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dc.contributor.authorZhang, Xinjun
dc.contributor.authorLi, Meng
dc.contributor.authorLin, Hai
dc.contributor.authorRao, Xi
dc.contributor.authorFeng, Weixing
dc.contributor.authorYang, Yuedong
dc.contributor.authorMort, Matthew
dc.contributor.authorCooper, David N
dc.contributor.authorWang, Yue
dc.contributor.authorWang, Yadong
dc.contributor.authorWells, Clark
dc.contributor.authorZhou, Yaoqi
dc.contributor.authorLiu, Yunlong
dc.date.accessioned2017-08-23T12:30:58Z
dc.date.available2017-08-23T12:30:58Z
dc.date.issued2017
dc.identifier.issn0340-6717
dc.identifier.doi10.1007/s00439-017-1783-x
dc.identifier.urihttp://hdl.handle.net/10072/344536
dc.description.abstractWhile synonymous single-nucleotide variants (sSNVs) have largely been unstudied, since they do not alter protein sequence, mounting evidence suggests that they may affect RNA conformation, splicing, and the stability of nascent-mRNAs to promote various diseases. Accurately prioritizing deleterious sSNVs from a pool of neutral ones can significantly improve our ability of selecting functional genetic variants identified from various genome-sequencing projects, and, therefore, advance our understanding of disease etiology. In this study, we develop a computational algorithm to prioritize sSNVs based on their impact on mRNA splicing and protein function. In addition to genomic features that potentially affect splicing regulation, our proposed algorithm also includes dozens structural features that characterize the functions of alternatively spliced exons on protein function. Our systematical evaluation on thousands of sSNVs suggests that several structural features, including intrinsic disorder protein scores, solvent accessible surface areas, protein secondary structures, and known and predicted protein family domains, show significant differences between disease-causing and neutral sSNVs. Our result suggests that the protein structure features offer an added dimension of information while distinguishing disease-causing and neutral synonymous variants. The inclusion of structural features increases the predictive accuracy for functional sSNV prioritization.
dc.description.peerreviewedYes
dc.languageEnglish
dc.language.isoeng
dc.publisherSpringer Verlag
dc.relation.ispartofpagefrom1
dc.relation.ispartofpageto11
dc.relation.ispartofjournalHuman genetics
dc.subject.fieldofresearchGenetics
dc.subject.fieldofresearchGenetics not elsewhere classified
dc.subject.fieldofresearchTraditional, complementary and integrative medicine
dc.subject.fieldofresearchcode3105
dc.subject.fieldofresearchcode310599
dc.subject.fieldofresearchcode4208
dc.titleregSNPs-splicing: a tool for prioritizing synonymous single-nucleotide substitution
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
dcterms.licensehttp://creativecommons.org/licenses/by/4.0/
dc.description.versionVersion of Record (VoR)
gro.description.notepublicThis publication has been entered into Griffith Research Online as an Advanced Online Version.
gro.rights.copyright© The Author(s) 2017. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
gro.hasfulltextFull Text
gro.griffith.authorZhou, Yaoqi
gro.griffith.authorYang, Yuedong


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