Pre-capture multiplexing provides additional power to detect copy number variation in exome sequencing.

BACKGROUND: As exome sequencing (ES) integrates into clinical practice, we should make every effort to utilize all information generated. Copy-number variation can lead to Mendelian disorders, but small copy-number variants (CNVs) often get overlooked or obscured by under-powered data collection. Many groups have developed methodology for detecting CNVs from ES, but existing methods often perform poorly for small CNVs and rely on large numbers of samples not always available to clinical laboratories. Furthermore, methods often rely on Bayesian approaches requiring user-defined priors in the setting of insufficient prior knowledge. This report first demonstrates the benefit of multiplexed exome capture (pooling samples prior to capture), then presents a novel detection algorithm, mcCNV ("multiplexed capture CNV"), built around multiplexed capture. RESULTS: We demonstrate: (1) multiplexed capture reduces inter-sample variance; (2) our mcCNV method, a novel depth-based algorithm for detecting CNVs from multiplexed capture ES data, improves the detection of small CNVs. We contrast our novel approach, agnostic to prior information, with the the commonly-used ExomeDepth. In a simulation study mcCNV demonstrated a favorable false discovery rate (FDR). When compared to calls made from matched genome sequencing, we find the mcCNV algorithm performs comparably to ExomeDepth. CONCLUSION: Implementing multiplexed capture increases power to detect single-exon CNVs. The novel mcCNV algorithm may provide a more favorable FDR than ExomeDepth. The greatest benefits of our approach derive from (1) not requiring a database of reference samples and (2) not requiring prior information about the prevalance or size of variants.

Increasing the diagnostic yield of exome sequencing by copy number variant analysis.

As whole exome sequencing (WES) becomes more widely used in the clinical realm, a wealth of unanalyzed information will be routinely generated. Using WES read depth data to predict copy number variation (CNV) could extend the diagnostic utility of this previously underutilized data by providing clinically important information such as previously unsuspected deletions or duplications. We evaluated ExomeDepth, a free R package, in addition to an aneuploidy prediction method, to detect CNVs in WES data. First, in a blinded pilot study, five out of five genomic alterations were correctly identified from clinical samples with previously defined chromosomal gains or losses, including submicroscopic deletions, duplications, and chromosomal trisomy. We then examined CNV calls among 53 patients participating in the NCGENES research study and undergoing WES, who had existing clinical chromosomal microarray (CMA) data that could be used for validation. For unique CNVs that overlap well with WES coverage regions, sensitivity was 89% for deletions and 65% for duplications. While specificity of the algorithm calls remains a concern, this is less of an issue at high threshold filtering levels. When applied to all 672 patients from the exome sequencing study, ExomeDepth identified eleven diagnostically relevant CNVs ranging in size from a two exon deletion to whole chromosome duplications, as well as numerous other CNVs with varying clinical significance. This opportunistic analysis of WES data yields an additional 1.6% of patients in this study with pathogenic or likely pathogenic CNVs that are clinically relevant to their phenotype as well as clinically relevant secondary findings. Finally, we demonstrate the potential value of copy number analysis in cases where a single heterozygous likely or known pathogenic single nucleotide alteration is identified in a gene associated with an autosomal recessive condition.

Diagnostic utility of exome sequencing in the evaluation of neuromuscular disorders.

OBJECTIVE: To evaluate the diagnostic yield and workflow of genome-scale sequencing in patients with neuromuscular disorders (NMDs). METHODS: We performed exome sequencing in 93 undiagnosed patients with various NMDs for whom a molecular diagnosis was not yet established. Variants on both targeted and broad diagnostic gene lists were identified. Prior diagnostic tests were extracted from the patient's medical record to evaluate the use of exome sequencing in the context of their prior diagnostic workup. RESULTS: The overall diagnostic yield of exome sequencing in our cohort was 12.9%, with one or more pathogenic or likely pathogenic variants identified in a causative gene associated with the patient's disorder. Targeted gene lists had the same diagnostic yield as a broad NMD gene list in patients with clear neuropathy or myopathy phenotypes, but evaluation of a broader set of disease genes was needed for patients with complex NMD phenotypes. Most patients with NMD had undergone prior testing, but only 10/16 (63%) of these procedures, such as muscle biopsy, were informative in pointing to a final molecular diagnosis. CONCLUSIONS: Genome-scale sequencing or analysis of a panel of relevant genes used early in the evaluation of patients with NMDs can provide or clarify a diagnosis and minimize invasive testing in many cases.

Genetic Complexity of Mitral Valve Prolapse Revealed by Clinical and Genetic Evaluation of a Large Family.

BACKGROUND: A genetic component to familial mitral valve prolapse (MVP) has been proposed for decades. Despite this, very few genes have been linked to MVP. Herein is described a four-generation pedigree with numerous individuals affected with severe MVP, some at strikingly young ages. METHODS: A detailed clinical evaluation performed on all affected family members demonstrated a spectrum of MVP morphologies and associated phenotypes. RESULTS: Linkage analysis failed to identify strong candidate loci, but revealed significant regions, which were investigated further using whole-exome sequencing of one of the severely affected family members. Whole-exome sequencing identified variants in this individual that fell within linkage analysis peak regions, but none was an obvious pathogenic candidate. Follow up segregation analysis of all exome-identified variants was performed to genotype other affected and unaffected individuals in the family, but no variants emerged as clear pathogenic candidates. Two notable variants of uncertain significance in candidate genes were identified: p.I1013S in PTPRJ at 11p11.2 and FLYWCH1 p.R540Q at 16p13.3. Neither gene has been previously linked to MVP in humans, although PTPRJ mutant mice display defects in endocardial cushions, which give rise to the cardiac valves. PTPRJ and FLYWCH1 expression was detected in adult human mitral valve cells, and in-silico analysis of these variants suggests they may be deleterious. However, neither variant segregated completely with all of the affected individuals in the family, particularly when 'affected' was broadly defined. CONCLUSIONS: While a contributory role for PTPRJ and FLYWCH1 in this family cannot be excluded, the study results underscored the difficulties involved in uncovering the genomic contribution to MVP, even in apparently Mendelian families.