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  1. C100 医学部/医学系研究科
  2. C100a 雑誌掲載論文
  3. 学術雑誌

Rules and tools to predict the splicing effects of exonic and intronic mutations

http://hdl.handle.net/2237/00027899
http://hdl.handle.net/2237/00027899
6092f51f-22da-42de-8c78-dac07bb1c121
名前 / ファイル ライセンス アクション
WIREsReviewforRepository.pdf WIREsReviewforRepository (461.9 kB)
Item type 学術雑誌論文 / Journal Article(1)
公開日 2018-04-16
タイトル
タイトル Rules and tools to predict the splicing effects of exonic and intronic mutations
言語 en
著者 Ohno, Kinji

× Ohno, Kinji

WEKO 76056

en Ohno, Kinji

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Takeda, Jun-ichi

× Takeda, Jun-ichi

WEKO 76057

en Takeda, Jun-ichi

Search repository
Masuda, Akio

× Masuda, Akio

WEKO 76058

en Masuda, Akio

Search repository
アクセス権
アクセス権 open access
アクセス権URI http://purl.org/coar/access_right/c_abf2
権利
言語 en
権利情報 This is the peer reviewed version of the following article: [Ohno, K. , Takeda, J. and Masuda, A. (2018), Rules and tools to predict the splicing effects of exonic and intronic mutations. WIREs RNA, 9: e1451. doi:10.1002/wrna.1451], which has been published in final form at [http://doi.org/10.1002/wrna.1451]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
抄録
内容記述 Development of next generation sequencing technologies has enabled detection of extensive arrays of germline and somatic single nucleotide variations (SNVs) in human diseases. SNVs affecting intronic GT‐AG dinucleotides invariably compromise pre‐mRNA splicing. Most exonic SNVs introduce missense/nonsense codons, but some affect auxiliary splicing cis‐elements or generate cryptic GT‐AG dinucleotides. Similarly, most intronic SNVs are silent, but some affect canonical and auxiliary splicing cis‐elements or generate cryptic GT‐AG dinucleotides. However, prediction of the splicing effects of SNVs is challenging. The splicing effects of SNVs generating cryptic AG or disrupting canonical AG can be inferred from the AG‐scanning model. Similarly, the splicing effects of SNVs affecting the first nucleotide G of an exon can be inferred from AG‐dependence of the 3′ splice site (ss). A variety of tools have been developed for predicting the splicing effects of SNVs affecting the 5′ ss, as well as exonic and intronic splicing enhancers/silencers. In contrast, only two tools, the Human Splicing Finder and the SVM‐BP finder, are available for predicting the position of the branch point sequence. Similarly, IntSplice and Splicing based Analysis of Variants (SPANR) are the only tools to predict the splicing effects of intronic SNVs. The rules and tools introduced in this review are mostly based on observations of a limited number of genes, and no rule or tool can ensure 100% accuracy. Experimental validation is always required before any clinically relevant conclusions are drawn. Development of efficient tools to predict aberrant splicing, however, will facilitate our understanding of splicing pathomechanisms in human diseases.
言語 en
内容記述タイプ Abstract
内容記述
内容記述 ファイル公開:2019-02-01
言語 ja
内容記述タイプ Other
出版者
言語 en
出版者 Wiley
言語
言語 eng
資源タイプ
資源タイプresource http://purl.org/coar/resource_type/c_6501
タイプ journal article
出版タイプ
出版タイプ AM
出版タイプResource http://purl.org/coar/version/c_ab4af688f83e57aa
DOI
関連タイプ isVersionOf
識別子タイプ DOI
関連識別子 https://doi.org/10.1002/wrna.1451
ISSN
収録物識別子タイプ PISSN
収録物識別子 17577004
書誌情報 en : Wiley Interdisciplinary Reviews: RNA

巻 9, 号 1, p. e1451, 発行日 2018-02
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