during transcription can have an important influence on the structure and function of RNA molecules, as regions closer to the 5' end can fold into metastable structures before potentially stronger interactions with the 3' end become available. Thermodynamic RNA folding models are not suitable to predict structures that result from cotranscriptional folding, as they can only calculate properties of the equilibrium distribution. Other software packages that simulate the kinetic process of RNA folding during transcription exist, but they are mostly applicable for short sequences. RESULTS We present a new algorithm that tracks changes to the RNA secondary structure ensemble during transcription. At every transcription step, new representative local minima are identified, a neighborhood relation is defined and transition rates are estimated for kinetic simulations. After every simulation, a part of the ensemble is removed and the remainder is used to search for new representative structures. The presented algorithm is deterministic (up to numeric instabilities of simulations), fast (in comparison with existing methods), and it is capable of folding RNAs much longer than 200 nucleotides. AVAILABILITY AND IMPLEMENTATION This software is open-source and available at https://github.com/ViennaRNA/drtransformer. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
| | - Ronny Lorenz
- Department of Theoretical Chemistry, University of Vienna, Vienna, Austria
| | - Ivo L Hofacker
- Department of Theoretical Chemistry, University of Vienna, Vienna, Austria,Research Group Bioinformatics and Computational Biology, Faculty of Computer Science, University of Vienna, Vienna, Austria
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4
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Binet T, Avalle B, Dávila Felipe M, Maffucci I. AptaMat: a matrix-based algorithm to compare single-stranded oligonucleotides secondary structures. Bioinformatics 2022; 39:6849515. [PMID: 36440922 PMCID: PMC9805580 DOI: 10.1093/bioinformatics/btac752] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 11/14/2022] [Accepted: 11/24/2022] [Indexed: 11/30/2022] Open
Abstract
MOTIVATION Comparing single-stranded nucleic acids (ssNAs) secondary structures is fundamental when investigating their function and evolution and predicting the effect of mutations on their structures. Many comparison metrics exist, although they are either too elaborate or not sensitive enough to distinguish close ssNAs structures. RESULTS In this context, we developed AptaMat, a simple and sensitive algorithm for ssNAs secondary structures comparison based on matrices representing the ssNAs secondary structures and a metric built upon the Manhattan distance in the plane. We applied AptaMat to several examples and compared the results to those obtained by the most frequently used metrics, namely the Hamming distance and the RNAdistance, and by a recently developed image-based approach. We showed that AptaMat is able to discriminate between similar sequences, outperforming all the other here considered metrics. In addition, we showed that AptaMat was able to correctly classify 14 RFAM families within a clustering procedure. AVAILABILITY AND IMPLEMENTATION The python code for AptaMat is available at https://github.com/GEC-git/AptaMat.git. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Thomas Binet
- Université de technologie de Compiègne, UPJV, CNRS, Enzyme and Cell Engineering, Centre de recherche Royallieu, CS 60 319 - 60 203, Compiègne Cedex, France
| | - Bérangère Avalle
- Université de technologie de Compiègne, UPJV, CNRS, Enzyme and Cell Engineering, Centre de recherche Royallieu, CS 60 319 - 60 203, Compiègne Cedex, France
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5
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Hohmann KF, Blümler A, Heckel A, Fürtig B. The RNA chaperone StpA enables fast RNA refolding by destabilization of mutually exclusive base pairs within competing secondary structure elements. Nucleic Acids Res 2021; 49:11337-11349. [PMID: 34614185 PMCID: PMC8565331 DOI: 10.1093/nar/gkab876] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Revised: 09/13/2021] [Accepted: 09/17/2021] [Indexed: 11/14/2022] Open
Abstract
In bacteria RNA gene regulatory elements refold dependent on environmental clues between two or more long-lived conformational states each associated with a distinct regulatory state. The refolding kinetics are strongly temperature-dependent and especially at lower temperatures they reach timescales that are biologically not accessible. To overcome this problem, RNA chaperones have evolved. However, the precise molecular mechanism of how these proteins accelerate RNA refolding reactions remains enigmatic. Here we show how the RNA chaperone StpA of Escherichia coli leads to an acceleration of a bistable RNA's refolding kinetics through the selective destabilization of key base pairing interactions. We find in laser assisted real-time NMR experiments on photocaged bistable RNAs that the RNA chaperone leads to a two-fold increase in refolding rates at low temperatures due to reduced stability of ground state conformations. Further, we can show that upon interaction with StpA, base pairing interactions in the bistable RNA are modulated to favor refolding through the dominant pseudoknotted transition pathway. Our results shed light on the molecular mechanism of the interaction between RNA chaperones and bistable RNAs and are the first step into a functional classification of chaperones dependent on their biophysical mode of operation.
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Affiliation(s)
- Katharina F Hohmann
- Institute for Organic Chemistry and Chemical Biology, Center for Biomolecular Magnetic Resonance BMRZ, Goethe University Frankfurt am Main, Max-von-Laue-Strasse 7, 60438 Frankfurt/Main, Germany
| | - Anja Blümler
- Institute for Organic Chemistry and Chemical Biology, Goethe University Frankfurt am Main, Max-von-Laue-Strasse 7, 60438 Frankfurt/Main, Germany
| | - Alexander Heckel
- Institute for Organic Chemistry and Chemical Biology, Goethe University Frankfurt am Main, Max-von-Laue-Strasse 7, 60438 Frankfurt/Main, Germany
| | - Boris Fürtig
- Institute for Organic Chemistry and Chemical Biology, Center for Biomolecular Magnetic Resonance BMRZ, Goethe University Frankfurt am Main, Max-von-Laue-Strasse 7, 60438 Frankfurt/Main, Germany
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6
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Zakh R, Churkin A, Totzeck F, Parr M, Tuller T, Etzion O, Dahari H, Roggendorf M, Frishman D, Barash D. A Mathematical Analysis of HDV Genotypes: From Molecules to Cells. MATHEMATICS (BASEL, SWITZERLAND) 2021; 9:2063. [PMID: 34540628 PMCID: PMC8445514 DOI: 10.3390/math9172063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Hepatitis D virus (HDV) is classified according to eight genotypes. The various genotypes are included in the HDVdb database, where each HDV sequence is specified by its genotype. In this contribution, a mathematical analysis is performed on RNA sequences in HDVdb. The RNA folding predicted structures of the Genbank HDV genome sequences in HDVdb are classified according to their coarse-grain tree-graph representation. The analysis allows discarding in a simple and efficient way the vast majority of the sequences that exhibit a rod-like structure, which is important for the virus replication, to attempt to discover other biological functions by structure consideration. After the filtering, there remain only a small number of sequences that can be checked for their additional stem-loops besides the main one that is known to be responsible for virus replication. It is found that a few sequences contain an additional stem-loop that is responsible for RNA editing or other possible functions. These few sequences are grouped into two main classes, one that is well-known experimentally belonging to genotype 3 for patients from South America associated with RNA editing, and the other that is not known at present belonging to genotype 7 for patients from Cameroon. The possibility that another function besides virus replication reminiscent of the editing mechanism in HDV genotype 3 exists in HDV genotype 7 has not been explored before and is predicted by eigenvalue analysis. Finally, when comparing native and shuffled sequences, it is shown that HDV sequences belonging to all genotypes are accentuated in their mutational robustness and thermodynamic stability as compared to other viruses that were subjected to such an analysis.
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Affiliation(s)
- Rami Zakh
- Department of Computer Science, Ben-Gurion University, Beer-Sheva 8410501, Israel
| | - Alexander Churkin
- Department of Software Engineering, Sami Shamoon College of Engineering, Beer-Sheva 8410501, Israel
| | - Franziska Totzeck
- Department of Bioinformatics, Wissenschaftszentrum Weihenstephan, Technische Universität München, Maximus-von-Imhof-Forum 3, 85354 Freising, Germany
| | - Marina Parr
- Department of Bioinformatics, Wissenschaftszentrum Weihenstephan, Technische Universität München, Maximus-von-Imhof-Forum 3, 85354 Freising, Germany
| | - Tamir Tuller
- Department of Biomedical Engineering, Tel-Aviv University, Tel-Aviv 6997801, Israel
| | - Ohad Etzion
- Soroka University Medical Center, Ben-Gurion University, Beer-Sheva 8410501, Israel
| | - Harel Dahari
- Stritch School of Medicine, Loyola University Chicago, Maywood, IL 60153, USA
| | - Michael Roggendorf
- Institute of Virology, Technische Universität München, 81675 Munich, Germany
| | - Dmitrij Frishman
- Department of Bioinformatics, Wissenschaftszentrum Weihenstephan, Technische Universität München, Maximus-von-Imhof-Forum 3, 85354 Freising, Germany
| | - Danny Barash
- Department of Computer Science, Ben-Gurion University, Beer-Sheva 8410501, Israel
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7
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Huang FW, Barrett CL, Reidys CM. The energy-spectrum of bicompatible sequences. Algorithms Mol Biol 2021; 16:7. [PMID: 34074304 PMCID: PMC8167974 DOI: 10.1186/s13015-021-00187-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Accepted: 05/24/2021] [Indexed: 12/04/2022] Open
Abstract
Background Genotype-phenotype maps provide a meaningful filtration of sequence space and RNA secondary structures are particular such phenotypes. Compatible sequences, which satisfy the base-pairing constraints of a given RNA structure, play an important role in the context of neutral evolution. Sequences that are simultaneously compatible with two given structures (bicompatible sequences), are beacons in phenotypic transitions, induced by erroneously replicating populations of RNA sequences. RNA riboswitches, which are capable of expressing two distinct secondary structures without changing the underlying sequence, are one example of bicompatible sequences in living organisms. Results We present a full loop energy model Boltzmann sampler of bicompatible sequences for pairs of structures. The sequence sampler employs a dynamic programming routine whose time complexity is polynomial when assuming the maximum number of exposed vertices, \documentclass[12pt]{minimal}
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\begin{document}$$\kappa $$\end{document}κ, is a constant. The parameter \documentclass[12pt]{minimal}
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\begin{document}$$\kappa $$\end{document}κ depends on the two structures and can be very large. We introduce a novel topological framework encapsulating the relations between loops that sheds light on the understanding of \documentclass[12pt]{minimal}
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\begin{document}$$\kappa $$\end{document}κ. Based on this framework, we give an algorithm to sample sequences with minimum \documentclass[12pt]{minimal}
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\begin{document}$$\kappa $$\end{document}κ on a particular topologically classified case as well as giving hints to the solution in the other cases. As a result, we utilize our sequence sampler to study some established riboswitches. Conclusion Our analysis of riboswitch sequences shows that a pair of structures needs to satisfy key properties in order to facilitate phenotypic transitions and that pairs of random structures are unlikely to do so. Our analysis observes a distinct signature of riboswitch sequences, suggesting a new criterion for identifying native sequences and sequences subjected to evolutionary pressure. Our free software is available at: https://github.com/FenixHuang667/Bifold.
