Exonic Splicing Mutations Are More Prevalent than Currently Estimated and Can Be Predicted by Using In Silico Tools

The identification of a causal mutation is essential for molecular diagnosis and clinical management of many genetic disorders. However, even if next-generation exome sequencing has greatly improved the detection of nucleotide changes, the biological interpretation of most exonic variants remains challenging. Moreover, particular attention is typically given to protein-coding changes often neglecting the potential impact of exonic variants on RNA splicing. Here, we used the exon 10 of MLH1, a gene implicated in hereditary cancer, as a model system to assess the prevalence of RNA splicing mutations among all single-nucleotide variants identified in a given exon. We performed comprehensive minigene assays and analyzed patient’s RNA when available. Our study revealed a staggering number of splicing mutations in MLH1 exon 10 (77% of the 22 analyzed variants), including mutations directly affecting splice sites and, particularly, mutations altering potential splicing regulatory elements (ESRs). We then used this thoroughly characterized dataset, together with experimental data derived from previous studies on BRCA1, BRCA2, CFTR and NF1, to evaluate the predictive power of 3 in silico approaches recently described as promising tools for pinpointing ESR-mutations. Our results indicate that ΔtESRseq and ΔHZEI-based approaches not only discriminate which variants affect splicing, but also predict the direction and severity of the induced splicing defects. In contrast, the ΔΨ-based approach did not show a compelling predictive power. Our data indicates that exonic splicing mutations are more prevalent than currently appreciated and that they can now be predicted by using bioinformatics methods. These findings have implications for all genetically-caused diseases.对诸多遗传性疾病而言，鉴定致病突变（causal mutation）是实现分子诊断与临床管理的必要前提。尽管新一代外显子组测序技术极大提升了核苷酸变异的检出效率，但绝大多数外显子变异的生物学功能阐释仍极具挑战。此外，当前研究往往重点关注蛋白质编码区变异，却常常忽视外显子变异对RNA剪接的潜在影响。本研究以遗传性癌症相关基因MLH1的第10号外显子作为模型系统，旨在评估单外显子内所有单核苷酸变异中RNA剪接突变的发生比例。我们开展了全面的迷你基因实验，并对可获取的患者RNA样本进行了分析。研究结果显示，MLH1第10号外显子中存在数量惊人的剪接突变：在所分析的22个变异中，剪接突变占比高达77%，其中既包括直接影响剪接位点的变异，也包含大量改变潜在剪接调控元件（Exonic Splicing Regulatory Elements，ESRs）的突变。随后，我们利用这一经过充分表征的数据集，结合此前针对BRCA1、BRCA2、CFTR及NF1基因的研究实验数据，评估了3种新近被提出的、用于精准识别ESRs相关突变的计算机虚拟（in silico）方法的预测效能。结果表明，基于ΔtESRseq与ΔHZEI的分析方法不仅能够区分出影响剪接的变异，还可预测诱导产生的剪接缺陷的方向与严重程度；与之相比，基于ΔΨ的分析方法则未展现出令人信服的预测效能。本研究数据显示，外显子剪接突变的实际发生率远高于当前学界的认知，且可通过生物信息学方法进行预测。上述研究发现对各类遗传性疾病的研究与临床实践均具有重要参考价值。