Sami S Amr1,2, Elissa Murphy1, Elizabeth Duffy1, Rojeen Niazi3, Jorune Balciuniene3, Minjie Luo3,4, Heidi L Rehm1,2,5, Ahmad N Abou Tayoun6,4. 1. Laboratory for Molecular Medicine, Partners Healthcare Personalized Medicine, Cambridge, MA. 2. Department of Pathology, Brigham & Women's Hospital and Harvard Medical School, Boston, MA. 3. Division of Genomic Diagnostics, The Children's Hospital of Philadelphia, Philadelphia, PA. 4. The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA. 5. The Broad Institute of MIT and Harvard, Cambridge, MA. 6. Division of Genomic Diagnostics, The Children's Hospital of Philadelphia, Philadelphia, PA; aboutayoua@chop.edu.
Abstract
BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
Authors: Lisong Shi; Yan Bai; Yara Kharbutli; Andrea M Oza; Sami S Amr; Lisa Edelmann; Lakshmi Mehta; Stuart A Scott Journal: Mol Genet Genomic Med Date: 2019-06-19 Impact factor: 2.183