SpliceAPP: an interactive web server to predict splicing errors arising from human mutations.

BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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 .

Mechanism and modeling of human disease-associated near-exon intronic variants that perturb RNA splicing.

It is estimated that 10%-30% of disease-associated genetic variants affect splicing. Splicing variants may generate deleteriously altered gene product and are potential therapeutic targets. However, systematic diagnosis or prediction of splicing variants is yet to be established, especially for the near-exon intronic splice region. The major challenge lies in the redundant and ill-defined branch sites and other splicing motifs therein. Here, we carried out unbiased massively parallel splicing assays on 5,307 disease-associated variants that overlapped with branch sites and collected 5,884 variants across the 5' splice region. We found that strong splice sites and exonic features preserve splicing from intronic sequence variation. Whereas the splice-altering mechanism of the 3' intronic variants is complex, that of the 5' is mainly splice-site destruction. Statistical learning combined with these molecular features allows precise prediction of altered splicing from an intronic variant. This statistical model provides the identity and ranking of biological features that determine splicing, which serves as transferable knowledge and out-performs the benchmarking predictive tool. Moreover, we demonstrated that intronic splicing variants may associate with disease risks in the human population. Our study elucidates the mechanism of splicing response of intronic variants, which classify disease-associated splicing variants for the promise of precision medicine.

A calpain-6/YAP axis in sarcoma stem cells that drives the outgrowth of tumors and metastases.

Sarcomas include cancer stem cells, but how these cells contribute to local and metastatic relapse is largely unknown. We previously showed the pro-tumor functions of calpain-6 in sarcoma stem cells. Here, we use an osteosarcoma cell model, osteosarcoma tissues and transcriptomic data from human tumors to study gene patterns associated with calpain-6 expression or suppression. Calpain-6 modulates the expression of Hippo pathway genes and stabilizes the hippo effector YAP. It also modulates the vesicular trafficking of ß-catenin degradation complexes. Calpain-6 expression is associated with genes of the G2M phase of the cell cycle, supports G2M-related YAP activities and up-regulated genes controlling mitosis in sarcoma stem cells and tissues. In mouse models of bone sarcoma, most tumor cells expressed calpain-6 during the early steps of tumor out-growth. YAP inhibition prevented the neoformation of primary tumors and metastases but had no effect on already developed tumors. It could even accelerate lung metastasis associated with large bone tumors by affecting tumor-associated inflammation in the host tissues. Our results highlight a specific mechanism involving YAP transcriptional activity in cancer stem cells that is crucial during the early steps of tumor and metastasis outgrowth and that could be targeted to prevent sarcoma relapse.