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 qual...

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Autores principales:	Lucie Grodecká, Pavla Lockerová, Barbora Ravčuková, Emanuele Buratti, Francisco E Baralle, Ladislav Dušek, Tomáš Freiberger
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2014
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/1a828e23d9c641e8b2d7b6964207b25e
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spelling	oai:doaj.org-article:1a828e23d9c641e8b2d7b6964207b25e2021-11-18T08:31:28ZExon first nucleotide mutations in splicing: evaluation of in silico prediction tools.1932-620310.1371/journal.pone.0089570https://doaj.org/article/1a828e23d9c641e8b2d7b6964207b25e2014-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24586880/?tool=EBIhttps://doaj.org/toc/1932-6203Mutations 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.Lucie GrodeckáPavla LockerováBarbora RavčukováEmanuele BurattiFrancisco E BaralleLadislav DušekTomáš FreibergerPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 9, Iss 2, p e89570 (2014)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Lucie Grodecká Pavla Lockerová Barbora Ravčuková Emanuele Buratti Francisco E Baralle Ladislav Dušek Tomáš Freiberger Exon first nucleotide mutations in splicing: evaluation of in silico prediction tools.
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	article
author	Lucie Grodecká Pavla Lockerová Barbora Ravčuková Emanuele Buratti Francisco E Baralle Ladislav Dušek Tomáš Freiberger
author_facet	Lucie Grodecká Pavla Lockerová Barbora Ravčuková Emanuele Buratti Francisco E Baralle Ladislav Dušek Tomáš Freiberger
author_sort	Lucie Grodecká
title	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_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_sort	exon first nucleotide mutations in splicing: evaluation of in silico prediction tools.
publisher	Public Library of Science (PLoS)
publishDate	2014
url	https://doaj.org/article/1a828e23d9c641e8b2d7b6964207b25e
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Exon first nucleotide mutations in splicing: evaluation of in silico prediction tools.

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