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8
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Huang J, Voß B. Simulation of Folding Kinetics for Aligned RNAs. Genes (Basel) 2021; 12:genes12030347. [PMID: 33652983 PMCID: PMC7996734 DOI: 10.3390/genes12030347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Revised: 02/18/2021] [Accepted: 02/22/2021] [Indexed: 11/16/2022] Open
Abstract
Studying the folding kinetics of an RNA can provide insight into its function and is thus a valuable method for RNA analyses. Computational approaches to the simulation of folding kinetics suffer from the exponentially large folding space that needs to be evaluated. Here, we present a new approach that combines structure abstraction with evolutionary conservation to restrict the analysis to common parts of folding spaces of related RNAs. The resulting algorithm can recapitulate the folding kinetics known for single RNAs and is able to analyse even long RNAs in reasonable time. Our program RNAliHiKinetics is the first algorithm for the simulation of consensus folding kinetics and addresses a long-standing problem in a new and unique way.
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Affiliation(s)
- Jiabin Huang
- Institute of Medical Microbiology, Virology and Hygiene, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany;
| | - Björn Voß
- Computational Biology Group, Institute of Biochemical Engineering, University of Stuttgart, Allmandring 31, 70569 Stuttgart, Germany
- Correspondence:
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9
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Entzian G, Raden M. pourRNA-a time- and memory-efficient approach for the guided exploration of RNA energy landscapes. Bioinformatics 2020; 36:462-469. [PMID: 31350881 DOI: 10.1093/bioinformatics/btz583] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2019] [Revised: 06/25/2019] [Accepted: 07/22/2019] [Indexed: 01/03/2023] Open
Abstract
MOTIVATION The folding dynamics of ribonucleic acids (RNAs) are typically studied via coarse-grained models of the underlying energy landscape to face the exponential growths of the RNA secondary structure space. Still, studies of exact folding kinetics based on gradient basin abstractions are currently limited to short sequence lengths due to vast memory requirements. In order to compute exact transition rates between gradient basins, state-of-the-art approaches apply global flooding schemes that require to memorize the whole structure space at once. pourRNA tackles this problem via local flooding techniques where memorization is limited to the structure ensembles of individual gradient basins. RESULTS Compared to the only available tool for exact gradient basin-based macro-state transition rates (namely barriers), pourRNA computes the same exact transition rates up to 10 times faster and requires two orders of magnitude less memory for sequences that are still computationally accessible for exhaustive enumeration. Parallelized computation as well as additional heuristics further speed up computations while still producing high-quality transition model approximations. The introduced heuristics enable a guided trade-off between model quality and required computational resources. We introduce and evaluate a macroscopic direct path heuristics to efficiently compute refolding energy barrier estimations for the co-transcriptionally trapped RNA sv11 of length 115 nt. Finally, we also show how pourRNA can be used to identify folding funnels and their respective energetically lowest minima. AVAILABILITY AND IMPLEMENTATION pourRNA is freely available at https://github.com/ViennaRNA/pourRNA. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Gregor Entzian
- Department of Theoretical Chemistry, Faculty of Chemistry, University of Vienna, Vienna 1090, Austria
| | - Martin Raden
- Bioinformatics Group, Department of Computer Science, University of Freiburg, Freiburg 79110, Germany
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10
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Takizawa H, Iwakiri J, Terai G, Asai K. Finding the direct optimal RNA barrier energy and improving pathways with an arbitrary energy model. Bioinformatics 2020; 36:i227-i235. [PMID: 32657400 PMCID: PMC7355307 DOI: 10.1093/bioinformatics/btaa469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022] Open
Abstract
Motivation RNA folding kinetics plays an important role in the biological functions of RNA molecules. An important goal in the investigation of the kinetic behavior of RNAs is to find the folding pathway with the lowest energy barrier. For this purpose, most of the existing methods use heuristics because the number of possible pathways is huge even if only the shortest (direct) folding pathways are considered. Results In this study, we propose a new method using a best-first search strategy to efficiently compute the exact solution of the minimum barrier energy of direct pathways. Using our method, we can find the exact direct pathways within a Hamming distance of 20, whereas the previous methods even miss the exact short pathways. Moreover, our method can be used to improve the pathways found by existing methods for exploring indirect pathways. Availability and implementation The source code and datasets created and used in this research are available at https://github.com/eukaryo/czno. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Hiroki Takizawa
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, Tokyo, Chiba 277-8561 Japan
| | - Junichi Iwakiri
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, Tokyo, Chiba 277-8561 Japan
| | - Goro Terai
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, Tokyo, Chiba 277-8561 Japan
| | - Kiyoshi Asai
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, Tokyo, Chiba 277-8561 Japan.,Artificial Intelligence Research Center (AIRC), National Institute of Advanced Science and Technology (AIST), Tokyo135-0064, Japan
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11
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Takitou S, Taneda A. Ant colony optimization for predicting RNA folding pathways. Comput Biol Chem 2019; 83:107118. [PMID: 31698162 DOI: 10.1016/j.compbiolchem.2019.107118] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2019] [Revised: 06/10/2019] [Accepted: 08/26/2019] [Indexed: 12/30/2022]
Abstract
RNA folding dynamics plays important roles in various functions of RNAs. To date, coarse-grained modeling has been successfully employed to simulate RNA folding dynamics on the energy landscape composed of secondary structures. In such a modeling, the energy barrier height between metastable structures is a key parameter that crucially affects the simulation results. Although a number of approaches ranging from the exact method to heuristic ones are available to predict the barrier heights, developing an efficient heuristic for this purpose is still an algorithmic challenge. We developed a novel RNA folding pathway prediction method, ACOfoldpath, based on Ant Colony Optimization (ACO). ACO is a widely used powerful combinatorial optimization algorithm inspired from the food-seeking behavior of ants. In ACOfoldpath, to accelerate the folding pathway prediction, we reduce the search space by utilizing originally devised structure generation rules. To evaluate the performance of the proposed method, we benchmarked ACOfoldpath on the known nineteen conformational RNA switches. As a result, ACOfoldpath successfully predicted folding pathways better than or comparable to the previous heuristics. The results of RNA folding dynamics simulations and pseudoknotted pathway predictions are also presented.
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Affiliation(s)
- Seira Takitou
- Course of Electronics and Information Technology, Graduate School of Science and Technology, Hirosaki University, Hirosaki, Aomori 036-8561, Japan
| | - Akito Taneda
- Graduate School of Science and Technology, Hirosaki University, Hirosaki, Aomori 036-8561, Japan.
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12
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Wu MJ, Andreasson JOL, Kladwang W, Greenleaf W, Das R. Automated Design of Diverse Stand-Alone Riboswitches. ACS Synth Biol 2019; 8:1838-1846. [PMID: 31298841 PMCID: PMC6703183 DOI: 10.1021/acssynbio.9b00142] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
![]()
Riboswitches that couple binding
of ligands to conformational changes
offer sensors and control elements for RNA synthetic biology and medical
biotechnology. However, design of these riboswitches has required
expert intuition or software specialized to transcription or translation
outputs; design has been particularly challenging for applications
in which the riboswitch output cannot be amplified by other molecular
machinery. We present a fully automated design method called RiboLogic
for such “stand-alone” riboswitches and test it via high-throughput experiments on 2875 molecules using
RNA-MaP (RNA on a massively parallel array) technology. These molecules
consistently modulate their affinity to the MS2 bacteriophage coat
protein upon binding of flavin mononucleotide, tryptophan, theophylline,
and microRNA miR-208a, achieving activation ratios of up to 20 and
significantly better performance than control designs. By encompassing
a wide diversity of stand-alone switches and highly quantitative data,
the resulting ribologic-solves experimental data
set provides a rich resource for further improvement of riboswitch
models and design methods.
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13
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Léger S, Costa MBW, Tulpan D. Pairwise visual comparison of small RNA secondary structures with base pair probabilities. BMC Bioinformatics 2019; 20:293. [PMID: 31142266 PMCID: PMC6542128 DOI: 10.1186/s12859-019-2902-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2019] [Accepted: 05/14/2019] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Predicted RNA secondary structures are typically visualized using dot-plots for base pair binding probabilities and planar graphs for unique structures, such as the minimum free energy structure. These are however difficult to analyze simultaneously. RESULTS This work introduces a compact unified view of the most stable conformation of an RNA secondary structure and its base pair probabilities, which is called the Circular Secondary Structure Base Pairs Probabilities Plot (CS2BP2-Plot). Along with our design we provide access to a web server implementation of our solution that facilitates pairwise comparison of short RNA (and DNA) sequences up to 200 base pairs. The web server first calculates the minimum free energy secondary structure and the base pair probabilities for up to 10 RNA or DNA sequences using RNAfold and then provides a two panel comparative view that includes CS2BP2-Plots along with the traditional graph, planar and circular diagrams obtained with VARNA. The CS2BP2-Plots include highlighting of the nucleotide differences between two selected sequences using ClustalW local alignments. We also provide descriptive statistics, dot-bracket secondary structure representations and ClustalW local alignments for compared sequences. CONCLUSIONS Using circular diagrams and colour and weight-coded arcs, we demonstrate how a single image can replace the state-of-the-art dual representations (dot-plots and minimum free energy structures) for base-pair probabilities of RNA secondary structures while allowing efficient exploration and comparison of different RNA conformations via a web server front end. With that, we provide the community, especially the biologically oriented, with an intuitive tool for ncRNA visualization. Web-server: https://nrcmonsrv01.nrc.ca/cs2bp2plot.
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Affiliation(s)
- Serge Léger
- Digital Technologies Research Center, National Research Council Canada, 100 des Aboiteaux St, Moncton, NB E1A7R1 Canada
| | - Maria Beatriz Walter Costa
- Department of Computer Science, TFome Research Group, Bioinformatics Group, Interdisciplinary Center of Bioinformatics, University of Leipzig, Härtelstrasse 16-18, D-04107 Leipzig, Germany
| | - Dan Tulpan
- Department of Animal Biosciences, Centre for Genetic Improvement of Livestock, University of Guelph, Guelph, Ontario Canada
- Digital Technologies Research Center, National Research Council Canada, 100 des Aboiteaux St, Moncton, NB E1A7R1 Canada
- School of Computer Science, University of Guelph, Guelph, Ontario Canada
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14
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Evolving methods for rational de novo design of functional RNA molecules. Methods 2019; 161:54-63. [PMID: 31059832 DOI: 10.1016/j.ymeth.2019.04.022] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2019] [Revised: 04/26/2019] [Accepted: 04/29/2019] [Indexed: 12/16/2022] Open
Abstract
Artificial RNA molecules with novel functionality have many applications in synthetic biology, pharmacy and white biotechnology. The de novo design of such devices using computational methods and prediction tools is a resource-efficient alternative to experimental screening and selection pipelines. In this review, we describe methods common to many such computational approaches, thoroughly dissect these methods and highlight open questions for the individual steps. Initially, it is essential to investigate the biological target system, the regulatory mechanism that will be exploited, as well as the desired components in order to define design objectives. Subsequent computational design is needed to combine the selected components and to obtain novel functionality. This process can usually be split into constrained sequence sampling, the formulation of an optimization problem and an in silico analysis to narrow down the number of candidates with respect to secondary goals. Finally, experimental analysis is important to check whether the defined design objectives are indeed met in the target environment and detailed characterization experiments should be performed to improve the mechanistic models and detect missing design requirements.
