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Next-generation sequencing (NGS) is now routinely used to interrogate large sets of genes in a diagnostic setting. Regions of high sequence homology continue to be a major challenge for short-read technologies and can lead to false-positive and false-negative diagnostic errors. At the scale of whole-exome sequencing (WES), laboratories may be limited in their knowledge of genes and regions that pose technical hurdles due to high homology. We have created an exome-wide resource that catalogs highly homologous regions that is tailored toward diagnostic applications. This resource was developed using a mappability-based approach tailored to current Sanger and NGS protocols. Gene-level and exon-level lists delineate regions that are difficult or impossible to analyze via standard NGS. These regions are ranked by degree of affectedness, annotated for medical relevance, and classified by the type of homology (within-gene, different functional gene, known pseudogene, uncharacterized noncoding region). Additionally, we provide a list of exons that cannot be analyzed by short-amplicon Sanger sequencing. This resource can help guide clinical test design, supplemental assay implementation, and results interpretation in the context of high homology. Genet Med18 12, 1282–1289.

Genomic reports are primarily organized in a narrative and unstructured format with variations in content and format. Regulatory requirements and professional guidelines for genetic test reporting exist but provide little guidance for effective communication of information. To assess clinical genomic reporting practices across 5 disciplines within molecular diagnostics, including germline, somatic solid tumors, somatic hematologic malignancies, pharmacogenomics, and prenatal cell-free DNA screening. Reporting practices were assessed by using a structured review of clinical genomic reports from multiple laboratories in 5 molecular disciplines spanning different practice settings. Report content was reviewed by the presence/absence of from 27 to 44 elements, including 23 elements required by the College of American Pathologists and/or the Clinical Laboratory Improvement Amendments of 1988 (CLIA). If present, the element's location on the report was recorded. A total of 69 genomics reports from 31 laboratories were reviewed. Overall, the reports were compliant with regulatory requirements but showed variability in both format and content. Six of 7 required reporting elements (per CLIA, 42 CFR [Code of Federal Regulations] 493.1291) were included in 90% of the reports. However, these elements were often located in different report sections. Only patient demographics were always found in a specific report section (header). These results show that reports are overall compliant with regulatory requirements, despite some reporting elements being less consistently reported. The lack of consistent presentation of the data elements presents an opportunity to improve the communication of molecular testing results to clinicians and patients.

Clinical exome sequencing (CES) has become the preferred diagnostic platform for complex pediatric disorders with suspected monogenic etiologies. Despite rapid advancements, the major challenge still resides in identifying the casual variants among the thousands of variants detected during CES testing, and thus establishing a molecular diagnosis. To improve the clinical exome diagnostic efficiency, we developed Phenoxome, a robust phenotype-driven model that adopts a network-based approach to facilitate automated variant prioritization. Phenoxome dissects the phenotypic manifestation of a patient in concert with their genomic profile to filter and then prioritize variants that are likely to affect the function of the gene (potentially pathogenic variants). To validate our method, we have compiled a clinical cohort of 105 positive patient samples that represent a wide range of genetic heterogeneity. Phenoxome identifies the causative variants within the top 5, 10, or 25 candidates in more than 50%, 71%, or 88% of these exomes, respectively. Furthermore, we show that our method is optimized for clinical testing by outperforming the current state-of-art method. We have demonstrated the performance of Phenoxome using a clinical cohort and showed that it enables rapid and accurate interpretation of clinical exomes. Phenoxome is available at https://phenoxome.chop.edu/.

Pediatric cardiomyopathy is rare, has a broad differential diagnosis, results in high morbidity and mortality, and has suboptimal diagnostic yield using next-generation sequencing panels. Exome sequencing has reported diagnostic yields ranging from 30% to 57% for neonates in intensive care units. We aimed to characterize the clinical utility of exome sequencing in infantile heart failure. Infants diagnosed with acute heart failure prior to 1 year old over a period of 34 months at a large tertiary children’s hospital were recruited. Demographic and diagnostic information was obtained from medical records. Fifteen eligible patients were enrolled. Dilated cardiomyopathy was the predominant cardiac diagnosis, seen in 60% of patients. A molecular diagnosis was identified in 66.7% of patients (10/15). Of those diagnoses, 70% would not have been detected using multigene next-generation sequencing panels focused on cardiomyopathy or arrhythmia disease genes. Genetic testing changed medical decision-making in 53% of all cases and 80% of positive cases, and was especially beneficial when testing was expedited. Given the broad differential diagnosis and critical status of infants with heart failure, rapid exome sequencing provides timely diagnoses, changes medical management, and should be the first-tier molecular test.

Hearing loss (HL) is the most common sensory disorder in children. Prompt molecular diagnosis may guide screening and management, especially in syndromic cases when HL is the single presenting feature. Exome sequencing (ES) is an appealing diagnostic tool for HL as the genetic causes are highly heterogeneous. ES was performed on a prospective cohort of 43 probands with HL. Sequence data were analyzed for primary and secondary findings. Capture and coverage analysis was performed for genes and variants associated with HL. The diagnostic rate using ES was 37.2%, compared with 15.8% for the clinical HL panel. Secondary findings were discovered in three patients. For 247 genes associated with HL, 94.7% of the exons were targeted for capture and 81.7% of these exons were covered at 20× or greater. Further analysis of 454 randomly selected HL-associated variants showed that 89% were targeted for capture and 75% were covered at a read depth of at least 20×. ES has an improved yield compared with clinical testing and may capture diagnoses not initially considered due to subtle clinical phenotypes. Technical challenges were identified, including inadequate capture and coverage of HL genes. Additional considerations of ES include secondary findings, cost, and turnaround time.

