Desmet F O, Béroud C
INSERM U1052 CNRS 5286, Lyon, France.
Methods Mol Biol. 2012;867:17-35. doi: 10.1007/978-1-61779-767-5_2.
Our knowledge about human genes and the consequences of mutations leading to human genetic diseases has drastically improved over the last few years. It has been recognized that many mutations are indeed pathogenic because they impact the mRNA rather than the protein itself. With our better understanding of the very complex mechanism of splicing, various bioinformatics tools have been developed. They are now frequently used not only to search for sequence motifs corresponding to splicing signals (splice sites, branch points, ESE, and ESS) but also to predict the impact of mutations on these signals. We now need to address the impact of mutations that affect the splicing process, as their consequences could vary from the activation of cryptic signals to the skipping of one or multiple exons. Despite the major developments of the bioinformatics field coupled to experimental data generated on splicing, it is today still not possible to efficiently predict the consequences of mutations impacting splicing signals, especially to predict if they will lead to exon skipping or to cryptic splice site activation.
在过去几年中,我们对人类基因以及导致人类遗传疾病的突变后果的了解有了显著提高。人们已经认识到,许多突变确实具有致病性,因为它们影响的是mRNA而非蛋白质本身。随着我们对极其复杂的剪接机制有了更好的理解,各种生物信息学工具应运而生。现在,这些工具不仅经常用于搜索与剪接信号(剪接位点、分支点、外显子剪接增强子和外显子剪接沉默子)相对应的序列基序,还用于预测突变对这些信号的影响。我们现在需要解决影响剪接过程的突变的影响,因为它们的后果可能从隐蔽信号的激活到一个或多个外显子的跳跃不等。尽管生物信息学领域取得了重大进展,并结合了关于剪接产生的实验数据,但如今仍然无法有效地预测影响剪接信号的突变的后果,尤其是无法预测它们是否会导致外显子跳跃或隐蔽剪接位点激活。