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15
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Hammer S, Wang W, Will S, Ponty Y. Fixed-parameter tractable sampling for RNA design with multiple target structures. BMC Bioinformatics 2019; 20:209. [PMID: 31023239 PMCID: PMC6482512 DOI: 10.1186/s12859-019-2784-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2018] [Accepted: 03/28/2019] [Indexed: 01/09/2023] Open
Abstract
Background The design of multi-stable RNA molecules has important applications in biology, medicine, and biotechnology. Synthetic design approaches profit strongly from effective in-silico methods, which substantially reduce the need for costly wet-lab experiments. Results We devise a novel approach to a central ingredient of most in-silico design methods: the generation of sequences that fold well into multiple target structures. Based on constraint networks, our approach supports generic Boltzmann-weighted sampling, which enables the positive design of RNA sequences with specific free energies (for each of multiple, possibly pseudoknotted, target structures) and GC-content. Moreover, we study general properties of our approach empirically and generate biologically relevant multi-target Boltzmann-weighted designs for an established design benchmark. Our results demonstrate the efficacy and feasibility of the method in practice as well as the benefits of Boltzmann sampling over the previously best multi-target sampling strategy—even for the case of negative design of multi-stable RNAs. Besides empirically studies, we finally justify the algorithmic details due to a fundamental theoretic result about multi-stable RNA design, namely the #P-hardness of the counting of designs. Conclusion introduces a novel, flexible, and effective approach to multi-target RNA design, which promises broad applicability and extensibility. Our free software is available at: https://github.com/yannponty/RNARedPrint
Supplementary data are available online. Electronic supplementary material The online version of this article (10.1186/s12859-019-2784-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Stefan Hammer
- Dept. Computer Science, and Interdisciplinary Center for Bioinformatics, Univ. Leipzig, Härtelstr. 16-18, Leipzig, D-04107, Germany.,Dept. Theoretical Chemistry, Univ. Vienna, Währingerstr. 17, Wien, A-1090, Austria.,Bioinformatics and Computational Biology Research Group, Univ. Vienna, Währingerstr. 17, Wien, A-1090, Austria
| | - Wei Wang
- CNRS UMR 7161 LIX, Ecole Polytechnique, Bat. Alan Turing, Palaiseau, 91120, France
| | - Sebastian Will
- Dept. Theoretical Chemistry, Univ. Vienna, Währingerstr. 17, Wien, A-1090, Austria. .,Bioinformatics and Computational Biology Research Group, Univ. Vienna, Währingerstr. 17, Wien, A-1090, Austria.
| | - Yann Ponty
- CNRS UMR 7161 LIX, Ecole Polytechnique, Bat. Alan Turing, Palaiseau, 91120, France.
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16
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Roh JH, Kilburn D, Behrouzi R, Sung W, Briber RM, Woodson SA. Effects of Preferential Counterion Interactions on the Specificity of RNA Folding. J Phys Chem Lett 2018; 9:5726-5732. [PMID: 30211556 PMCID: PMC6351067 DOI: 10.1021/acs.jpclett.8b02086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
The real-time search for native RNA structure is essential for the operation of regulatory RNAs. We previously reported that a fraction of the Azoarcus ribozyme achieves a compact structure in less than a millisecond. To scrutinize the forces that drive initial folding steps, we used time-resolved SAXS to compare the folding dynamics of this ribozyme in thermodynamically isostable concentrations of different counterions. The results show that the size of the fast-folding population increases with the number of available counterions and correlates with the flexibility of initial RNA structures. Within 1 ms of folding, Mg2+ exhibits a smaller preferential interaction coefficient per charge, ΔΓ+/ Z, than Na+ or [Co(NH3)6]3+. The lower ΔΓ+/ Z corresponds to a smaller yield of folded RNA, although Mg2+ stabilizes native RNA more efficiently than other ions at equilibrium. These results suggest that strong Mg2+-RNA interactions impede the search for globally native structure during early folding stages.
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Affiliation(s)
- Joon Ho Roh
- Department of Materials Science and Engineering , University of Maryland , College Park , Maryland 20742 , United States
- T. C. Jenkins Department of Biophysics , Johns Hopkins University , Baltimore , Maryland 21218 , United States
| | - Duncan Kilburn
- T. C. Jenkins Department of Biophysics , Johns Hopkins University , Baltimore , Maryland 21218 , United States
| | - Reza Behrouzi
- Cell Biology , Harvard Medical School , Boston , Massachusetts 02115 , United States
| | - Wokyung Sung
- Department of Physics , Pohang University of Science and Technology , Pohang 37673 , Republic of Korea
| | - R M Briber
- Department of Materials Science and Engineering , University of Maryland , College Park , Maryland 20742 , United States
| | - Sarah A Woodson
- T. C. Jenkins Department of Biophysics , Johns Hopkins University , Baltimore , Maryland 21218 , United States
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17
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Hammer S, Tschiatschek B, Flamm C, Hofacker IL, Findeiß S. RNAblueprint: flexible multiple target nucleic acid sequence design. Bioinformatics 2018; 33:2850-2858. [PMID: 28449031 PMCID: PMC5870862 DOI: 10.1093/bioinformatics/btx263] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2016] [Accepted: 04/21/2017] [Indexed: 01/06/2023] Open
Abstract
Motivation Realizing the value of synthetic biology in biotechnology and medicine requires the design of molecules with specialized functions. Due to its close structure to function relationship, and the availability of good structure prediction methods and energy models, RNA is perfectly suited to be synthetically engineered with predefined properties. However, currently available RNA design tools cannot be easily adapted to accommodate new design specifications. Furthermore, complicated sampling and optimization methods are often developed to suit a specific RNA design goal, adding to their inflexibility. Results We developed a C ++ library implementing a graph coloring approach to stochastically sample sequences compatible with structural and sequence constraints from the typically very large solution space. The approach allows to specify and explore the solution space in a well defined way. Our library also guarantees uniform sampling, which makes optimization runs performant by not only avoiding re-evaluation of already found solutions, but also by raising the probability of finding better solutions for long optimization runs. We show that our software can be combined with any other software package to allow diverse RNA design applications. Scripting interfaces allow the easy adaption of existing code to accommodate new scenarios, making the whole design process very flexible. We implemented example design approaches written in Python to demonstrate these advantages. Availability and implementation RNAblueprint, Python implementations and benchmark datasets are available at github: https://github.com/ViennaRNA. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Stefan Hammer
- Faculty of Chemistry, Department of Theoretical Chemistry.,Faculty of Computer Science, Research Group Bioinformatics and Computational Biology
| | - Birgit Tschiatschek
- Faculty of Computer Science, Research Group Bioinformatics and Computational Biology
| | - Christoph Flamm
- Faculty of Chemistry, Department of Theoretical Chemistry.,Research Network Chemistry Meets Microbiology, University of Vienna, 1090 Vienna, Austria
| | - Ivo L Hofacker
- Faculty of Chemistry, Department of Theoretical Chemistry.,Faculty of Computer Science, Research Group Bioinformatics and Computational Biology.,Center for Non-Coding RNA in Technology and Health, University of Copenhagen, Copenhagen DK-1870, Denmark
| | - Sven Findeiß
- Faculty of Chemistry, Department of Theoretical Chemistry.,Faculty of Computer Science, Research Group Bioinformatics and Computational Biology
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18
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Findeiß S, Etzel M, Will S, Mörl M, Stadler PF. Design of Artificial Riboswitches as Biosensors. SENSORS 2017; 17:s17091990. [PMID: 28867802 PMCID: PMC5621056 DOI: 10.3390/s17091990] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/08/2017] [Revised: 08/23/2017] [Accepted: 08/25/2017] [Indexed: 12/11/2022]
Abstract
RNA aptamers readily recognize small organic molecules, polypeptides, as well as other nucleic acids in a highly specific manner. Many such aptamers have evolved as parts of regulatory systems in nature. Experimental selection techniques such as SELEX have been very successful in finding artificial aptamers for a wide variety of natural and synthetic ligands. Changes in structure and/or stability of aptamers upon ligand binding can propagate through larger RNA constructs and cause specific structural changes at distal positions. In turn, these may affect transcription, translation, splicing, or binding events. The RNA secondary structure model realistically describes both thermodynamic and kinetic aspects of RNA structure formation and refolding at a single, consistent level of modelling. Thus, this framework allows studying the function of natural riboswitches in silico. Moreover, it enables rationally designing artificial switches, combining essentially arbitrary sensors with a broad choice of read-out systems. Eventually, this approach sets the stage for constructing versatile biosensors.
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Affiliation(s)
- Sven Findeiß
- Bioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, University Leipzig, Härtelstraße 16-18, 04107 Leipzig, Germany.
- Faculty of Computer Science, Research Group Bioinformatics and Computational Biology, University of Vienna, Währingerstraße 29, A-1090 Vienna, Austria.
- Faculty of Chemistry, Department of Theoretical Chemistry, University of Vienna, Währingerstraße 17, A-1090 Vienna, Austria.
| | - Maja Etzel
- Institute for Biochemistry, Leipzig University, Brüderstraße 34, 04103 Leipzig, Germany.
| | - Sebastian Will
- Bioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, University Leipzig, Härtelstraße 16-18, 04107 Leipzig, Germany.
- Faculty of Chemistry, Department of Theoretical Chemistry, University of Vienna, Währingerstraße 17, A-1090 Vienna, Austria.
- Institute for Biochemistry, Leipzig University, Brüderstraße 34, 04103 Leipzig, Germany.
| | - Mario Mörl
- Institute for Biochemistry, Leipzig University, Brüderstraße 34, 04103 Leipzig, Germany.
| | - Peter F Stadler
- Bioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, University Leipzig, Härtelstraße 16-18, 04107 Leipzig, Germany.
- Faculty of Chemistry, Department of Theoretical Chemistry, University of Vienna, Währingerstraße 17, A-1090 Vienna, Austria.
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, 04103 Leipzig, Germany.
- Max Planck Institute for Mathematics in the Sciences, Inselstraße 22, 04103 Leipzig, Germany.
- Fraunhofer Institute for Cell Therapy and Immunology, Perlickstrasse 1, 04103 Leipzig, Germany.
- Center for RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg , Denmark.
- Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USA.
