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Allele-Specific Droplet Digital PCR Combined with a Next-Generation Sequencing-Based Algorithm for Diagnostic Copy Number Analysis in Genes with High Homology: Proof of Concept Using Stereocilin



Allele-Specific Droplet Digital PCR Combined with a Next-Generation Sequencing-Based Algorithm for Diagnostic Copy Number Analysis in Genes with High Homology: Proof of Concept Using Stereocilin



Clinical Chemistry 64(4): 705-714



Copy number variants (CNVs) can substantially contribute to the pathogenic variant spectrum in several disease genes. The detection of this type of variant is complicated in genes with high homology to other genomic sequences, yet such genomics regions are more likely to lead to CNVs, making it critical to address detection in these settings. We developed a copy number analysis approach for high homology genes/regions that consisted of next-generation sequencing (NGS)-based dosage analysis accompanied by allele-specific droplet digital PCR (ddPCR) confirmatory testing. We applied this approach to copy number analysis in STRC, a gene with 98.9% homology to a nonfunctional pseudogene, pSTRC, and characterized its accuracy in detecting different copy number states by use of known samples. Using a cohort of 517 patients with hearing loss, we prospectively demonstrated the clinical utility of the approach, which contributed 30 of the 122 total positives (6%) to the diagnostic yield, increasing the overall yield from 17.6% to 23.6%. Positive STRC genotypes included homozygous (n = 15) or compound heterozygous (n = 8) deletions, or heterozygous deletions in trans with pathogenic sequence variants (n = 7). Finally, this approach limited ddPCR testing to cases with NGS copy number findings, thus markedly reducing the number of costly and laborious, albeit specific, ddPCR tests. NGS-based CNV detection followed by allele-specific ddPCR confirmatory testing is a reliable and affordable approach for copy number analysis in medically relevant genes with homology issues.

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Accession: 045865181

Download citation: RISBibTeXText

PMID: 29339441

DOI: 10.1373/clinchem.2017.280685


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