SRA project number


SRA runID number


SSCV (distinct) number

Examples: TP53, SMARCA4, NRF2


on 2023/12/26, We released SSCV DB v1.0.

The SSCV DB represents an experimental challenge that autonomously develops a registry of splice-site creating variants (SSCVs) using publicly available transcriptome sequencing data, and provides this resource to the research community.

Genetic variants that result in abnormal splicing play a significant role in the onset of genetic disorders and cancer. This database primarily focuses on SSCVs, which are crucial for several reasons:

  1. SSCVs often appear as seemingly insignificant variations, including silent mutations in exonic areas and mutations within deep intronic regions.
  2. Extracting SSCVs is more complex and demanding compared to identifying splicing-associated variants that disrupt conventional splice-sites, typically found near exon-intron boundaries. This is because SSCVs can occur across the entire genome, making their detection a challenge that requires high precision and sensitivity.
  3. Moreover, SSCVs, particularly those in deep intronic regions, are frequently identified as optimal targets for splice-switching antisense oligonucleotide (ASO) therapies. This highlights their potential as valuable treatment avenues for patients suffering from rare diseases.

We have developed a software, juncmut, designed to detect SSCVs only using transcriptome sequencing data. This approach is refined to minimize false positives. Additionally, juncmut can operate on individual transcriptomes without requiring predefined groups in the analysis, facilitating the efficient compilation of SSCVs via a consolidated process of extensive transcriptome sequencing. We are confident that this tool will be instrumental in uncovering new biological understanding and in identifying novel targets for splice-switching antisense ASOs.

Overview of the proposed framework for detecting splice-site creating variants from raw sequencing data registered in Sequence Read Archive (Iida et al., bioRxiv, 2024).