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19
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Michálik J, Touzet H, Ponty Y. Efficient approximations of RNA kinetics landscape using non-redundant sampling. Bioinformatics 2017; 33:i283-i292. [PMID: 28882001 PMCID: PMC5870705 DOI: 10.1093/bioinformatics/btx269] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
MOTIVATION Kinetics is key to understand many phenomena involving RNAs, such as co-transcriptional folding and riboswitches. Exact out-of-equilibrium studies induce extreme computational demands, leading state-of-the-art methods to rely on approximated kinetics landscapes, obtained using sampling strategies that strive to generate the key landmarks of the landscape topology. However, such methods are impeded by a large level of redundancy within sampled sets. Such a redundancy is uninformative, and obfuscates important intermediate states, leading to an incomplete vision of RNA dynamics. RESULTS We introduce RNANR, a new set of algorithms for the exploration of RNA kinetics landscapes at the secondary structure level. RNANR considers locally optimal structures, a reduced set of RNA conformations, in order to focus its sampling on basins in the kinetic landscape. Along with an exhaustive enumeration, RNANR implements a novel non-redundant stochastic sampling, and offers a rich array of structural parameters. Our tests on both real and random RNAs reveal that RNANR allows to generate more unique structures in a given time than its competitors, and allows a deeper exploration of kinetics landscapes. AVAILABILITY AND IMPLEMENTATION RNANR is freely available at https://project.inria.fr/rnalands/rnanr . CONTACT yann.ponty@lix.polytechnique.fr.
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Affiliation(s)
- Juraj Michálik
- AMIB project, Inria Saclay, Palaiseau, France
- LIX CNRS UMR 7161, Ecole Polytechnique, Palaiseau, France
| | - Hélène Touzet
- CNRS, CRIStAL (UMR 9189, University of Lille), Villeneuve d’Ascq, France
- Bonsai project, Inria Lille-Nord Europe, Villeneuve d’Ascq, France
| | - Yann Ponty
- AMIB project, Inria Saclay, Palaiseau, France
- LIX CNRS UMR 7161, Ecole Polytechnique, Palaiseau, France
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20
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Wolfe BR, Porubsky NJ, Zadeh JN, Dirks RM, Pierce NA. Constrained Multistate Sequence Design for Nucleic Acid Reaction Pathway Engineering. J Am Chem Soc 2017; 139:3134-3144. [DOI: 10.1021/jacs.6b12693] [Citation(s) in RCA: 72] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Affiliation(s)
- Brian R. Wolfe
- Division of Biology & Biological Engineering, California Institute of Technology, Pasadena, California 91125, United States
| | - Nicholas J. Porubsky
- Division of Chemistry & Chemical Engineering, California Institute of Technology, Pasadena, California 91125, United States
| | - Joseph N. Zadeh
- Division of Biology & Biological Engineering, California Institute of Technology, Pasadena, California 91125, United States
| | - Robert M. Dirks
- Division of Biology & Biological Engineering, California Institute of Technology, Pasadena, California 91125, United States
| | - Niles A. Pierce
- Division of Biology & Biological Engineering, California Institute of Technology, Pasadena, California 91125, United States
- Division of Engineering & Applied Science, California Institute of Technology, Pasadena, California 91125, United States
- Weatherall
Institute of Molecular Medicine, University of Oxford, Oxford OX3 9DS, United Kingdom
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21
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Garcia-Martin JA, Dotu I, Fernandez-Chamorro J, Lozano G, Ramajo J, Martinez-Salas E, Clote P. RNAiFold2T: Constraint Programming design of thermo-IRES switches. Bioinformatics 2016; 32:i360-i368. [PMID: 27307638 PMCID: PMC4908349 DOI: 10.1093/bioinformatics/btw265] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Abstract
MOTIVATION RNA thermometers (RNATs) are cis-regulatory elements that change secondary structure upon temperature shift. Often involved in the regulation of heat shock, cold shock and virulence genes, RNATs constitute an interesting potential resource in synthetic biology, where engineered RNATs could prove to be useful tools in biosensors and conditional gene regulation. RESULTS Solving the 2-temperature inverse folding problem is critical for RNAT engineering. Here we introduce RNAiFold2T, the first Constraint Programming (CP) and Large Neighborhood Search (LNS) algorithms to solve this problem. Benchmarking tests of RNAiFold2T against existent programs (adaptive walk and genetic algorithm) inverse folding show that our software generates two orders of magnitude more solutions, thus allowing ample exploration of the space of solutions. Subsequently, solutions can be prioritized by computing various measures, including probability of target structure in the ensemble, melting temperature, etc. Using this strategy, we rationally designed two thermosensor internal ribosome entry site (thermo-IRES) elements, whose normalized cap-independent translation efficiency is approximately 50% greater at 42 °C than 30 °C, when tested in reticulocyte lysates. Translation efficiency is lower than that of the wild-type IRES element, which on the other hand is fully resistant to temperature shift-up. This appears to be the first purely computational design of functional RNA thermoswitches, and certainly the first purely computational design of functional thermo-IRES elements. AVAILABILITY RNAiFold2T is publicly available as part of the new release RNAiFold3.0 at https://github.com/clotelab/RNAiFold and http://bioinformatics.bc.edu/clotelab/RNAiFold, which latter has a web server as well. The software is written in C ++ and uses OR-Tools CP search engine. CONTACT clote@bc.edu SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
| | - Ivan Dotu
- Department of Experimental and Health Sciences, Research Programme on Biomedical Informatics (GRIB), Universitat Pompeu Fabra. Dr. Aiguader 88, Barcelona, Spain
| | - Javier Fernandez-Chamorro
- Centro de Biologia Molecular Severo Ochoa, Consejo Superior de Investigaciones Cientificas-Universidad Autonoma de Madrid, 28049 Madrid, Spain
| | - Gloria Lozano
- Centro de Biologia Molecular Severo Ochoa, Consejo Superior de Investigaciones Cientificas-Universidad Autonoma de Madrid, 28049 Madrid, Spain
| | - Jorge Ramajo
- Centro de Biologia Molecular Severo Ochoa, Consejo Superior de Investigaciones Cientificas-Universidad Autonoma de Madrid, 28049 Madrid, Spain
| | - Encarnacion Martinez-Salas
- Centro de Biologia Molecular Severo Ochoa, Consejo Superior de Investigaciones Cientificas-Universidad Autonoma de Madrid, 28049 Madrid, Spain
| | - Peter Clote
- Biology Department, Boston College, Chestnut Hill, MA 02467, USA
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22
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Badelt S, Flamm C, Hofacker IL. Computational Design of a Circular RNA with Prionlike Behavior. ARTIFICIAL LIFE 2016; 22:172-184. [PMID: 26934089 DOI: 10.1162/artl_a_00197] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
RNA molecules engineered to fold into predefined conformations have enabled the design of a multitude of functional RNA devices in the field of synthetic biology and nanotechnology. More complex designs require efficient computational methods, which need to consider not only equilibrium thermodynamics but also the kinetics of structure formation. Here we present a novel type of RNA design that mimics the behavior of prions, that is, sequences capable of interaction-triggered autocatalytic replication of conformations. Our design was computed with the ViennaRNA package and is based on circular RNA that embeds domains amenable to intermolecular kissing interactions.
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23
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Kucharík M, Hofacker IL, Stadler PF, Qin J. Pseudoknots in RNA folding landscapes. Bioinformatics 2016; 32:187-94. [PMID: 26428288 PMCID: PMC4708108 DOI: 10.1093/bioinformatics/btv572] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2015] [Revised: 09/10/2015] [Accepted: 09/27/2015] [Indexed: 02/04/2023] Open
Abstract
MOTIVATION The function of an RNA molecule is not only linked to its native structure, which is usually taken to be the ground state of its folding landscape, but also in many cases crucially depends on the details of the folding pathways such as stable folding intermediates or the timing of the folding process itself. To model and understand these processes, it is necessary to go beyond ground state structures. The study of rugged RNA folding landscapes holds the key to answer these questions. Efficient coarse-graining methods are required to reduce the intractably vast energy landscapes into condensed representations such as barrier trees or basin hopping graphs : BHG) that convey an approximate but comprehensive picture of the folding kinetics. So far, exact and heuristic coarse-graining methods have been mostly restricted to the pseudoknot-free secondary structures. Pseudoknots, which are common motifs and have been repeatedly hypothesized to play an important role in guiding folding trajectories, were usually excluded. RESULTS We generalize the BHG framework to include pseudoknotted RNA structures and systematically study the differences in predicted folding behavior depending on whether pseudoknotted structures are allowed to occur as folding intermediates or not. We observe that RNAs with pseudoknotted ground state structures tend to have more pseudoknotted folding intermediates than RNAs with pseudoknot-free ground state structures. The occurrence and influence of pseudoknotted intermediates on the folding pathway, however, appear to depend very strongly on the individual RNAs so that no general rule can be inferred. AVAILABILITY AND IMPLEMENTATION The algorithms described here are implemented in C++ as standalone programs. Its source code and Supplemental material can be freely downloaded from http://www.tbi.univie.ac.at/bhg.html. CONTACT qin@bioinf.uni-leipzig.de SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
| | - Ivo L Hofacker
- Institute for Theoretical Chemistry, Research Group BCB, Faculty of Computer Science, University of Vienna, Austria, RTH, University of Copenhagen, Frederiksberg, Denmark
| | - Peter F Stadler
- Institute for Theoretical Chemistry, RTH, University of Copenhagen, Frederiksberg, Denmark, Department of Computer Science & IZBI & iDiv & LIFE, Leipzig University, Max Planck Institute for Mathematics in the Sciences, Fraunhofer Institute IZI, Leipzig, Germany, Santa Fe Institute, Santa Fe, NM 87501, USA and
| | - Jing Qin
- Institute for Theoretical Chemistry, RTH, University of Copenhagen, Frederiksberg, Denmark, IMADA, University of Southern Denmark, Campusvej 55, Odense, Denmark
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24
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Abstract
We describe the first dynamic programming algorithm that computes the expected degree for the network, or graph G = (V, E) of all secondary structures of a given RNA sequence a = a1, …, an. Here, the nodes V correspond to all secondary structures of a, while an edge exists between nodes s, t if the secondary structure t can be obtained from s by adding, removing or shifting a base pair. Since secondary structure kinetics programs implement the Gillespie algorithm, which simulates a random walk on the network of secondary structures, the expected network degree may provide a better understanding of kinetics of RNA folding when allowing defect diffusion, helix zippering, and related conformation transformations. We determine the correlation between expected network degree, contact order, conformational entropy, and expected number of native contacts for a benchmarking dataset of RNAs. Source code is available at http://bioinformatics.bc.edu/clotelab/RNAexpNumNbors.
