Combined Bioinformatic and Splicing Analysis of Likely Benign Intronic and Synonymous Variants Reveals Evidence for Pathogenicity.

Background: Current clinical variant analysis pipelines focus on coding variants and intronic variants within 10-20 bases of an exon-intron boundary that may affect splicing. The impact of newer splicing prediction algorithms combined with Methods: Exome sequencing data from 576 pediatric cancer patients enrolled in the Texas KidsCanSeq study were filtered for intronic or synonymous variants absent from population databases, predicted to alter splicing via SpliceAI (>0.20), and scored as potentially deleterious by CADD (>10.0). Total cellular RNA was extracted from monocytes and RT-PCR products analyzed. Subsequently, rare synonymous or intronic B/LB variants in a subset of genes submitted to ClinVar were similarly evaluated. Variants predicted to lead to a frameshifted splicing product were functionally assessed using an Results: KidsCanSeq exome data analysis revealed a rare, heterozygous, intronic variant (NM_177438.3( Conclusions: Our results demonstrate the power of newer predictive splicing algorithms to highlight rare variants previously considered B/LB in patients with features of hereditary conditions. Incorporation of SpliceAI annotation of existing variant data combined with either direct RNA analysis or