Hereditary hearing loss is highly heterogeneous. To keep up with rapidly emerging disease-causing genes, we developed the AUDIOME test for nonsyndromic hearing loss (NSHL) using an exome sequencing (ES) platform and targeted analysis for the curated genes. A tiered strategy was implemented for this test. Tier 1 includes combined Sanger and targeted deletion analyses of the two most common NSHL genes and two mitochondrial genes. Nondiagnostic tier 1 cases are subjected to ES and array followed by targeted analysis of the remaining AUDIOME genes. ES resulted in good coverage of the selected genes with 98.24% of targeted bases at >15 ×. A fill-in strategy was developed for the poorly covered regions, which generally fell within GC-rich or highly homologous regions. Prospective testing of 33 patients with NSHL revealed a diagnosis in 11 (33%) and a possible diagnosis in 8 cases (24.2%). Among those, 10 individuals had variants in tier 1 genes. The ES data in the remaining nondiagnostic cases are readily available for further analysis. The tiered and ES-based test provides an efficient and cost-effective diagnostic strategy for NSHL, with the potential to reflex to full exome to identify causal changes outside of the AUDIOME test.

Targeted DNA enrichment coupled with next generation sequencing has been increasingly used for interrogation of select sub-genomic regions at high depth of coverage in a cost effective manner. Specificity measured by on-target efficiency is a key performance metric for target enrichment. Non-specific capture leads to off-target reads, resulting in waste of sequencing throughput on irrelevant regions. Microdroplet-PCR allows simultaneous amplification of up to thousands of regions in the genome and is among the most commonly used strategies for target enrichment. Here we show that carryover of single-stranded template genomic DNA from microdroplet-PCR constitutes a major contributing factor for off-target reads in the resultant libraries. Moreover, treatment of microdroplet-PCR enrichment products with a nuclease specific to single-stranded DNA alleviates off-target load and improves enrichment specificity. We propose that nuclease treatment of enrichment products should be incorporated in the workflow of targeted sequencing using microdroplet-PCR for target capture. These findings may have a broad impact on other PCR based applications for which removal of template DNA is beneficial.

Introduction: RASopathies include disorders generally characterized by developmental delay, specific heart defects, short stature, cardiac hypertrophy, and facial dysmorphisms. Next-generation sequencing (NGS)-based panels have widespread acceptance as a diagnostic tool for RASopathies. Materials and methods: The first 126 patients evaluated by clinical examination and the NGS RASopathy panel at the Children’s Hospital of Philadelphia were enrolled. We calculated diagnosis rate, correlated reported clinical findings with positive or negative test results, and identified final molecular diagnoses in 28/96 patients who tested negative for RASopathies. Results: Twenty-four patients had pathogenic variants on the RASopathy panel, for a diagnostic yield of 19%. Reported features of pulmonic stenosis and ptosis were significantly correlated with a positive test result; no reported features were significantly correlated with a negative test result. We identified 27 different alternative diagnoses for patients originally suspected of having RASopathies. Discussion: This study provides information that can assist in guiding differential diagnosis and genetic testing for patients suspected of having a RASopathy disorder. Genet Med advance online publication 20 October 2016

Purpose As massively parallel sequencing is increasingly being used for clinical decision making, it has become critical to understand parameters that affect sequencing quality and to establish methods for measuring and reporting clinical sequencing standards. In this report, we propose a definition for reduced coverage regions and describe a set of standards for variant calling in clinical sequencing applications. Methods To enable sequencing centers to assess the regions of poor sequencing quality in their own data, we optimized and used a tool (ExCID) to identify reduced coverage loci within genes or regions of particular interest. We used this framework to examine sequencing data from 500 patients generated in 10 projects at sequencing centers in the National Human Genome Research Institute/National Cancer Institute Clinical Sequencing Exploratory Research Consortium. Results This approach identified reduced coverage regions in clinically relevant genes, including known clinically relevant loci that were uniquely missed at individual centers, in multiple centers, and in all centers. Conclusion This report provides a process road map for clinical sequencing centers looking to perform similar analyses on their data.

Genomic medicine holds great promise for improving health care, but integrating searchable and actionable genetic data into electronic health records (EHRs) remains a challenge. Here we describe Neptune, a system for managing the interaction between a clinical laboratory and an EHR system during the clinical reporting process. We developed Neptune and applied it to two clinical sequencing projects that required report customization, variant reanalysis, and EHR integration. Neptune has been applied for the generation and delivery of over 15,000 clinical genomic reports. This work spans two clinical tests based on targeted gene panels that contain 68 and 153 genes respectively. These projects demanded customizable clinical reports that contained a variety of genetic data types including single-nucleotide variants (SNVs), copy-number variants (CNVs), pharmacogenomics, and polygenic risk scores. Two variant reanalysis activities were also supported, highlighting this important workflow. Methods are needed for delivering structured genetic data to EHRs. This need extends beyond developing data formats to providing infrastructure that manages the reporting process itself. Neptune was successfully applied on two high-throughput clinical sequencing projects to build and deliver clinical reports to EHR systems. The software is open source and available at https://gitlab.com/bcm-hgsc/neptune.