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Exon First Nucleotide Mutations in Splicing: Evaluation of In Silico Prediction Tools
Mutations in the first nucleotide of exons (E(+1)) mostly affect pre-mRNA splicing when found in AG-dependent 3′ splice sites, whereas AG-independent splice sites are more resistant. The AG-dependency, however, may be difficult to assess just from primary sequence data as it depends on the quality o...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3931810/ https://www.ncbi.nlm.nih.gov/pubmed/24586880 http://dx.doi.org/10.1371/journal.pone.0089570 |
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author | Grodecká, Lucie Lockerová, Pavla Ravčuková, Barbora Buratti, Emanuele Baralle, Francisco E. Dušek, Ladislav Freiberger, Tomáš |
author_facet | Grodecká, Lucie Lockerová, Pavla Ravčuková, Barbora Buratti, Emanuele Baralle, Francisco E. Dušek, Ladislav Freiberger, Tomáš |
author_sort | Grodecká, Lucie |
collection | PubMed |
description | Mutations in the first nucleotide of exons (E(+1)) mostly affect pre-mRNA splicing when found in AG-dependent 3′ splice sites, whereas AG-independent splice sites are more resistant. The AG-dependency, however, may be difficult to assess just from primary sequence data as it depends on the quality of the polypyrimidine tract. For this reason, in silico prediction tools are commonly used to score 3′ splice sites. In this study, we have assessed the ability of sequence features and in silico prediction tools to discriminate between the splicing-affecting and non-affecting E(+1) variants. For this purpose, we newly tested 16 substitutions in vitro and derived other variants from literature. Surprisingly, we found that in the presence of the substituting nucleotide, the quality of the polypyrimidine tract alone was not conclusive about its splicing fate. Rather, it was the identity of the substituting nucleotide that markedly influenced it. Among the computational tools tested, the best performance was achieved using the Maximum Entropy Model and Position-Specific Scoring Matrix. As a result of this study, we have now established preliminary discriminative cut-off values showing sensitivity up to 95% and specificity up to 90%. This is expected to improve our ability to detect splicing-affecting variants in a clinical genetic setting. |
format | Online Article Text |
id | pubmed-3931810 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-39318102014-02-25 Exon First Nucleotide Mutations in Splicing: Evaluation of In Silico Prediction Tools Grodecká, Lucie Lockerová, Pavla Ravčuková, Barbora Buratti, Emanuele Baralle, Francisco E. Dušek, Ladislav Freiberger, Tomáš PLoS One Research Article Mutations in the first nucleotide of exons (E(+1)) mostly affect pre-mRNA splicing when found in AG-dependent 3′ splice sites, whereas AG-independent splice sites are more resistant. The AG-dependency, however, may be difficult to assess just from primary sequence data as it depends on the quality of the polypyrimidine tract. For this reason, in silico prediction tools are commonly used to score 3′ splice sites. In this study, we have assessed the ability of sequence features and in silico prediction tools to discriminate between the splicing-affecting and non-affecting E(+1) variants. For this purpose, we newly tested 16 substitutions in vitro and derived other variants from literature. Surprisingly, we found that in the presence of the substituting nucleotide, the quality of the polypyrimidine tract alone was not conclusive about its splicing fate. Rather, it was the identity of the substituting nucleotide that markedly influenced it. Among the computational tools tested, the best performance was achieved using the Maximum Entropy Model and Position-Specific Scoring Matrix. As a result of this study, we have now established preliminary discriminative cut-off values showing sensitivity up to 95% and specificity up to 90%. This is expected to improve our ability to detect splicing-affecting variants in a clinical genetic setting. Public Library of Science 2014-02-21 /pmc/articles/PMC3931810/ /pubmed/24586880 http://dx.doi.org/10.1371/journal.pone.0089570 Text en © 2014 Grodecka et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Grodecká, Lucie Lockerová, Pavla Ravčuková, Barbora Buratti, Emanuele Baralle, Francisco E. Dušek, Ladislav Freiberger, Tomáš Exon First Nucleotide Mutations in Splicing: Evaluation of In Silico Prediction Tools |
title | Exon First Nucleotide Mutations in Splicing: Evaluation of In Silico Prediction Tools |
title_full | Exon First Nucleotide Mutations in Splicing: Evaluation of In Silico Prediction Tools |
title_fullStr | Exon First Nucleotide Mutations in Splicing: Evaluation of In Silico Prediction Tools |
title_full_unstemmed | Exon First Nucleotide Mutations in Splicing: Evaluation of In Silico Prediction Tools |
title_short | Exon First Nucleotide Mutations in Splicing: Evaluation of In Silico Prediction Tools |
title_sort | exon first nucleotide mutations in splicing: evaluation of in silico prediction tools |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3931810/ https://www.ncbi.nlm.nih.gov/pubmed/24586880 http://dx.doi.org/10.1371/journal.pone.0089570 |
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