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

Authors

Owen R Hirschi
Stephanie A Felker
Surya P Rednam
Kelly L Vallance
D Williams Parsons
Angshumoy Roy
Gregory M Cooper
Sharon E Plon

Publication Date

1-1-2024

Journal

Genetics in Medicine Open

DOI

10.1016/j.gimo.2024.101850

PMID

39669609

PMCID

PMC11613871

PubMedCentral® Posted Date

5-15-2024

PubMedCentral® Full Text Version

Post-print

Published Open-Access

yes

Keywords

Intronic, RNA, Splicing, Synonymous, Variant Classification

Abstract

PURPOSE: Clinical variant analysis pipelines likely have poor sensitivity to the effects on splicing from variants beyond 10 to 20 bases of exon-intron boundaries. Here, we demonstrate the value of SpliceAI to inform curation of rare variants previously classified as benign/likely benign (B/LB) under current guidelines.

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 >10 by combined annotation-dependent depletion. Rare synonymous or intronic B/LB variants in 61 genes submitted to ClinVar were also evaluated and RNA further assessed in monocyte-derived messenger RNA and/or an in vitro splice reporter assay in HEK-293T cells.

RESULTS: SpliceAI-supplemented analysis of the KidsCanSeq cohort revealed a

CONCLUSION: Incorporation of SpliceAI in variant curation pipelines may improve classification of B/LB intronic and synonymous variants and highlight putative pathogenic variants for functional assays and RNA analysis, thereby increasing diagnostic yield for rare diseases.

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