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  • regSNPs-splicing: a tool for prioritizing synonymous single-nucleotide substitution

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    Author(s)
    Zhang, Xinjun
    Li, Meng
    Lin, Hai
    Rao, Xi
    Feng, Weixing
    Yang, Yuedong
    Mort, Matthew
    Cooper, David N
    Wang, Yue
    Wang, Yadong
    Wells, Clark
    Zhou, Yaoqi
    Liu, Yunlong
    Griffith University Author(s)
    Zhou, Yaoqi
    Yang, Yuedong
    Year published
    2017
    Metadata
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    Abstract
    While 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 ...
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    While 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.
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    Journal Title
    Human genetics
    DOI
    https://doi.org/10.1007/s00439-017-1783-x
    Copyright Statement
    © 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.
    Note
    This publication has been entered into Griffith Research Online as an Advanced Online Version.
    Subject
    Genetics
    Genetics not elsewhere classified
    Traditional, complementary and integrative medicine
    Publication URI
    http://hdl.handle.net/10072/344536
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    • Journal articles

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