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bioRxiv · 10.1101/2025.06.28.662167

Spliformer-v2 predicts multi-tissue RNA splicing and reveals functional genomic links with neurodegenerative diseases

Tang, X.·Lei, H.·Guo, J.·Shen, Y.·Zhang, M.
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Abstract

Precise regulation of pre-mRNA splicing underlies transcriptomic diversity and is disrupted in aging and disease, yet tissue-specific splice-altering genetic variants remain poorly resolved. Here, we present Spliformer-V2, a SegmentNT-based deep learning model for predicting and interpreting variant effects on RNA splicing across human tissues. We generated a diploid sequence resolved RNA splice map from paired whole-genome-sequencing and RNA-seq data across 12 central nervous system (CNS) and 6 peripheral tissues for model development. Spliformer-V2 outperformed SpliceTransformer, Pangolin and AlphaGenome in predicting splice-site usage, identified tissue-specific splicing regulatory motifs, and revealed tissue vulnerability to pathogenic splice-altering variants. Analyses of loci associated with 8 neurological diseases prioritized CNS-specific mis-splice-vulnerable genes. In 1,405 amyotrophic lateral sclerosis (ALS) genomes, Spliformer-V2 nominated rare splice-altering variants enriched in PTPRN2, which showed reduced expression in TDP-43-depleted neurons. PTPRN2 overexpression rescued C9ORF72-patient derived motor neuron degeneration and modulated TDP-43 mislocalization, indicating it as a potential therapeutic modifier in ALS.

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Tang, X., Lei, H., Guo, J., Shen, Y., Zhang, M.. 2025-07-03. Spliformer-v2 predicts multi-tissue RNA splicing and reveals functional genomic links with neurodegenerative diseases. https://doi.org/10.1101/2025.06.28.662167

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