Grodecká Lucie, Buratti Emanuele, Freiberger Tomáš
Centre for Cardiovascular Surgery and Transplantation, Brno 65691, Czech Republic.
International Centre for Genetic Engineering and Biotechnology, 34149 Trieste, Italy.
Int J Mol Sci. 2017 Jul 31;18(8):1668. doi: 10.3390/ijms18081668.
For more than three decades, researchers have known that consensus splice sites alone are not sufficient regulatory elements to provide complex splicing regulation. Other regulators, so-called splicing regulatory elements (SREs) are needed. Most importantly, their sequence variants often underlie the development of various human disorders. However, due to their variable location and high degeneracy, these regulatory sequences are also very difficult to recognize and predict. Many different approaches aiming to identify SREs have been tried, often leading to the development of in silico prediction tools. While these tools were initially expected to be helpful to identify splicing-affecting mutations in genetic diagnostics, we are still quite far from meeting this goal. In fact, most of these tools are not able to accurately discern the SRE-affecting pathological variants from those not affecting splicing. Nonetheless, several recent evaluations have given appealing results (namely for EX-SKIP, ESRseq and Hexplorer predictors). In this review, we aim to summarize the history of the different approaches to SRE prediction, and provide additional validation of these tools based on patients' clinical data. Finally, we evaluate their usefulness for diagnostic settings and discuss the challenges that have yet to be met.
三十多年来，研究人员已经知道，仅共有剪接位点不足以作为提供复杂剪接调控的调控元件。还需要其他调控因子，即所谓的剪接调控元件（SRE）。最重要的是，它们的序列变异往往是各种人类疾病发生的基础。然而，由于它们位置可变且高度简并，这些调控序列也很难识别和预测。人们尝试了许多旨在识别SRE的不同方法，这常常促成了计算机预测工具的开发。虽然最初期望这些工具有助于在基因诊断中识别影响剪接的突变，但我们距离实现这一目标仍有很大差距。事实上，这些工具中的大多数无法准确区分影响SRE的病理性变异与不影响剪接的变异。尽管如此，最近的几项评估给出了令人满意的结果（特别是对于EX-SKIP、ESRseq和Hexplorer预测器）。在这篇综述中，我们旨在总结SRE预测不同方法的历史，并基于患者的临床数据对这些工具进行额外验证。最后，我们评估它们在诊断环境中的实用性，并讨论尚未解决的挑战。
