Systematically developing a registry of splice-site creating variants utilizing massive publicly available transcriptome sequence data

Naoko Iida, Ai Okada, Yoshihisa Kobayashi, Kenichi Chiba, Yasushi Yatabe and Yuichi Shiraishi ()
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Naoko Iida: National Cancer Center Research Institute
Ai Okada: National Cancer Center Research Institute
Yoshihisa Kobayashi: National Cancer Center Research Institute
Kenichi Chiba: National Cancer Center Research Institute
Yasushi Yatabe: National Cancer Center Research Institute
Yuichi Shiraishi: National Cancer Center Research Institute

Nature Communications, 2025, vol. 16, issue 1, 1-15

Abstract: Abstract Genomic variants causing abnormal splicing play important roles in genetic disorders and cancer development. Among them, variants that cause the formation of novel splice-sites (splice-site creating variants, SSCVs) are particularly difficult to identify and often overlooked in genomic studies. Additionally, these SSCVs are frequently considered promising candidates for treatment with splice-switching antisense oligonucleotides (ASOs). To leverage massive transcriptome sequence data such as those available from the Sequence Read Archive, we develop a novel framework to screen for SSCVs solely using transcriptome data. We apply it to 322,072 publicly available transcriptomes and identify 30,130 SSCVs. Among them, 5121 SSCVs affect disease-causing variants. By utilizing this extensive collection of SSCVs, we reveal the characteristics of Alu exonization via SSCVs, especially the hotspots of SSCVs within Alu sequences and their evolutionary relationships. We discover novel gain-of-function SSCVs in the deep intronic region of the NOTCH1 gene and demonstrate that their activation can be suppressed using splice-switching ASOs. Collectively, we provide a systematic approach for automatically acquiring a registry of SSCVs, which facilitates the elucidation of novel biological mechanisms underlying splicing and serves as a valuable resource for drug discovery. The catalogs of SSCVs identified in this study are accessible on the SSCV DB ( https://sscvdb.io ).

Date: 2025
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DOI: 10.1038/s41467-024-55185-y

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