Publicação
Performance of in silico tools for the evaluation of UGT1A1 missense variants
| Resumo: | Variations in the gene encoding uridine diphosphate glucuronosyltransferase 1A1 (UGT1A1) are particularly important because they have been associated with hyperbilirubinemia in Gilbert’s and Crigler–Najjar syndromes as well as with changes in drug metabolism. Several variants associated with these phenotypes are nonsynonymous single-nucleotide polymorphisms (nsSNPs). Bioinformatics approaches have gained increasing importance in predicting the functional significance of these variants. This study was focused on the predictive ability of bioinformatics approaches to determine the pathogenicity of human UGT1A1 nsSNPs, which were previously characterized at the protein level by in vivo and in vitro studies. Using 16 Web algorithms, we evaluated 48 nsSNPs described in the literature and databases. Eight of these algorithms reached or exceeded 90% sensitivity and six presented a Matthews correlation coefficient above 0.46. The best-performing method was MutPred, followed by Sorting Intolerant from Tolerant (SIFT). The prediction measures varied significantly when predictors such us SIFT, polyphen-2, and Prediction of Pathological Mutations on Proteins were run with their native alignment generated by the tool, or with an input alignment that was strictly built with UGT1A1 orthologs and manually curated. Our results showed that the prediction performance of some methods based on sequence conservation analysis can be negatively affected when nsSNPs are positioned at the hypervariable or constant regions of UGT1A1 ortholog sequences. |
|---|---|
| Autores principais: | Rodrigues, Carina |
| Outros Autores: | Santos-Silva, Alice; Costa, Elísio; Bronze-da-Rocha, Elsa |
| Assunto: | nsSNPs Genotype Bioinformatics Phenotype Protein function |
| Ano: | 2015 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Instituto Politécnico de Bragança |
| Idioma: | inglês |
| Origem: | Biblioteca Digital do IPB |
| _version_ | 1867173368164253696 |
|---|---|
| author | Rodrigues, Carina |
| author2 | Santos-Silva, Alice Costa, Elísio Bronze-da-Rocha, Elsa |
| author2_role | author author author |
| author_facet | Rodrigues, Carina Santos-Silva, Alice Costa, Elísio Bronze-da-Rocha, Elsa |
| author_role | author |
| contributor_name_str_mv | Biblioteca Digital do IPB |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Rodrigues, Carina\",\"Person.identifier.orcid\":\"0000-0001-9773-1413\"},{\"Person.name\":\"Santos-Silva, Alice\"},{\"Person.name\":\"Costa, Elísio\"},{\"Person.name\":\"Bronze-da-Rocha, Elsa\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | Biblioteca Digital do IPB |
| datacite.creators.creator.creatorName.fl_str_mv | Rodrigues, Carina Santos-Silva, Alice Costa, Elísio Bronze-da-Rocha, Elsa |
| datacite.date.Accepted.fl_str_mv | 2015-01-01T00:00:00Z |
| datacite.date.available.fl_str_mv | 2016-03-02T15:47:40Z |
| datacite.date.embargoed.fl_str_mv | 2016-03-02T15:47:40Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | nsSNPs Genotype Bioinformatics Phenotype Protein function |
| datacite.titles.title.fl_str_mv | Performance of in silico tools for the evaluation of UGT1A1 missense variants |
| dc.contributor.none.fl_str_mv | Biblioteca Digital do IPB |
| dc.creator.none.fl_str_mv | Rodrigues, Carina Santos-Silva, Alice Costa, Elísio Bronze-da-Rocha, Elsa |
| dc.date.Accepted.fl_str_mv | 2015-01-01T00:00:00Z |
| dc.date.available.fl_str_mv | 2016-03-02T15:47:40Z |
| dc.date.embargoed.fl_str_mv | 2016-03-02T15:47:40Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10198/12776 |
| dc.language.none.fl_str_mv | eng |
| dc.publisher.none.fl_str_mv | Wiley-Blackwell |
| dc.rights.cclincense.fl_str_mv | http://creativecommons.org/licenses/by/4.0/ |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.subject.none.fl_str_mv | nsSNPs Genotype Bioinformatics Phenotype Protein function |
| dc.title.fl_str_mv | Performance of in silico tools for the evaluation of UGT1A1 missense variants |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_6501 |
| description | Variations in the gene encoding uridine diphosphate glucuronosyltransferase 1A1 (UGT1A1) are particularly important because they have been associated with hyperbilirubinemia in Gilbert’s and Crigler–Najjar syndromes as well as with changes in drug metabolism. Several variants associated with these phenotypes are nonsynonymous single-nucleotide polymorphisms (nsSNPs). Bioinformatics approaches have gained increasing importance in predicting the functional significance of these variants. This study was focused on the predictive ability of bioinformatics approaches to determine the pathogenicity of human UGT1A1 nsSNPs, which were previously characterized at the protein level by in vivo and in vitro studies. Using 16 Web algorithms, we evaluated 48 nsSNPs described in the literature and databases. Eight of these algorithms reached or exceeded 90% sensitivity and six presented a Matthews correlation coefficient above 0.46. The best-performing method was MutPred, followed by Sorting Intolerant from Tolerant (SIFT). The prediction measures varied significantly when predictors such us SIFT, polyphen-2, and Prediction of Pathological Mutations on Proteins were run with their native alignment generated by the tool, or with an input alignment that was strictly built with UGT1A1 orthologs and manually curated. Our results showed that the prediction performance of some methods based on sequence conservation analysis can be negatively affected when nsSNPs are positioned at the hypervariable or constant regions of UGT1A1 ortholog sequences. |
