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Updated: Jun 13, 2025

Comparative Lesions Analysis Through a Targeted Sequencing Approach
Published on: November 5, 2019
Long-read DNA and cDNA sequencing identify cancer-predisposing deep intronic variation in tumor-suppressor genes
Suleyman Gulsuner1, Amal AbuRayyan1, Jessica B Mandell1
1Departments of Medicine (Medical Genetics) and Genome Sciences, University of Washington, Seattle, Washington 98195-7720, USA.
Abstract:
The vast majority of deeply intronic genomic variants are benign, but some extremely rare or private deep intronic variants lead to exonification of intronic sequence with abnormal transcriptional consequences. Damaging variants of this class are likely underreported as causes of disease for several reasons: Most clinical DNA and RNA testing does not include full intronic sequences; many of these variants lie in complex repetitive regions that cannot be aligned from short-read whole-genome sequence; and, until recently, consequences of deep intronic variants were not accurately predicted by in silico tools. We evaluated the frequency and consequences of rare deep intronic variants for families severely affected with breast, ovarian, pancreatic, and/or metastatic prostate cancer, but with no causal variant identified by any previous genomic or cDNA-based approach. For 10 tumor-suppressor genes, we used multiplexed adaptive sampling long-read DNA sequencing and cDNA sequencing, based on patient-derived DNA and RNA, to systematically evaluate deep intronic variation. We identified all variants across the full genomic loci of targeted genes, applied the in silico tools SpliceAI and Pangolin to predict variants of functional consequence, and then carried out long-read cDNA sequencing to identify aberrant transcripts. For eight of the 120 (6%) previously unsolved families, rare deep intronic variants in BRCA1, PALB2, and ATM create intronic pseudoexons that are spliced into transcripts, leading to premature truncations. These results suggest that long-read DNA and cDNA sequencing can be integrated into variant discovery, with strategies for accurately characterizing pathogenic variants.
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