GRODECKÁ, Lucie, Pavla LOCKEROVÁ, Barbora RAVČUKOVÁ, Emanuele BURATTI, Francisco E. BARALLE, Ladislav DUŠEK and Tomáš FREIBERGER. Exon First Nucleotide Mutations in Splicing: Evaluation of In Silico Prediction Tools. PLoS One. SAN FRANCISCO: PUBLIC LIBRARY SCIENCE, vol. 9, No 2, p. "nestránkováno", 13 pp. ISSN 1932-6203. doi:10.1371/journal.pone.0089570. 2014.
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Basic information
Original name Exon First Nucleotide Mutations in Splicing: Evaluation of In Silico Prediction Tools
Authors GRODECKÁ, Lucie (203 Czech Republic, belonging to the institution), Pavla LOCKEROVÁ (203 Czech Republic), Barbora RAVČUKOVÁ (203 Czech Republic), Emanuele BURATTI (380 Italy), Francisco E. BARALLE (380 Italy), Ladislav DUŠEK (203 Czech Republic, belonging to the institution) and Tomáš FREIBERGER (203 Czech Republic, guarantor, belonging to the institution).
Edition PLoS One, SAN FRANCISCO, PUBLIC LIBRARY SCIENCE, 2014, 1932-6203.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 30000 3. Medical and Health Sciences
Country of publisher United Kingdom of Great Britain and Northern Ireland
Confidentiality degree is not subject to a state or trade secret
WWW URL
Impact factor Impact factor: 3.234
RIV identification code RIV/00216224:14740/14:00075261
Organization unit Central European Institute of Technology
Doi http://dx.doi.org/10.1371/journal.pone.0089570
UT WoS 000331717900122
Keywords in English POLYPYRIMIDINE TRACT RECOGNITION; HUMAN-DISEASE GENES; CONFORMATIONAL SELECTION; COMPUTATIONAL TOOLS; SEQUENCE MOTIFS; FACTOR U2AF(35); MSH2 MISSENSE; SITE; ENHANCERS; U2AF(65)
Tags EL OK, kontrola MP, OA, ok, podil, rivok
Tags International impact, Reviewed
Changed by Changed by: Martina Prášilová, učo 342282. Changed: 18/12/2014 09:52.
Abstract
Mutations in the first nucleotide of exons (E+1) mostly affect pre-mRNA splicing when found in AG-dependent 39 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 39 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.
Links
ED1.1.00/02.0068, research and development projectName: CEITEC - central european institute of technology
EE2.3.20.0045, research and development projectName: Podpora profesního růstu a mezinárodní integrace výzkumných týmů v oblasti molekulární medicíny
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