Institute of Molecular Biology, Academia Sinica, No. 128, Sec. 2, Academia Road, Nangang District, Taipei City, 115014, Taiwan.
Genome and Systems Biology Degree Program, Academia Sinica and National Taiwan University, Taipei, Taiwan.
BMC Genomics. 2024 Jun 15;25(1):600. doi: 10.1186/s12864-024-10512-x.
Splicing variants are a major class of pathogenic mutations, with their severity equivalent to nonsense mutations. However, redundant and degenerate splicing signals hinder functional assessments of sequence variations within introns, particularly at branch sites. We have established a massively parallel splicing assay to assess the impact on splicing of 11,191 disease-relevant variants. Based on the experimental results, we then applied regression-based methods to identify factors determining splicing decisions and their respective weights.
Our statistical modeling is highly sensitive, accurately annotating the splicing defects of near-exon intronic variants, outperforming state-of-the-art predictive tools. We have incorporated the algorithm and branchpoint information into a web-based tool, SpliceAPP, to provide an interactive application. This user-friendly website allows users to upload any genetic variants with genome coordinates (e.g., chr15 74,687,208 A G), and the tool will output predictions for splicing error scores and evaluate the impact on nearby splice sites. Additionally, users can query branch site information within the region of interest.
In summary, SpliceAPP represents a pioneering approach to screening pathogenic intronic variants, contributing to the development of precision medicine. It also facilitates the annotation of splicing motifs. SpliceAPP is freely accessible using the link https://bc.imb.sinica.edu.tw/SpliceAPP . Source code can be downloaded at https://github.com/hsinnan75/SpliceAPP .
剪接变异是一类主要的致病性突变，其严重程度等同于无义突变。然而，冗余和简并的剪接信号阻碍了对内含子中序列变异的功能评估，特别是在分支位点。我们建立了一种大规模并行剪接测定法，以评估 11,191 种与疾病相关的变异对剪接的影响。基于实验结果，我们随后应用基于回归的方法来确定决定剪接决策的因素及其各自的权重。
我们的统计建模非常敏感，能够准确注释近外显子内含子变异的剪接缺陷，优于最先进的预测工具。我们已经将该算法和分支点信息纳入到一个基于网络的工具 SpliceAPP 中，以提供一个交互式应用程序。这个用户友好的网站允许用户上传任何具有基因组坐标的遗传变异（例如，chr15 74,687,208 A G），并且该工具将输出剪接错误评分的预测，并评估对附近剪接位点的影响。此外，用户可以查询感兴趣区域内的分支位点信息。
总之，SpliceAPP 代表了一种筛查致病性内含子变异的开创性方法，有助于精准医学的发展。它还促进了剪接基序的注释。可通过链接 https://bc.imb.sinica.edu.tw/SpliceAPP 免费访问 SpliceAPP。源代码可在 https://github.com/hsinnan75/SpliceAPP 下载。
