Human Splicing Finder: an online bioinformatics tool to predict splicing signals.
Human Splicing Finder: an online bioinformatics tool to predict splicing signals.
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DOI：
10.1093/nar/gkp215
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发表时间：
2009-05
影响因子：
14.9
通讯作者：
Béroud C
中科院分区：
文献类型：
--
作者：
Desmet FO;Hamroun D;Lalande M;Collod-Béroud G;Claustres M;Béroud C
每年都有成千上万的突变被发现。尽管许多突变直接影响蛋白质表达，但现在认为越来越多的突变影响mRNA剪接。它们主要影响现有的剪接位点，但同义、非同义或无义突变也可以产生或破坏剪接位点或辅助顺式剪接序列。为了便于分析不同的突变，我们设计了人类剪接模板（HSF），这是一种预测突变对剪接信号的影响或识别任何人类序列中剪接基序的工具。它包含用于辅助序列预测的所有可用矩阵以及用于9 G8和Tra 2-β丝氨酸-精氨酸蛋白和hnRNP A1核糖核蛋白结合位点的新矩阵。我们还开发了新的位置权重矩阵来评估5 '和3'剪接位点和分支点的强度。我们使用一组已知导致剪接缺陷的83个内含子和35个外显子突变来评估HSF效率。我们发现，突变效应在几乎所有情况下都被正确预测。因此，HSF可以代表用于研究、诊断和治疗（例如治疗性外显子跳跃）目的以及全球研究（例如GEN 2 PHEN欧洲项目或人类变异组项目）的有价值的资源。
Thousands of mutations are identified yearly. Although many directly affect protein expression, an increasing proportion of mutations is now believed to influence mRNA splicing. They mostly affect existing splice sites, but synonymous, non-synonymous or nonsense mutations can also create or disrupt splice sites or auxiliary cis-splicing sequences. To facilitate the analysis of the different mutations, we designed Human Splicing Finder (HSF), a tool to predict the effects of mutations on splicing signals or to identify splicing motifs in any human sequence. It contains all available matrices for auxiliary sequence prediction as well as new ones for binding sites of the 9G8 and Tra2-β Serine-Arginine proteins and the hnRNP A1 ribonucleoprotein. We also developed new Position Weight Matrices to assess the strength of 5′ and 3′ splice sites and branch points. We evaluated HSF efficiency using a set of 83 intronic and 35 exonic mutations known to result in splicing defects. We showed that the mutation effect was correctly predicted in almost all cases. HSF could thus represent a valuable resource for research, diagnostic and therapeutic (e.g. therapeutic exon skipping) purposes as well as for global studies, such as the GEN2PHEN European Project or the Human Variome Project.
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影响因子：
14.9
作者：
Cartegni, L;Wang, JH;Krainer, AR
通讯作者：
Krainer, AR
影响因子：
3.9
作者：
Béroud, C;Hamroun, D;Claustres, M
通讯作者：
Claustres, M
影响因子：
3.5
作者：
Chavanas, S;Gache, Y;Meneguzzi, G
通讯作者：
Meneguzzi, G
影响因子：
64.5
作者：
BREITBART, RE;NGUYEN, HT;NADALGINARD, B
通讯作者：
NADALGINARD, B
影响因子：
9.8
作者：
Baala, Lekbir;Romano, Stephane;Attie-Bitach, Tania
通讯作者：
Attie-Bitach, Tania