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25
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Wolfe BR, Pierce NA. Sequence Design for a Test Tube of Interacting Nucleic Acid Strands. ACS Synth Biol 2015; 4:1086-100. [PMID: 25329866 DOI: 10.1021/sb5002196] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
We describe an algorithm for designing the equilibrium base-pairing properties of a test tube of interacting nucleic acid strands. A target test tube is specified as a set of desired "on-target" complexes, each with a target secondary structure and target concentration, and a set of undesired "off-target" complexes, each with vanishing target concentration. Sequence design is performed by optimizing the test tube ensemble defect, corresponding to the concentration of incorrectly paired nucleotides at equilibrium evaluated over the ensemble of the test tube. To reduce the computational cost of accepting or rejecting mutations to a random initial sequence, the structural ensemble of each on-target complex is hierarchically decomposed into a tree of conditional subensembles, yielding a forest of decomposition trees. Candidate sequences are evaluated efficiently at the leaf level of the decomposition forest by estimating the test tube ensemble defect from conditional physical properties calculated over the leaf subensembles. As optimized subsequences are merged toward the root level of the forest, any emergent defects are eliminated via ensemble redecomposition and sequence reoptimization. After successfully merging subsequences to the root level, the exact test tube ensemble defect is calculated for the first time, explicitly checking for the effect of the previously neglected off-target complexes. Any off-target complexes that form at appreciable concentration are hierarchically decomposed, added to the decomposition forest, and actively destabilized during subsequent forest reoptimization. For target test tubes representative of design challenges in the molecular programming and synthetic biology communities, our test tube design algorithm typically succeeds in achieving a normalized test tube ensemble defect ≤1% at a design cost within an order of magnitude of the cost of test tube analysis.
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Affiliation(s)
- Brian R. Wolfe
- Division of Biology and Biological
Engineering and ‡Division of Engineering and Applied
Science, California Institute of Technology, Pasadena, California 91125, United States
| | - Niles A. Pierce
- Division of Biology and Biological
Engineering and ‡Division of Engineering and Applied
Science, California Institute of Technology, Pasadena, California 91125, United States
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26
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Jabbari H, Aminpour M, Montemagno C. Computational Approaches to Nucleic Acid Origami. ACS COMBINATORIAL SCIENCE 2015; 17:535-47. [PMID: 26348196 DOI: 10.1021/acscombsci.5b00079] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Recent advances in experimental DNA origami have dramatically expanded the horizon of DNA nanotechnology. Complex 3D suprastructures have been designed and developed using DNA origami with applications in biomaterial science, nanomedicine, nanorobotics, and molecular computation. Ribonucleic acid (RNA) origami has recently been realized as a new approach. Similar to DNA, RNA molecules can be designed to form complex 3D structures through complementary base pairings. RNA origami structures are, however, more compact and more thermodynamically stable due to RNA's non-canonical base pairing and tertiary interactions. With all these advantages, the development of RNA origami lags behind DNA origami by a large gap. Furthermore, although computational methods have proven to be effective in designing DNA and RNA origami structures and in their evaluation, advances in computational nucleic acid origami is even more limited. In this paper, we review major milestones in experimental and computational DNA and RNA origami and present current challenges in these fields. We believe collaboration between experimental nanotechnologists and computer scientists are critical for advancing these new research paradigms.
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Affiliation(s)
- Hosna Jabbari
- Ingenuity Lab, 11421 Saskatchewan
Drive, Edmonton, Alberta T6G 2M9, Canada
- Department
of Chemical and Materials Engineering, University of Alberta, Edmonton T6G 2V4, Canada
| | - Maral Aminpour
- Ingenuity Lab, 11421 Saskatchewan
Drive, Edmonton, Alberta T6G 2M9, Canada
- Department
of Chemical and Materials Engineering, University of Alberta, Edmonton T6G 2V4, Canada
| | - Carlo Montemagno
- Ingenuity Lab, 11421 Saskatchewan
Drive, Edmonton, Alberta T6G 2M9, Canada
- Department
of Chemical and Materials Engineering, University of Alberta, Edmonton T6G 2V4, Canada
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27
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Taneda A. Multi-objective optimization for RNA design with multiple target secondary structures. BMC Bioinformatics 2015; 16:280. [PMID: 26335276 PMCID: PMC4559319 DOI: 10.1186/s12859-015-0706-x] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2014] [Accepted: 08/17/2015] [Indexed: 12/24/2022] Open
Abstract
Background RNAs are attractive molecules as the biological parts for synthetic biology. In particular, the ability of conformational changes, which can be encoded in designer RNAs, enables us to create multistable molecular switches that function in biological circuits. Although various algorithms for designing such RNA switches have been proposed, the previous algorithms optimize the RNA sequences against the weighted sum of objective functions, where empirical weights among objective functions are used. In addition, an RNA design algorithm for multiple pseudoknot targets is currently not available. Results We developed a novel computational tool for automatically designing RNA sequences which fold into multiple target secondary structures. Our algorithm designs RNA sequences based on multi-objective genetic algorithm, by which we can explore the RNA sequences having good objective function values without empirical weight parameters among the objective functions. Our algorithm has great flexibility by virtue of this weight-free nature. We benchmarked our multi-target RNA design algorithm with the datasets of two, three, and four target structures and found that our algorithm shows better or comparable design performances compared with the previous algorithms, RNAdesign and Frnakenstein. In addition to the benchmarks with pseudoknot-free datasets, we benchmarked MODENA with two-target pseudoknot datasets and found that MODENA can design the RNAs which have the target pseudoknotted secondary structures whose free energies are close to the lowest free energy. Moreover, we applied our algorithm to a ribozyme-based ON-switch which takes a ribozyme-inactive secondary structure when the theophylline aptamer structure is assumed. Conclusions Currently, MODENA is the only RNA design software which can be applied to multiple pseudoknot targets. Successful design results for the multiple targets and an RNA device indicate usefulness of our multi-objective RNA design algorithm. Electronic supplementary material The online version of this article (doi:10.1186/s12859-015-0706-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Akito Taneda
- Graduate School of Science and Technology, Hirosaki University, 3 Bunkyo-cho, Hirosaki, Aomori, Japan.
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28
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Petkovic S, Badelt S, Block S, Flamm C, Delcea M, Hofacker I, Müller S. Sequence-controlled RNA self-processing: computational design, biochemical analysis, and visualization by AFM. RNA (NEW YORK, N.Y.) 2015; 21:1249-1260. [PMID: 25999318 PMCID: PMC4478344 DOI: 10.1261/rna.047670.114] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/12/2014] [Accepted: 03/07/2015] [Indexed: 06/04/2023]
Abstract
Reversible chemistry allowing for assembly and disassembly of molecular entities is important for biological self-organization. Thus, ribozymes that support both cleavage and formation of phosphodiester bonds may have contributed to the emergence of functional diversity and increasing complexity of regulatory RNAs in early life. We have previously engineered a variant of the hairpin ribozyme that shows how ribozymes may have circularized or extended their own length by forming concatemers. Using the Vienna RNA package, we now optimized this hairpin ribozyme variant and selected four different RNA sequences that were expected to circularize more efficiently or form longer concatemers upon transcription. (Two-dimensional) PAGE analysis confirms that (i) all four selected ribozymes are catalytically active and (ii) high yields of cyclic species are obtained. AFM imaging in combination with RNA structure prediction enabled us to calculate the distributions of monomers and self-concatenated dimers and trimers. Our results show that computationally optimized molecules do form reasonable amounts of trimers, which has not been observed for the original system so far, and we demonstrate that the combination of theoretical prediction, biochemical and physical analysis is a promising approach toward accurate prediction of ribozyme behavior and design of ribozymes with predefined functions.
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Affiliation(s)
- Sonja Petkovic
- Institute for Biochemistry, Ernst-Moritz-Arndt University Greifswald, 17487 Greifswald, Germany
| | - Stefan Badelt
- Institute for Theoretical Chemistry, University of Vienna, A-1090 Vienna, Austria
| | - Stephan Block
- ZIK HIKE-Center for Innovation Competence, Humoral Immune Reactions in Cardiovascular Diseases, Ernst-Moritz-Arndt University Greifswald, 17489 Greifswald, Germany
| | - Christoph Flamm
- Institute for Theoretical Chemistry, University of Vienna, A-1090 Vienna, Austria
| | - Mihaela Delcea
- ZIK HIKE-Center for Innovation Competence, Humoral Immune Reactions in Cardiovascular Diseases, Ernst-Moritz-Arndt University Greifswald, 17489 Greifswald, Germany
| | - Ivo Hofacker
- Institute for Theoretical Chemistry, University of Vienna, A-1090 Vienna, Austria Research Group Bioinformatics and Computational Biology, University of Vienna, A-1090 Vienna, Austria
| | - Sabine Müller
- Institute for Biochemistry, Ernst-Moritz-Arndt University Greifswald, 17487 Greifswald, Germany
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Li Y, Zhong C, Zhang S. Finding consensus stable local optimal structures for aligned RNA sequences and its application to discovering riboswitch elements. ACTA ACUST UNITED AC 2015; 10:498-518. [PMID: 24989865 DOI: 10.1504/ijbra.2014.062997] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Many non-coding RNAs (ncRNAs) can fold into alternate native structures and perform different biological functions. The computational prediction of an ncRNA's alternate native structures can be conducted by analysing the ncRNA's energy landscape. Previously, we have developed a computational approach, RNASLOpt, to predict alternate native structures for a single RNA. In this paper, in order to improve the accuracy of the prediction, we incorporate structural conservation information among a family of related ncRNA sequences to the prediction. We propose a comparative approach, RNAConSLOpt, to produce all possible consensus SLOpt stack configurations that are conserved on the consensus energy landscape of a family of related ncRNAs. Benchmarking tests show that RNAConSLOpt can reduce the number of candidate structures compared with RNASLOpt, and can predict ncRNAs' alternate native structures accurately. Moreover, an application of the proposed pipeline to bacteria in Bacillus genus has discovered several novel riboswitch candidates.
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Affiliation(s)
- Yuan Li
- Department of Electrical Engineering and Computer Science, University of Central Florida, Orlando, Florida 32816, USA
| | - Cuncong Zhong
- Department of Electrical Engineering and Computer Science, University of Central Florida, Orlando, Florida 32816, USA
| | - Shaojie Zhang
- Department of Electrical Engineering and Computer Science, University of Central Florida, Orlando, Florida 32816, USA
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Fürtig B, Nozinovic S, Reining A, Schwalbe H. Multiple conformational states of riboswitches fine-tune gene regulation. Curr Opin Struct Biol 2015; 30:112-124. [PMID: 25727496 DOI: 10.1016/j.sbi.2015.02.007] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2015] [Revised: 02/06/2015] [Accepted: 02/11/2015] [Indexed: 01/08/2023]
Abstract
Riboswitches are structured regions of mRNAs that modulate gene expression in response to specific binding of low molecular-weight ligands. They function by induced transitions between different functional conformations. The standard model assumed that the two functional states, the ligand-bound and ligand-free state, populated only two stable conformations. Recent discoveries of multiple conformations for the apo-state and holo-state of riboswitches challenge this model. Moreover, it becomes evident that detected conformational heterogeneity--mostly in the apo-state--provides sensitivity to multiple environmental inputs for riboswitch-based gene-regulation.
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Affiliation(s)
- Boris Fürtig
- Institute of Organic Chemistry and Chemical Biology, BMRZ, Johann Wolfgang Goethe-Universität, Max von Laue-Straße 7, 60438 Frankfurt am Main, Germany
| | - Senada Nozinovic
- Institute of Organic Chemistry and Chemical Biology, BMRZ, Johann Wolfgang Goethe-Universität, Max von Laue-Straße 7, 60438 Frankfurt am Main, Germany
| | - Anke Reining
- Institute of Organic Chemistry and Chemical Biology, BMRZ, Johann Wolfgang Goethe-Universität, Max von Laue-Straße 7, 60438 Frankfurt am Main, Germany
| | - Harald Schwalbe
- Institute of Organic Chemistry and Chemical Biology, BMRZ, Johann Wolfgang Goethe-Universität, Max von Laue-Straße 7, 60438 Frankfurt am Main, Germany.
