Long-read sequencing to identify inherited mutations predisposing to breast cancer
We aimed to detect deeply intronic mutations within genes linked to breast/ovarian cancer that are potentially under-reported in clinical testing due to technical limitations. Current DNA and RNA tests typically exclude these regions, which harbor many variants within complex repetitive sequences that short-read sequencing cannot align. By employing targeted long read sequencing together with recent in silico prediction tools, we assessed the implications of rare deep intronic variants in severely affected patients with breast, ovarian, and/or metastatic prostate cancer, who had previously tested negative using standard genomic or cDNA methods. Through this approach, we identified participants who carried deep intronic mutations in tumor suppressor genes, resulting in abnormal... (for more see dbGaP study page.)