Zhang Tongda, Wu Yiran, Lan Zhangzhang, Shi Quan, Yang Ying, Guo Jian
BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, Guangdong 518000, China.
BGI-Shenzhen, Shenzhen, Guangdong 518083, China.
Biomed Res Int. 2017;2017:5096208. doi: 10.1155/2017/5096208. Epub 2017 Jul 24.
Synonymous mutation is the single nucleotide change that does not cause an amino acid change but can affect the rate and efficiency of translation. So recent increase in our knowledge has revealed a substantial contribution of synonymous mutations to human disease risk and other complex traits. Nevertheless, there are still rarely synonymous mutation prediction methods.
Nonsynonymous and synonymous coding SNPs show similar likelihood and effect size of human disease association. Here we defined synonymous and missense variation as single nucleotide substitution variation. And then we evaluated the intolerance of genic transcripts to single nucleotide substitution variation based on gnomAD 123136 individuals. After regressing all variations on common variations, we defined residuals of regression model as every genomics region intolerance scores.
We constructed a total of 24799 nonoverlapped region-based intolerance score by their intolerance to single nucleotide substitution variation (Syntool). The results show that Syntool score can discriminate synonymous disease causing mutations in Human Gene Mutation Database (HGMD Professional) and ClinVar database much better than others. Taken together, this study provides a novel prediction system for synonymous mutations, called Syntool, which could be helpful in identifying candidate synonymous disease causing mutations.
同义突变是指单核苷酸改变但不引起氨基酸变化，却可影响翻译速率和效率的情况。因此，最近我们知识的增加揭示了同义突变对人类疾病风险和其他复杂性状的重大贡献。然而，同义突变预测方法仍然很少。
非同义编码单核苷酸多态性（SNP）和同义编码SNP显示出相似的人类疾病关联可能性和效应大小。在此，我们将同义变异和错义变异定义为单核苷酸替代变异。然后，我们基于gnomAD的123136个个体评估基因转录本对单核苷酸替代变异的不耐受性。在将所有变异对常见变异进行回归后，我们将回归模型的残差定义为每个基因组区域的不耐受性得分。
我们根据对单核苷酸替代变异的不耐受性构建了总共24799个基于非重叠区域的不耐受性得分（Syntool）。结果表明，Syntool得分在区分人类基因突变数据库（HGMD Professional）和ClinVar数据库中的同义致病突变方面比其他方法要好得多。综上所述，本研究提供了一种用于同义突变的新型预测系统，称为Syntool，它有助于识别候选同义致病突变。