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31
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Abstract
In this article, we introduce the software suite Hermes, which provides fast, novel algorithms for RNA secondary structure kinetics. Using the fast Fourier transform to efficiently compute the Boltzmann probability that a secondary structure S of a given RNA sequence has base pair distance x (resp. y) from reference structure A (resp. B), Hermes computes the exact kinetics of folding from A to B in this coarse-grained model. In particular, Hermes computes the mean first passage time from the transition probability matrix by using matrix inversion, and also computes the equilibrium time from the rate matrix by using spectral decomposition. Due to the model granularity and the speed of Hermes, it is capable of determining secondary structure refolding kinetics for large RNA sequences, beyond the range of other methods. Comparative benchmarking of Hermes with other methods indicates that Hermes provides refolding kinetics of accuracy suitable for use in the computational design of RNA, an important area of synthetic biology. Source code and documentation for Hermes are available.
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Affiliation(s)
- Evan Senter
- Department of Biology, Boston College , Chestnut Hill, Massachusetts
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32
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Abstract
In this chapter, we review both computational and experimental aspects of de novo RNA sequence design. We give an overview of currently available design software and their limitations, and discuss the necessary setup to experimentally validate proper function in vitro and in vivo. We focus on transcription-regulating riboswitches, a task that has just recently lead to first successful designs of such RNA elements.
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Affiliation(s)
- Sven Findeiß
- Research Group Bioinformatics and Computational Biology, Faculty of Computer Science, University of Vienna, Vienna, Austria; Institute for Theoretical Chemistry, University of Vienna, Vienna, Austria
| | - Manja Wachsmuth
- Institute for Biochemistry, University of Leipzig, Leipzig, Germany
| | - Mario Mörl
- Institute for Biochemistry, University of Leipzig, Leipzig, Germany.
| | - Peter F Stadler
- Institute for Theoretical Chemistry, University of Vienna, Vienna, Austria; Bioinformatics Group, Department of Computer Science and the Interdisciplinary Center for Bioinformatic, University of Leipzig, Leipzig, Germany; Center for RNA in Technology and Health, University of Copenhagen, Frederiksberg, Denmark; Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany; Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany; Santa Fe Institute, Santa Fe, New Mexico, USA
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33
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Mann M, Kucharík M, Flamm C, Wolfinger MT. Memory-efficient RNA energy landscape exploration. Bioinformatics 2014; 30:2584-91. [PMID: 24833804 PMCID: PMC4155248 DOI: 10.1093/bioinformatics/btu337] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2014] [Revised: 04/25/2014] [Accepted: 05/08/2014] [Indexed: 02/01/2023] Open
Abstract
MOTIVATION Energy landscapes provide a valuable means for studying the folding dynamics of short RNA molecules in detail by modeling all possible structures and their transitions. Higher abstraction levels based on a macro-state decomposition of the landscape enable the study of larger systems; however, they are still restricted by huge memory requirements of exact approaches. RESULTS We present a highly parallelizable local enumeration scheme that enables the computation of exact macro-state transition models with highly reduced memory requirements. The approach is evaluated on RNA secondary structure landscapes using a gradient basin definition for macro-states. Furthermore, we demonstrate the need for exact transition models by comparing two barrier-based approaches, and perform a detailed investigation of gradient basins in RNA energy landscapes. AVAILABILITY AND IMPLEMENTATION Source code is part of the C++ Energy Landscape Library available at http://www.bioinf.uni-freiburg.de/Software/.
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Affiliation(s)
- Martin Mann
- Bioinformatics Group, Department of Computer Science, University of Freiburg, 79110 Freiburg, Germany, Institute for Theoretical Chemistry, University of Vienna, 1090 Vienna, Center for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, University of Vienna, Medical University of Vienna, and Department of Biochemistry and Molecular Cell Biology, Max F. Perutz Laboratories, University of Vienna, A-1030 Vienna, Austria
| | - Marcel Kucharík
- Bioinformatics Group, Department of Computer Science, University of Freiburg, 79110 Freiburg, Germany, Institute for Theoretical Chemistry, University of Vienna, 1090 Vienna, Center for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, University of Vienna, Medical University of Vienna, and Department of Biochemistry and Molecular Cell Biology, Max F. Perutz Laboratories, University of Vienna, A-1030 Vienna, Austria
| | - Christoph Flamm
- Bioinformatics Group, Department of Computer Science, University of Freiburg, 79110 Freiburg, Germany, Institute for Theoretical Chemistry, University of Vienna, 1090 Vienna, Center for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, University of Vienna, Medical University of Vienna, and Department of Biochemistry and Molecular Cell Biology, Max F. Perutz Laboratories, University of Vienna, A-1030 Vienna, Austria
| | - Michael T Wolfinger
- Bioinformatics Group, Department of Computer Science, University of Freiburg, 79110 Freiburg, Germany, Institute for Theoretical Chemistry, University of Vienna, 1090 Vienna, Center for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, University of Vienna, Medical University of Vienna, and Department of Biochemistry and Molecular Cell Biology, Max F. Perutz Laboratories, University of Vienna, A-1030 Vienna, Austria Bioinformatics Group, Department of Computer Science, University of Freiburg, 79110 Freiburg, Germany, Institute for Theoretical Chemistry, University of Vienna, 1090 Vienna, Center for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, University of Vienna, Medical University of Vienna, and Department of Biochemistry and Molecular Cell Biology, Max F. Perutz Laboratories, University of Vienna, A-1030 Vienna, Austria Bioinformatics Group, Department of Computer Science, University of Freiburg, 79110 Freiburg, Germany, Institute for Theoretical Chemistry, University of Vienna, 1090 Vienna, Center for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, University of Vienna, Medical University of Vienna, and Department of Biochemistry and Molecular Cell Biology, Max F. Perutz Laboratories, University of Vienna, A-1030 Vienna, Austria
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34
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Dotu I, Garcia-Martin JA, Slinger BL, Mechery V, Meyer MM, Clote P. Complete RNA inverse folding: computational design of functional hammerhead ribozymes. Nucleic Acids Res 2014; 42:11752-62. [PMID: 25209235 PMCID: PMC4191386 DOI: 10.1093/nar/gku740] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Nanotechnology and synthetic biology currently constitute one of the most innovative, interdisciplinary fields of research, poised to radically transform society in the 21st century. This paper concerns the synthetic design of ribonucleic acid molecules, using our recent algorithm, RNAiFold, which can determine all RNA sequences whose minimum free energy secondary structure is a user-specified target structure. Using RNAiFold, we design ten cis-cleaving hammerhead ribozymes, all of which are shown to be functional by a cleavage assay. We additionally use RNAiFold to design a functional cis-cleaving hammerhead as a modular unit of a synthetic larger RNA. Analysis of kinetics on this small set of hammerheads suggests that cleavage rate of computationally designed ribozymes may be correlated with positional entropy, ensemble defect, structural flexibility/rigidity and related measures. Artificial ribozymes have been designed in the past either manually or by SELEX (Systematic Evolution of Ligands by Exponential Enrichment); however, this appears to be the first purely computational design and experimental validation of novel functional ribozymes. RNAiFold is available at http://bioinformatics.bc.edu/clotelab/RNAiFold/.
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Affiliation(s)
- Ivan Dotu
- Biology Department, Boston College, 140 Commonwealth Avenue, Chestnut Hill, MA 02467, USA
| | | | - Betty L Slinger
- Biology Department, Boston College, 140 Commonwealth Avenue, Chestnut Hill, MA 02467, USA
| | - Vinodh Mechery
- Hofstra North Shore-LIJ School of Medicine, Hempstead, NY 11549, USA
| | - Michelle M Meyer
- Biology Department, Boston College, 140 Commonwealth Avenue, Chestnut Hill, MA 02467, USA
| | - Peter Clote
- Biology Department, Boston College, 140 Commonwealth Avenue, Chestnut Hill, MA 02467, USA
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35
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36
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Huang J, Voß B. Analysing RNA-kinetics based on folding space abstraction. BMC Bioinformatics 2014; 15:60. [PMID: 24575751 PMCID: PMC3974018 DOI: 10.1186/1471-2105-15-60] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2013] [Accepted: 02/24/2014] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND RNA molecules, especially non-coding RNAs, play vital roles in the cell and their biological functions are mostly determined by structural properties. Often, these properties are related to dynamic changes in the structure, as in the case of riboswitches, and thus the analysis of RNA folding kinetics is crucial for their study. Exact approaches to kinetic folding are computationally expensive and, thus, limited to short sequences. In a previous study, we introduced a position-specific abstraction based on helices which we termed helix index shapes (hishapes) and a hishape-based algorithm for near-optimal folding pathway computation, called HiPath. The combination of these approaches provides an abstract view of the folding space that offers information about the global features. RESULTS In this paper we present HiKinetics, an algorithm that can predict RNA folding kinetics for sequences up to several hundred nucleotides long. This algorithm is based on RNAHeliCes, which decomposes the folding space into abstract classes, namely hishapes, and an improved version of HiPath, namely HiPath2, which estimates plausible folding pathways that connect these classes. Furthermore, we analyse the relationship of hishapes to locally optimal structures, the results of which strengthen the use of the hishape abstraction for studying folding kinetics. Finally, we show the application of HiKinetics to the folding kinetics of two well-studied RNAs. CONCLUSIONS HiKinetics can calculate kinetic folding based on a novel hishape decomposition. HiKinetics, together with HiPath2 and RNAHeliCes, is available for download at http://www.cyanolab.de/software/RNAHeliCes.htm.
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Affiliation(s)
- Jiabin Huang
- Genetics & Experimental Bioinformatics, Faculty of Biology, University of Freiburg, Schänzlestr. 1, 79104, Freiburg, Germany
| | - Björn Voß
- Genetics & Experimental Bioinformatics, Faculty of Biology, University of Freiburg, Schänzlestr. 1, 79104, Freiburg, Germany
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37
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Senter E, Dotu I, Clote P. RNA folding pathways and kinetics using 2D energy landscapes. J Math Biol 2014; 70:173-96. [PMID: 24515409 DOI: 10.1007/s00285-014-0760-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2013] [Revised: 09/26/2013] [Indexed: 11/27/2022]
Abstract
RNA folding pathways play an important role in various biological processes, such as (i) the hok/sok (host-killing/suppression of killing) system in E. coli to check for sufficient plasmid copy number, (ii) the conformational switch in spliced leader (SL) RNA from Leptomonas collosoma, which controls trans splicing of a portion of the '5 exon, and (iii) riboswitches--portions of the 5' untranslated region of messenger RNA that regulate genes by allostery. Since RNA folding pathways are determined by the energy landscape, we describe a novel algorithm, FFTbor2D, which computes the 2D projection of the energy landscape for a given RNA sequence. Given two metastable secondary structures A, B for a given RNA sequence, FFTbor2D computes the Boltzmann probability p(x, y) = Z(x,y)/Z that a secondary structure has base pair distance x from A and distance y from B. Using polynomial interpolationwith the fast Fourier transform,we compute p(x, y) in O(n(5)) time and O(n(2)) space, which is an improvement over an earlier method, which runs in O(n(7)) time and O(n(4)) space. FFTbor2D has potential applications in synthetic biology, where one might wish to design bistable switches having target metastable structures A, B with favorable pathway kinetics. By inverting the transition probability matrix determined from FFTbor2D output, we show that L. collosoma spliced leader RNA has larger mean first passage time from A to B on the 2D energy landscape, than 97.145% of 20,000 sequences, each having metastable structures A, B. Source code and binaries are freely available for download at http://bioinformatics.bc.edu/clotelab/FFTbor2D. The program FFTbor2D is implemented in C++, with optional OpenMP parallelization primitives.
