Maximizing the Detection of Copy Number Variants in the Highly Homologous Deafness-Infertility Syndrome Locus in Standard-of-care Testing
Year: 2023
Type: editorial
Abstract: Genome-wide chromosomal microarrays (CMA) can identify pathogenic copy number variants (CNVs) associated with patients’ clinical indications but also have the potential to detect incidental findings and carrier status for recessive disorders. Patients can benefit from maximizing the detection and reporting of potentially clinically significant CNVs from this standard-of-care genome-wide test in accordance with professional guidelines (1); however, accurate detection of specific CNVs can be limited by the technology used and the complexity of the genomic regions under consideration. One example of this complexity is in the detection of disease-causing variants in the STRC gene associated with DFNB16, the second most frequent cause of autosomal recessive nonsyndromic hearing loss (NSHL), which is a common sensory disorder with high genetic heterogeneity. DFNB16 is estimated to account for up to 16% of individuals with NSHL (2). Most pathogenic STRC alterations are deletions encompassing all or part of the gene. These deletions often extend into the neighboring gene CATSPER2, which is associated with male fertility. Homozygous, contiguous deletions involving both STRC and CATSPER2 cause deafness-infertility syndrome (DIS), a contiguous gene deletion syndrome characterized by nonsyndromic, congenital to post-lingual onset of mild to moderate bilateral sensorineural hearing loss in both males and females and exclusive male infertility. Several studies have reported that 1%–2% of individuals are asymptomatic heterozygous carriers for a deletion of STRC with or without CATSPER2 (2, 3). The high frequency of STRC deletions has also led to reports of “pseudodominant inheritance,” in which a parent and child both have hearing loss as a result of homozygous STRC deletions (3, 4). Owing to the high prevalence of the recurrent DIS deletions in both the general population and the individuals with NSHL and the importance of genetic findings in guiding management of NSHL, reporting the deletions of this region in both carriers and affected individuals would be desirable, especially from the commonly used clinical testing platform, such as genome-wide CMA. However, detecting deletions of the DIS region is complicated by the existence of a highly homologous, tandem, segmental duplication that contains nonprocessed pseudogenes for STRC and CATSPER2 (STRCP1 and CATSPER2P1). These pseudogenes are very similar, with STRCP1 being 98.9% identical to STRC across the whole gene, 99.6% identical across the coding sequence, and 100% identical for 15 out of 29 exons. For this reason, targeted testing of this locus requires allele-specific probe-based technologies such as droplet digital PCR (ddPCR) or multiplex ligation-dependent probe amplification (MLPA) to differentiate between STRC and STRCP1 (as well as CATSPER2 from CATSPER2P1) (5). Whereas these methods are highly specific and accurate, it may not be practical to perform additional targeted tests to supplement genome-wide testing like CMA or short-read next-generation genome sequencing. Adding targeted assays not only increases the cost but also the complexity of the test processes. Using a widely utilized genome-wide CMA platform, the study by Sack et al. (6) in this issue of Clinical Chemistry evaluates the viability and practicability of accurately detecting CNVs involving the complicated and highly homologous DIS region without the need for additional, burdensome supplemental testing. By examining the homology of probes from a commonly used array platform located in the DIS region, a set of unique probes without significant pseudogene homology were designated. Targeted evaluation of these unique probes resulted in a 100% concordance against a well-established targeted method, ddPCR, compared to a 40.9% concordance using the automated array software. This study demonstrated the powerful ability of manual evaluation for copy number using the unique probes, while the automated analysis often misassigns the zygosity or miscalculates the number of copies due to the cross-hybridization of the probe to both the genes and pseudogenes. Additionally, the authors created a tool that efficiently automates this manual process. While detection of CNVs in the DIS region on other array platforms has been used in clinical diagnosis (2, 7, 8), this study systematically validated the method for calling the CNVs in the DIS region by a commonly used array platform and developed a process that makes it feasible to incorporate this method into routine laboratory CMA analysis. The clear procedure and strong validation data shown in this work also have the potential to extend this method to other medically relevant genes with high homology, common deletion