Exon first nucleotide mutations in splicing: evaluation of in silico prediction tools
Jazyk angličtina Země Spojené státy americké Médium electronic-ecollection
Typ dokumentu hodnotící studie, časopisecké články, práce podpořená grantem
PubMed
24586880
PubMed Central
PMC3931810
DOI
10.1371/journal.pone.0089570
PII: PONE-D-13-39583
Knihovny.cz E-zdroje
- MeSH
- agamaglobulinemie genetika MeSH
- bodová mutace * MeSH
- exony MeSH
- genetické nemoci vázané na chromozom X genetika MeSH
- HeLa buňky MeSH
- lidé MeSH
- místa sestřihu RNA * MeSH
- modely genetické MeSH
- molekulární sekvence - údaje MeSH
- počítačová simulace MeSH
- proteinkinasa BTK MeSH
- sekvenční analýza DNA MeSH
- sestřih RNA MeSH
- software * MeSH
- tyrosinkinasy genetika MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- hodnotící studie MeSH
- práce podpořená grantem MeSH
- Názvy látek
- místa sestřihu RNA * MeSH
- proteinkinasa BTK MeSH
- tyrosinkinasy MeSH
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.
Institute of Biostatistics and Analyses Masaryk University Brno Czech Republic
International Centre for Genetic Engineering and Biotechnology Trieste Italy
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