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Affiliation(s)
- Evan Senter
- Department of Biology, Boston College, Chestnut Hill, MA, 02467, USA
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38
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Garcia-Martin JA, Clote P, Dotu I. RNAiFOLD: a constraint programming algorithm for RNA inverse folding and molecular design. J Bioinform Comput Biol 2013; 11:1350001. [PMID: 23600819 DOI: 10.1142/s0219720013500017] [Citation(s) in RCA: 59] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Synthetic biology is a rapidly emerging discipline with long-term ramifications that range from single-molecule detection within cells to the creation of synthetic genomes and novel life forms. Truly phenomenal results have been obtained by pioneering groups--for instance, the combinatorial synthesis of genetic networks, genome synthesis using BioBricks, and hybridization chain reaction (HCR), in which stable DNA monomers assemble only upon exposure to a target DNA fragment, biomolecular self-assembly pathways, etc. Such work strongly suggests that nanotechnology and synthetic biology together seem poised to constitute the most transformative development of the 21st century. In this paper, we present a Constraint Programming (CP) approach to solve the RNA inverse folding problem. Given a target RNA secondary structure, we determine an RNA sequence which folds into the target structure; i.e. whose minimum free energy structure is the target structure. Our approach represents a step forward in RNA design--we produce the first complete RNA inverse folding approach which allows for the specification of a wide range of design constraints. We also introduce a Large Neighborhood Search approach which allows us to tackle larger instances at the cost of losing completeness, while retaining the advantages of meeting design constraints (motif, GC-content, etc.). Results demonstrate that our software, RNAiFold, performs as well or better than all state-of-the-art approaches; nevertheless, our approach is unique in terms of completeness, flexibility, and the support of various design constraints. The algorithms presented in this paper are publicly available via the interactive webserver http://bioinformatics.bc.edu/clotelab/RNAiFold; additionally, the source code can be downloaded from that site.
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39
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Senter E, Sheikh S, Dotu I, Ponty Y, Clote P. Using the fast fourier transform to accelerate the computational search for RNA conformational switches. PLoS One 2012; 7:e50506. [PMID: 23284639 PMCID: PMC3526635 DOI: 10.1371/journal.pone.0050506] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2012] [Accepted: 10/26/2012] [Indexed: 01/12/2023] Open
Abstract
Using complex roots of unity and the Fast Fourier Transform, we design a new thermodynamics-based algorithm, FFTbor, that computes the Boltzmann probability that secondary structures differ by base pairs from an arbitrary initial structure of a given RNA sequence. The algorithm, which runs in quartic time and quadratic space , is used to determine the correlation between kinetic folding speed and the ruggedness of the energy landscape, and to predict the location of riboswitch expression platform candidates. A web server is available at http://bioinformatics.bc.edu/clotelab/FFTbor/.
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Affiliation(s)
- Evan Senter
- Biology Department, Boston College, Chestnut Hill, Massachusetts, United States of America
| | - Saad Sheikh
- Computer Science Department, University of Florida, Gainesville, Florida, United States of America
| | - Ivan Dotu
- Biology Department, Boston College, Chestnut Hill, Massachusetts, United States of America
| | - Yann Ponty
- Laboratoire d'Informatique, Ecole Polytechnique, Palaiseau, France
| | - Peter Clote
- Biology Department, Boston College, Chestnut Hill, Massachusetts, United States of America
- * E-mail:
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40
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Huang J, Backofen R, Voß B. Abstract folding space analysis based on helices. RNA (NEW YORK, N.Y.) 2012; 18:2135-2147. [PMID: 23104999 PMCID: PMC3504666 DOI: 10.1261/rna.033548.112] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2012] [Accepted: 09/24/2012] [Indexed: 06/01/2023]
Abstract
RNA has many pivotal functions especially in the regulation of gene expression by ncRNAs. Identification of their structure is an important requirement for understanding their function. Structure prediction alone is often insufficient for this task, due to algorithmic problems, parameter inaccuracies, and biological peculiarities. Among the latter, there are base modifications, cotranscriptional folding leading to folding traps, and conformational switching as in the case of riboswitches. All these require more in-depth analysis of the folding space. The major drawback, which all methods have to cope with, is the exponential growth of the folding space. Therefore, methods are often limited in the sequence length they can analyze, or they make use of heuristics, sampling, or abstraction. Our approach adopts the abstraction strategy and remedies some problems of existing methods. We introduce a position-specific abstraction based on helices that we term helix index shapes, or hishapes for short. Utilizing a dynamic programming framework, we have implemented this abstraction in the program RNAHeliCes. Furthermore, we developed two hishape-based methods, one for energy barrier estimation, called HiPath, and one for abstract structure comparison, termed HiTed. We demonstrate the superior performance of HiPath compared to other existing methods and the competitive accuracy of HiTed. RNAHeliCes, together with HiPath and HiTed, are available for download at http://www.cyanolab.de/software/RNAHeliCes.htm.
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Affiliation(s)
- Jiabin Huang
- Genetics & Experimental Bioinformatics, Faculty of Biology, University of Freiburg, Freiburg 79104, Germany
| | - Rolf Backofen
- Chair for Bioinformatics, Faculty of Technology, University of Freiburg, Freiburg 79110, Germany
| | - Björn Voß
- Genetics & Experimental Bioinformatics, Faculty of Biology, University of Freiburg, Freiburg 79104, Germany
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41
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Lyngsø RB, Anderson JWJ, Sizikova E, Badugu A, Hyland T, Hein J. Frnakenstein: multiple target inverse RNA folding. BMC Bioinformatics 2012; 13:260. [PMID: 23043260 PMCID: PMC3534541 DOI: 10.1186/1471-2105-13-260] [Citation(s) in RCA: 52] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2012] [Accepted: 09/23/2012] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND RNA secondary structure prediction, or folding, is a classic problem in bioinformatics: given a sequence of nucleotides, the aim is to predict the base pairs formed in its three dimensional conformation. The inverse problem of designing a sequence folding into a particular target structure has only more recently received notable interest. With a growing appreciation and understanding of the functional and structural properties of RNA motifs, and a growing interest in utilising biomolecules in nano-scale designs, the interest in the inverse RNA folding problem is bound to increase. However, whereas the RNA folding problem from an algorithmic viewpoint has an elegant and efficient solution, the inverse RNA folding problem appears to be hard. RESULTS In this paper we present a genetic algorithm approach to solve the inverse folding problem. The main aims of the development was to address the hitherto mostly ignored extension of solving the inverse folding problem, the multi-target inverse folding problem, while simultaneously designing a method with superior performance when measured on the quality of designed sequences. The genetic algorithm has been implemented as a Python program called Frnakenstein. It was benchmarked against four existing methods and several data sets totalling 769 real and predicted single structure targets, and on 292 two structure targets. It performed as well as or better at finding sequences which folded in silico into the target structure than all existing methods, without the heavy bias towards CG base pairs that was observed for all other top performing methods. On the two structure targets it also performed well, generating a perfect design for about 80% of the targets. CONCLUSIONS Our method illustrates that successful designs for the inverse RNA folding problem does not necessarily have to rely on heavy biases in base pair and unpaired base distributions. The design problem seems to become more difficult on larger structures when the target structures are real structures, while no deterioration was observed for predicted structures. Design for two structure targets is considerably more difficult, but far from impossible, demonstrating the feasibility of automated design of artificial riboswitches. The Python implementation is available at http://www.stats.ox.ac.uk/research/genome/software/frnakenstein.
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Affiliation(s)
- Rune B Lyngsø
- Department of Statistics, University of Oxford, Oxford OX1 3TG, UK
| | | | - Elena Sizikova
- Department of Computer Science, University of Oxford, Oxford OX1 3QD, UK
| | - Amarendra Badugu
- ETH Zürich, Department of Biosystems Science and Engineering, 4058 Basel, Switzerland
| | - Tomas Hyland
- Mathematics Institute, University of Oxford, Oxford OX1 3LB, UK
| | - Jotun Hein
- Department of Statistics, University of Oxford, Oxford OX1 3TG, UK
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42
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Bompfünewerer AF, Flamm C, Fried C, Fritzsch G, Hofacker IL, Lehmann J, Missal K, Mosig A, Müller B, Prohaska SJ, Stadler BMR, Stadler PF, Tanzer A, Washietl S, Witwer C. Evolutionary patterns of non-coding RNAs. Theory Biosci 2012; 123:301-69. [PMID: 18202870 DOI: 10.1016/j.thbio.2005.01.002] [Citation(s) in RCA: 59] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2004] [Accepted: 01/24/2005] [Indexed: 01/04/2023]
Abstract
A plethora of new functions of non-coding RNAs (ncRNAs) have been discovered in past few years. In fact, RNA is emerging as the central player in cellular regulation, taking on active roles in multiple regulatory layers from transcription, RNA maturation, and RNA modification to translational regulation. Nevertheless, very little is known about the evolution of this "Modern RNA World" and its components. In this contribution, we attempt to provide at least a cursory overview of the diversity of ncRNAs and functional RNA motifs in non-translated regions of regular messenger RNAs (mRNAs) with an emphasis on evolutionary questions. This survey is complemented by an in-depth analysis of examples from different classes of RNAs focusing mostly on their evolution in the vertebrate lineage. We present a survey of Y RNA genes in vertebrates and study the molecular evolution of the U7 snRNA, the snoRNAs E1/U17, E2, and E3, the Y RNA family, the let-7 microRNA (miRNA) family, and the mRNA-like evf-1 gene. We furthermore discuss the statistical distribution of miRNAs in metazoans, which suggests an explosive increase in the miRNA repertoire in vertebrates. The analysis of the transcription of ncRNAs suggests that small RNAs in general are genetically mobile in the sense that their association with a hostgene (e.g. when transcribed from introns of a mRNA) can change on evolutionary time scales. The let-7 family demonstrates, that even the mode of transcription (as intron or as exon) can change among paralogous ncRNA.
