<i>CRYPTID-exon</i> : streamlined detection of cryptic exons from RNA-seq data

Cryptic splicing has emerged as a pervasive feature of mammalian gene expression, with recent studies uncovering thousands of previously unannotated splice sites. Despite its prevalence, the functional consequences of this hidden layer of splicing remain largely unknown due to challenges in identifying the exact exonic regions introduced into mRNA transcripts. Here, we introduce a novel computational approach, <i>CRYPTID-exon</i>, that accurately predicts exon boundaries by modeling RNA-seq read coverage around empirically derived splice sites. We use <i>CRYPTID-exon</i> to identify and characterize thousands of cryptic exons in nascent and mature RNA from human cells. Additionally, we demonstrate that <i>CRYPTID-exon</i> is well powered to identify exons that are sensitive to translation-mediated degradation processes. Finally, given the growing interest in leveraging cryptic exons to modulate gene expression levels, we use our approach to identify cryptic exons in disease-relevant genes. We see that targeting these cryptic exons with splice-switching antisense oligonucleotides (ASOs) can alter gene expression and splicing patterns of the parent genes. Our study provides a framework to systematically identify and characterize cryptic exons, which will enable downstream insights into their impact on mRNA stability and translation.