Leveraging Unique Chromosomal Microarray Probes to Accurately Detect Copy Number at the Highly Homologous 15q15.3 Deafness-Infertility Syndrome Locus

遗传学 拷贝数变化 同源染色体 生物 微阵列 基因座(遗传学) 微阵列分析技术 不育 计算生物学 基因 怀孕 基因组 基因表达
作者
Laura M. Sack,Lauren Mertens,Elissa Murphy,Laura Hutchinson,Anne B.S. Giersch,Heather Mason‐Suares
出处
期刊:Clinical Chemistry [American Association for Clinical Chemistry]
卷期号:69 (6): 583-594 被引量:1
标识
DOI:10.1093/clinchem/hvad032
摘要

Biallelic deletions at 15q15.3, including STRC and CATSPER2, cause autosomal recessive deafness-infertility syndrome (DIS), while biallelic deletions of STRC alone cause nonsyndromic hearing loss. These deletions are among the leading genetic causes of mild-moderate hearing loss, but their detection using chromosomal microarray (CMA) is impeded by a tandem duplication containing highly homologous pseudogenes. We sought to assess copy number variant (CNV) detection in this region by a commonly-employed CMA platform.Twenty-two specimens with known 15q15.3 CNVs, determined by droplet digital PCR (ddPCR), were analyzed by CMA. To investigate the impact of pseudogene homology on CMA performance, a probe-level analysis of homology was performed, and log2 ratios of unique and pseudogene-homologous probes compared.Assessment of 15q15.3 CNVs by CMA compared to ddPCR revealed 40.9% concordance, with frequent mis-assignment of zygosity by the CMA automated calling software. Probe-level analysis of pseudogene homology suggested that probes with high homology contributed to this discordance, with significant differences in log2 ratios between unique and pseudogene-homologous CMA probes. Two clusters containing several unique probes could reliably detect CNVs involving STRC and CATSPER2, despite the noise of surrounding probes, discriminating between homozygous vs heterozygous losses and complex rearrangements. CNV detection by these probe clusters showed 100% concordance with ddPCR.Manual analysis of clusters containing unique CMA probes without significant pseudogene homology improves CNV detection and zygosity assignment in the highly homologous DIS region. Incorporation of this method into CMA analysis and reporting processes can improve DIS diagnosis and carrier detection.
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