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43
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Rodrigo G, Fares MA. Describing the structural robustness landscape of bacterial small RNAs. BMC Evol Biol 2012; 12:52. [PMID: 22500888 PMCID: PMC3368786 DOI: 10.1186/1471-2148-12-52] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2012] [Accepted: 04/13/2012] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The potential role of RNA molecules as gene expression regulators has led to a new perspective on the intracellular control and genome organization. Because secondary structures are crucial for their regulatory role, we sought to investigate their robustness to mutations and environmental changes. RESULTS Here, we dissected the structural robustness landscape of the small non-coding RNAs (sncRNAs) encoded in the genome of the bacterium Escherichia coli. We found that bacterial sncRNAs are not significantly robust to both mutational and environmental perturbations when compared against artificial, unbiased sequences. However, we found that, on average, bacterial sncRNAs tend to be significantly plastic, and that mutational and environmental robustness strongly correlate. We further found that, on average, epistasis in bacterial sncRNAs is significantly antagonistic, and positively correlates with plasticity. Moreover, the evolution of robustness is likely dependent upon the environmental stability of the cell, with more fluctuating environments leading to the emergence and fixation of more robust molecules. Mutational robustness also appears to be correlated with structural functionality and complexity. CONCLUSION Our study provides a deep characterization of the structural robustness landscape of bacterial sncRNAs, suggesting that evolvability could be evolved as a consequence of selection for more plastic molecules. It also supports that environmental fluctuations could promote mutational robustness. As a result, plasticity emerges to link robustness, functionality and evolvability.
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Affiliation(s)
- Guillermo Rodrigo
- Instituto de Biología Molecular y Celular de Plantas, Consejo Superior de Investigaciones Científicas, Universidad Politécnica de Valencia, Ingeniero Fausto Elio s/n, 46022 Valencia, Spain.
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Li Y, Zhang S. Predicting folding pathways between RNA conformational structures guided by RNA stacks. BMC Bioinformatics 2012; 13 Suppl 3:S5. [PMID: 22536903 PMCID: PMC3402921 DOI: 10.1186/1471-2105-13-s3-s5] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Accurately predicting low energy barrier folding pathways between conformational secondary structures of an RNA molecule can provide valuable information for understanding its catalytic and regulatory functions. Most existing heuristic algorithms guide the construction of folding pathways by free energies of intermediate structures in the next move during the folding. However due to the size and ruggedness of RNA energy landscape, energy-guided search can become trapped in local optima. RESULTS In this paper, we propose an algorithm that guides the construction of folding pathways through the formation and destruction of RNA stacks. Guiding the construction of folding pathways by coarse grained movements of RNA stacks can help reduce the search space and make it easier to jump out of local optima. RNAEAPath is able to find lower energy barrier folding pathways between secondary structures of conformational switches and outperforms the existing heuristic algorithms in most test cases. CONCLUSIONS RNAEAPath provides an alternate approach for predicting low-barrier folding pathways between RNA conformational secondary structures. The source code of RNAEAPath and the test data sets are available at http://genome.ucf.edu/RNAEAPath.
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Affiliation(s)
- Yuan Li
- Department of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL 32816-2362, USA
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Okada Y, Saito Y, Sato K, Sakakibara Y. Improved measurements of RNA structure conservation with generalized centroid estimators. Front Genet 2012; 2:54. [PMID: 22303350 PMCID: PMC3268607 DOI: 10.3389/fgene.2011.00054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2011] [Accepted: 08/08/2011] [Indexed: 11/13/2022] Open
Abstract
Identification of non-protein-coding RNAs (ncRNAs) in genomes is a crucial task for not only molecular cell biology but also bioinformatics. Secondary structures of ncRNAs are employed as a key feature of ncRNA analysis since biological functions of ncRNAs are deeply related to their secondary structures. Although the minimum free energy (MFE) structure of an RNA sequence is regarded as the most stable structure, MFE alone could not be an appropriate measure for identifying ncRNAs since the free energy is heavily biased by the nucleotide composition. Therefore, instead of MFE itself, several alternative measures for identifying ncRNAs have been proposed such as the structure conservation index (SCI) and the base pair distance (BPD), both of which employ MFE structures. However, these measurements are unfortunately not suitable for identifying ncRNAs in some cases including the genome-wide search and incur high false discovery rate. In this study, we propose improved measurements based on SCI and BPD, applying generalized centroid estimators to incorporate the robustness against low quality multiple alignments. Our experiments show that our proposed methods achieve higher accuracy than the original SCI and BPD for not only human-curated structural alignments but also low quality alignments produced by CLUSTAL W. Furthermore, the centroid-based SCI on CLUSTAL W alignments is more accurate than or comparable with that of the original SCI on structural alignments generated with RAF, a high quality structural aligner, for which twofold expensive computational time is required on average. We conclude that our methods are more suitable for genome-wide alignments which are of low quality from the point of view on secondary structures than the original SCI and BPD.
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Affiliation(s)
- Yohei Okada
- Department of Biosciences and Informatics, Keio University Yokohama, Japan
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Lorenz R, Bernhart SH, Höner zu Siederdissen C, Tafer H, Flamm C, Stadler PF, Hofacker IL. ViennaRNA Package 2.0. Algorithms Mol Biol 2011; 6:26. [PMID: 22115189 PMCID: PMC3319429 DOI: 10.1186/1748-7188-6-26] [Citation(s) in RCA: 2910] [Impact Index Per Article: 223.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2011] [Accepted: 11/24/2011] [Indexed: 12/31/2022] Open
Abstract
Background Secondary structure forms an important intermediate level of description of nucleic acids that encapsulates the dominating part of the folding energy, is often well conserved in evolution, and is routinely used as a basis to explain experimental findings. Based on carefully measured thermodynamic parameters, exact dynamic programming algorithms can be used to compute ground states, base pairing probabilities, as well as thermodynamic properties. Results The ViennaRNA Package has been a widely used compilation of RNA secondary structure related computer programs for nearly two decades. Major changes in the structure of the standard energy model, the Turner 2004 parameters, the pervasive use of multi-core CPUs, and an increasing number of algorithmic variants prompted a major technical overhaul of both the underlying RNAlib and the interactive user programs. New features include an expanded repertoire of tools to assess RNA-RNA interactions and restricted ensembles of structures, additional output information such as centroid structures and maximum expected accuracy structures derived from base pairing probabilities, or z-scores for locally stable secondary structures, and support for input in fasta format. Updates were implemented without compromising the computational efficiency of the core algorithms and ensuring compatibility with earlier versions. Conclusions The ViennaRNA Package 2.0, supporting concurrent computations via OpenMP, can be downloaded from http://www.tbi.univie.ac.at/RNA.
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Spitzer R, Kloiber K, Tollinger M, Kreutz C. Kinetics of DNA refolding from longitudinal exchange NMR spectroscopy. Chembiochem 2011; 12:2007-10. [PMID: 21739562 DOI: 10.1002/cbic.201100318] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2011] [Indexed: 12/22/2022]
Affiliation(s)
- Romana Spitzer
- Institute of Organic Chemistry, University of Innsbruck, Innrain 52a, 6020 Innsbruck, Austria
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Design of interacting multi-stable nucleic acids for molecular information processing. Biosystems 2011; 105:14-24. [PMID: 21396427 DOI: 10.1016/j.biosystems.2011.02.006] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2011] [Revised: 02/28/2011] [Accepted: 02/28/2011] [Indexed: 11/23/2022]
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Shukla GC, Haque F, Tor Y, Wilhelmsson LM, Toulmé JJ, Isambert H, Guo P, Rossi JJ, Tenenbaum SA, Shapiro BA. A boost for the emerging field of RNA nanotechnology. ACS NANO 2011; 5:3405-18. [PMID: 21604810 PMCID: PMC3102291 DOI: 10.1021/nn200989r] [Citation(s) in RCA: 80] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
This Nano Focus article highlights recent advances in RNA nanotechnology as presented at the First International Conference of RNA Nanotechnology and Therapeutics, which took place in Cleveland, OH, USA (October 23-25, 2010) ( http://www.eng.uc.edu/nanomedicine/RNA2010/ ), chaired by Peixuan Guo and co-chaired by David Rueda and Scott Tenenbaum. The conference was the first of its kind to bring together more than 30 invited speakers in the frontier of RNA nanotechnology from France, Sweden, South Korea, China, and throughout the United States to discuss RNA nanotechnology and its applications. It provided a platform for researchers from academia, government, and the pharmaceutical industry to share existing knowledge, vision, technology, and challenges in the field and promoted collaborations among researchers interested in advancing this emerging scientific discipline. The meeting covered a range of topics, including biophysical and single-molecule approaches for characterization of RNA nanostructures; structure studies on RNA nanoparticles by chemical or biochemical approaches, computation, prediction, and modeling of RNA nanoparticle structures; methods for the assembly of RNA nanoparticles; chemistry for RNA synthesis, conjugation, and labeling; and application of RNA nanoparticles in therapeutics. A special invited talk on the well-established principles of DNA nanotechnology was arranged to provide models for RNA nanotechnology. An Administrator from National Institutes of Health (NIH) National Cancer Institute (NCI) Alliance for Nanotechnology in Cancer discussed the current nanocancer research directions and future funding opportunities at NCI. As indicated by the feedback received from the invited speakers and the meeting participants, this meeting was extremely successful, exciting, and informative, covering many groundbreaking findings, pioneering ideas, and novel discoveries.
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Affiliation(s)
- Girish C. Shukla
- Center for Gene Regulation in Health and Disease, Department of Biological Sciences, Cleveland State University, Cleveland, Ohio 44115, United States
| | - Farzin Haque
- Nanobiomedical Center, College of Engineering and Applied Science, and College of Medicine, University of Cincinnati, Cincinnati, Ohio 45267, United States
| | - Yitzhak Tor
- Department of Chemistry & Biochemistry, University of California, San Diego, La Jolla, California 92093, United States
| | - L. Marcus Wilhelmsson
- Department of Chemical and Biological Engineering/Physical Chemistry, Chalmers University of Technology, Kemivägen 10, SE-412 96 Göteborg, Sweden
| | - Jean-Jacques Toulmé
- Université Bordeaux Segalen, INSERM U869, Bâtiment 3A 1er étage, 33076 Bordeaux Cedex, France
| | - Hervé Isambert
- Institut Curie, Research Division, CNRS UMR 168, 11 rue P. & M. Curie, 75005 Paris, France
| | - Peixuan Guo
- Nanobiomedical Center, College of Engineering and Applied Science, and College of Medicine, University of Cincinnati, Cincinnati, Ohio 45267, United States
| | - John J. Rossi
- Department of Molecular and Cellular Biology, Beckman Research Institute of City of Hope, Duarte, California 91010, United States
| | - Scott A. Tenenbaum
- College of Nanoscale Science & Engineering, University at Albany-SUNY, Albany, New York 12203, United States
| | - Bruce A. Shapiro
- Center for Cancer Research Nanobiology Program, National Cancer Institute at Frederick, Frederick, Maryland 21702, United States
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