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Aims: DNA-based carrier screening is a standard component of donor eligibility protocols practiced by U.S. sperm banks. Applicants who test positive for carrying a recessive disease mutation are typically disqualified. The aim of our study was to examine the utility of a range of screening panels adopted by the industry and the effectiveness of the screening paradigm in reducing a future child's risk of inheriting disease. Methods: A cohort of 27 donor applicants, who tested negative on an initial cystic fibrosis carrier test, was further screened with three expanded commercial carrier testing panels. These results were then compared to a systematic analysis of the applicants' DNA using next-generation sequencing (NGS) data. Results: The carrier panels detected serious pediatric disease mutations in one, four, or six donor applicants. Because each panel screens distinct regions of the genome, no single donor was uniformly identified as carrier positive by all three panels. In contrast, systematic NGS analysis identified all donors as carriers of one or more mutations associated with severe monogenic pediatric disease. These included 30 variants classified as “pathogenic” based on clinical observation and 66 with a high likelihood of causing gene dysfunction. Conclusion: Despite tremendous advances in variant identification, understanding, and analysis, the vast majority of disease-causing mutation combinations remain undetected by commercial carrier screening panels, which cover a narrow, and often distinct, subset of genes and mutations. The biological reality is that all donors and recipients carry serious recessive disease mutations. This challenges the utility of any screening protocol that anchors donor eligibility to carrier status. A more effective approach to reducing recessive disease risk would consider joint comprehensive analysis of both donor and recipient disease mutations. This type of high-resolution recessive disease risk analysis is now available and affordable, but industry practice must be modified to incorporate its use.

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BackgroundDetection of copy number variants (CNVs) is an important aspect of clinical testing for several disorders, including Duchenne muscular dystrophy, and is often performed using multiplex ligation-dependent probe amplification (MLPA). However, since many genetic carrier screens depend instead on next-generation sequencing (NGS) for wider discovery of small variants, they often do not include CNV analysis. Moreover, most computational techniques developed to detect CNVs from exome sequencing data are not suitable for carrier screening, as they require matched normals, very large cohorts, or extensive gene panels.MethodsWe present a computational software package, geneCNV (http://github.com/vkozareva/geneCNV), which can identify exon-level CNVs using exome sequencing data from only a few genes. The tool relies on a hierarchical parametric model trained on a small cohort of reference samples.ResultsUsing geneCNV, we accurately inferred heterozygous CNVs in the DMD gene across a cohort of 15 test subjects. These results were validated against MLPA, the current standard for clinical CNV analysis in DMD. We also benchmarked the tool’s performance against other computational techniques and found comparable or improved CNV detection in DMD using data from panels ranging from 4,000 genes to as few as 8 genes.ConclusionsgeneCNV allows for the creation of cost-effective screening panels by allowing NGS sequencing approaches to generate results equivalent to bespoke genotyping assays like MLPA. By using a parametric model to detect CNVs, it also fulfills regulatory requirements to define a reference range for a genetic test. It is freely available and can be incorporated into any Illumina sequencing pipeline to create clinical assays for detection of exon duplications and deletions.Electronic supplementary materialThe online version of this article (10.1186/s12920-018-0404-4) contains supplementary material, which is available to authorized users.

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