alleles, and carrier screening recommendations by professional guidelines, such as the alpha-globin locus (HBA1 and HBA2) or congenital adrenal hyperplasia (CYP21A2 and CYP21A1P) (9–11). The presence of highly homologous sequences in the gene regions similar to the DIS area renders them susceptible to nonallelic homologous recombination, leading to a high carrier frequency of deletions in various populations. Clinical laboratories can develop comparable approaches to identify clinically relevant CNVs involving these technically difficult gene regions according to their own needs or patient populations. Short-read next-generation sequencing (NGS)-based assays are routinely used in clinical settings to simultaneously detect sequence, copy number, and structural variants in a single assay and are poised to be the first-tier clinical testing methodology. NGS, however, suffers from the same challenges as arrays, where the genomic regions with high homology may produce inaccurate alignments, resulting in false-positive or false-negative variant calls. If a laboratory reports carrier deletion alleles of well-characterized disorders in highly homologous genes from exome or genome sequencing data, similar approaches as described in Sack’s paper can be used for NGS data by masking nonunique regions. Custom bioinformatics workflows have proven effective in reducing the number of false-positive CNV calls in such nonunique regions. A recent study demonstrated the possibility of accurately detecting CNVs in the STRC region from exome sequencing data by excluding the nonunique exons with poor mappability (12). Similarly, there are other bioinformatics approaches that use differentiating bases to identify CNVs in these challenging regions, and locus-specific callers are increasingly being developed and implemented into clinical practice (13). These locus-specific variant callers enable us to extract more value out of the existing short-read sequencing assays without additional assay costs. None of the manual evaluations of unique array probes, targeted ddPCR and MLPA, or short-read NGS data can accurately identify all CNVs in extremely high homology regions such as the first 15 exons of the STRC gene (5, 6). In addition, the variants in these homologous regions may be even more complicated than what has been recognized. More recently, third-generation long-read sequencing technologies have demonstrated the possibility of sequencing challenging regions with high accuracy and can detect sequence and structural variants with high confidence (11). Similarly, the latest complete long-read technologies are positioned as complementary assays to short-reads by producing synthetic long-reads assembled from “land-marked” long fragments and achieving results similar to those of third-generation sequencing platforms in complex regions of the genome (14). These promising technologies may improve the precise determination of phased copy number and structural variants on a single platform. CNVs represent a significant part of the disease-causing variant spectrum, particularly in genes with high homology. To maximize diagnostic yields, clinical laboratories can push to validate and implement methods that can improve testing sensitivity and specificity on widely utilized and common platforms already in clinical use. The approaches outlined in Sack’s paper to overcome technical barriers in a cost-effective manner could have a significant impact on the clinical laboratory diagnosis and management of patients. CMA, genome-wide chromosomal microarrays; CNVs, copy number variants; NSHL, nonsyndromic hearing loss; DIS, deafness-infertility syndrome; ddPCR, droplet digital PCR; MLPA, multiplex ligation-dependent probe amplification; NGS, next-generation sequencing The corresponding author takes full responsibility that all authors on this publication have met the following required criteria of eligibility for authorship: (a) significant contributions to the conception and design, acquisition of data, or analysis and interpretation of data; (b) drafting or revising the article for intellectual content; (c) final approval of the published article; and (d) agreement to be accountable for all aspects of the article thus ensuring that questions related to the accuracy or integrity of any part of the article are appropriately investigated and resolved. Nobody who qualifies for authorship has been omitted from the list. Minjie Luo (Conceptualization-Lead, Supervision-Lead, Writing—original draft-Lead, Writing—review & editing-Lead), Laura Conlin (Writing—original draft-Supporting, Writing—review & editing-Supporting), and Ramakrishnan Rajagopalan (Writing—original draft-Supporting, Writing—review & editing-Supporting) No authors declared any potential conflicts of interest.
Source: Clinical Chemistry
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: bronze
OpenAlex ID: W4376225455