| dirty | 0 |
| eu_rights_str_mv | openAccess |
| format | article |
| fulltext.url.fl_str_mv | https://bibliotecadigital.ipb.pt/bitstreams/3d262bd4-2294-4f56-ba7e-d0624717bb93/download |
| id | ipb_beb487e246dbe413cdccbd65c4b9947f |
| identifier.url.fl_str_mv | http://hdl.handle.net/10198/12776 |
| instacron_str | ipb |
| institution | Instituto Politécnico de Bragança |
| instname_str | Instituto Politécnico de Bragança |
| language | eng |
| network_acronym_str | ipb |
| network_name_str | Biblioteca Digital do IPB |
| oai_identifier_str | oai:bibliotecadigital.ipb.pt:10198/12776 |
| organization_str_mv | urn:organizationAcronym:ipb |
| person_str_mv | Rodrigues, Carina Rodrigues, Carina https://www.ciencia-id.pt/C415-C677-0253 C415-C677-0253 http://orcid.org/0000-0001-9773-1413 0000-0001-9773-1413 Santos-Silva, Alice Costa, Elísio Bronze-da-Rocha, Elsa |
| publishDate | 2015 |
| publisher.none.fl_str_mv | Wiley-Blackwell |
| reponame_str | Biblioteca Digital do IPB |
| repository_id_str | urn:repositoryAcronym:ipb |
| service_str_mv | urn:repositoryAcronym:ipb |
| spelling | engWiley-Blackwellpt_PTVariations in the gene encoding uridine diphosphate glucuronosyltransferase 1A1 (UGT1A1) are particularly important because they have been associated with hyperbilirubinemia in Gilbert’s and Crigler–Najjar syndromes as well as with changes in drug metabolism. Several variants associated with these phenotypes are nonsynonymous single-nucleotide polymorphisms (nsSNPs). Bioinformatics approaches have gained increasing importance in predicting the functional significance of these variants. This study was focused on the predictive ability of bioinformatics approaches to determine the pathogenicity of human UGT1A1 nsSNPs, which were previously characterized at the protein level by in vivo and in vitro studies. Using 16 Web algorithms, we evaluated 48 nsSNPs described in the literature and databases. Eight of these algorithms reached or exceeded 90% sensitivity and six presented a Matthews correlation coefficient above 0.46. The best-performing method was MutPred, followed by Sorting Intolerant from Tolerant (SIFT). The prediction measures varied significantly when predictors such us SIFT, polyphen-2, and Prediction of Pathological Mutations on Proteins were run with their native alignment generated by the tool, or with an input alignment that was strictly built with UGT1A1 orthologs and manually curated. Our results showed that the prediction performance of some methods based on sequence conservation analysis can be negatively affected when nsSNPs are positioned at the hypervariable or constant regions of UGT1A1 ortholog sequences.application/pdfpt_PTPerformance of in silico tools for the evaluation of UGT1A1 missense variantsPersonalRodrigues, CarinaDSpacehttp://dspace.org/items/ef666665-6593-48be-bc48-6a1bb58bedbdDSpacehttp://dspace.org/items/ef666665-6593-48be-bc48-6a1bb58bedbdRodriguesCarinaCiência IDhttps://www.ciencia-id.ptC415-C677-0253ORCIDhttp://orcid.org0000-0001-9773-1413Santos-Silva, AliceCosta, ElísioBronze-da-Rocha, ElsaHostingInstitutionOrganizationalBiblioteca Digital do IPBe-mailmailto:dspace@ipb.ptdspace@ipb.ptISSNIsPartOf1098-1004DOIIsPartOf10.1002/humu.229032016-03-02T15:47:40Z20152015-01-01T00:00:00ZHandlehttp://hdl.handle.net/10198/12776http://purl.org/coar/access_right/c_abf2open accessnsSNPsGenotypeBioinformaticsPhenotypeProtein function461379 bytesliteraturehttp://purl.org/coar/resource_type/c_6501journal article2015http://creativecommons.org/licenses/by/4.0/http://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://bibliotecadigital.ipb.pt/bitstreams/3d262bd4-2294-4f56-ba7e-d0624717bb93/downloadHuman Mutation3612151225 |
| spellingShingle | Performance of in silico tools for the evaluation of UGT1A1 missense variants Rodrigues, Carina nsSNPs Genotype Bioinformatics Phenotype Protein function |
| status | SINGLETON |
| subject.fl_str_mv | nsSNPs Genotype Bioinformatics Phenotype Protein function |
| title | Performance of in silico tools for the evaluation of UGT1A1 missense variants |
| title_full | Performance of in silico tools for the evaluation of UGT1A1 missense variants |
| title_fullStr | Performance of in silico tools for the evaluation of UGT1A1 missense variants |
| title_full_unstemmed | Performance of in silico tools for the evaluation of UGT1A1 missense variants |
| title_short | Performance of in silico tools for the evaluation of UGT1A1 missense variants |
| title_sort | Performance of in silico tools for the evaluation of UGT1A1 missense variants |
| topic | nsSNPs Genotype Bioinformatics Phenotype Protein function |
| topic_facet | nsSNPs Genotype Bioinformatics Phenotype Protein function |
| url | http://hdl.handle.net/10198/12776 |
| visible | 1 |