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Modified RNAs and predictions with the ViennaRNA Package
MOTIVATION: In living organisms, many RNA molecules are modified post-transcriptionally. This turns the widely known four-letter RNA alphabet ACGU into a much larger one with currently more than 300 known distinct modified bases. The roles for the majority of modified bases remain uncertain, but man...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10676514/ https://www.ncbi.nlm.nih.gov/pubmed/37971965 http://dx.doi.org/10.1093/bioinformatics/btad696 |
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author | Varenyk, Yuliia Spicher, Thomas Hofacker, Ivo L Lorenz, Ronny |
author_facet | Varenyk, Yuliia Spicher, Thomas Hofacker, Ivo L Lorenz, Ronny |
author_sort | Varenyk, Yuliia |
collection | PubMed |
description | MOTIVATION: In living organisms, many RNA molecules are modified post-transcriptionally. This turns the widely known four-letter RNA alphabet ACGU into a much larger one with currently more than 300 known distinct modified bases. The roles for the majority of modified bases remain uncertain, but many are already well-known for their ability to influence the preferred structures that an RNA may adopt. In fact, tRNAs sometimes require certain modifications to fold into their cloverleaf shaped structure. However, predicting the structure of RNAs with base modifications is still difficult due to the lack of efficient algorithms that can deal with the extended sequence alphabet, as well as missing parameter sets that account for the changes in stability induced by the modified bases. RESULTS: We present an approach to include sparse energy parameter data for modified bases into the ViennaRNA Package. Our method does not require any changes to the underlying efficient algorithms but instead uses a set of plug-in constraints that adapt the predictions in terms of loop evaluation at runtime. These adaptations are efficient in the sense that they are only performed for loops where additional parameters are actually available for. In addition, our approach also facilitates the inclusion of more modified bases as soon as further parameters become available. AVAILABILITY AND IMPLEMENTATION: Source code and documentation are available at https://www.tbi.univie.ac.at/RNA. |
format | Online Article Text |
id | pubmed-10676514 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-106765142023-11-16 Modified RNAs and predictions with the ViennaRNA Package Varenyk, Yuliia Spicher, Thomas Hofacker, Ivo L Lorenz, Ronny Bioinformatics Applications Note MOTIVATION: In living organisms, many RNA molecules are modified post-transcriptionally. This turns the widely known four-letter RNA alphabet ACGU into a much larger one with currently more than 300 known distinct modified bases. The roles for the majority of modified bases remain uncertain, but many are already well-known for their ability to influence the preferred structures that an RNA may adopt. In fact, tRNAs sometimes require certain modifications to fold into their cloverleaf shaped structure. However, predicting the structure of RNAs with base modifications is still difficult due to the lack of efficient algorithms that can deal with the extended sequence alphabet, as well as missing parameter sets that account for the changes in stability induced by the modified bases. RESULTS: We present an approach to include sparse energy parameter data for modified bases into the ViennaRNA Package. Our method does not require any changes to the underlying efficient algorithms but instead uses a set of plug-in constraints that adapt the predictions in terms of loop evaluation at runtime. These adaptations are efficient in the sense that they are only performed for loops where additional parameters are actually available for. In addition, our approach also facilitates the inclusion of more modified bases as soon as further parameters become available. AVAILABILITY AND IMPLEMENTATION: Source code and documentation are available at https://www.tbi.univie.ac.at/RNA. Oxford University Press 2023-11-16 /pmc/articles/PMC10676514/ /pubmed/37971965 http://dx.doi.org/10.1093/bioinformatics/btad696 Text en © The Author(s) 2023. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Note Varenyk, Yuliia Spicher, Thomas Hofacker, Ivo L Lorenz, Ronny Modified RNAs and predictions with the ViennaRNA Package |
title | Modified RNAs and predictions with the ViennaRNA Package |
title_full | Modified RNAs and predictions with the ViennaRNA Package |
title_fullStr | Modified RNAs and predictions with the ViennaRNA Package |
title_full_unstemmed | Modified RNAs and predictions with the ViennaRNA Package |
title_short | Modified RNAs and predictions with the ViennaRNA Package |
title_sort | modified rnas and predictions with the viennarna package |
topic | Applications Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10676514/ https://www.ncbi.nlm.nih.gov/pubmed/37971965 http://dx.doi.org/10.1093/bioinformatics/btad696 |
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