Center for Computational and Genomic Medicine, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.
Genomics and Computational Biology Graduate Program, University of Pennsylvania, Philadelphia, PA 19104, USA.
Brief Bioinform. 2023 Sep 20;24(5). doi: 10.1093/bib/bbad284.
Genomic variants affecting pre-messenger RNA splicing and its regulation are known to underlie many rare genetic diseases. However, common workflows for genetic diagnosis and clinical variant interpretation frequently overlook splice-altering variants. To better serve patient populations and advance biomedical knowledge, it has become increasingly important to develop and refine approaches for detecting and interpreting pathogenic splicing variants. In this review, we will summarize a few recent developments and challenges in using RNA sequencing technologies for rare disease investigation. Moreover, we will discuss how recent computational splicing prediction tools have emerged as complementary approaches for revealing disease-causing variants underlying splicing defects. We speculate that continuous improvements to sequencing technologies and predictive modeling will not only expand our understanding of splicing regulation but also bring us closer to filling the diagnostic gap for rare disease patients.
已知影响前信使 RNA 剪接及其调控的基因组变异是许多罕见遗传疾病的基础。然而，遗传诊断和临床变异解释的常用工作流程经常忽略改变剪接的变异。为了更好地为患者群体服务和推进生物医学知识，开发和完善检测和解释致病性剪接变异的方法变得越来越重要。在这篇综述中，我们将总结使用 RNA 测序技术进行罕见病研究的一些最新进展和挑战。此外，我们将讨论最近的计算剪接预测工具如何作为揭示导致剪接缺陷的致病变异的补充方法出现。我们推测，测序技术和预测模型的不断改进不仅将扩大我们对剪接调控的理解，还将使我们更接近为罕见病患者填补诊断空白。
