Parallel detection of single nucleotide variants and copy number variants with exome analysis: Validation in a cohort of 700 undiagnosed patients

Abstract

Copy number variants (CNVs) are significant causes of rare and undiagnosed diseases. Parallel detection of single nucleotide variants (SNVs) and CNVs with exome analysis, if feasible, would shorten the diagnostic closure in a timely manner. We validated such “parallel” approach through a cohort study of 791 undiagnosed patients. In addition to routine exome analysis, we applied an innovative algorithm EXCAVATOR2 which enhances sensitivity by paradoxically exploiting read depth data that covers nonexonic regions where baits were not originally intended to hybridize. About 48 patients had copy number variations, 42 deletions, and 6 duplications with a resolution of 0.51–14.7 mega base pairs. Importantly from a clinical standpoint, we identified three patients with “dual diagnosis” due to concurrent pathogenic CNV and SNV. We suggest “hitting two birds with one stone” approach to exome data is an efficient strategy in deciphering undiagnosed patients and may well be considered as a first-tier genetic test.