The Development and Validation of Clinical Exome-Based Panels Using ExomeSlicer

Abstract

Exome-based panels are becoming the preferred diagnostic strategy in clinical laboratories. This approach enables dynamic gene content update and, if needed, cost-effective reflex to whole-exome sequencing. Currently, no guidelines or appropriate resources are available to support the clinical implementation of exome-based panels. Here, we highlight principles and important considerations for the clinical development and validation of exome-based panels. In addition, we developed ExomeSlicer, a novel, web-based resource, which uses empirical exon-level next-generation sequencing quality metrics to predict and visualize technically challenging exome-wide regions in any gene or genes of interest. Exome sequencing data from 100 clinical epilepsy cases were used to illustrate the clinical utility of ExomeSlicer in predicting poor-quality regions and its impact on streamlining the ad hoc Sanger sequencing fill in burden. With the use of ExomeSlicer,>2100 low complexity and/or high-homology regions affecting >1615 genes across the exome were also characterized. These regions can be a source of false-positive or false-negative variant calls, which can lead to misdiagnoses in tested patients and/or inaccurate functional annotations. We provide important considerations and a novel resource for the clinical development of exome-based panels.

A single‐center SCN8A‐related epilepsy cohort: clinical, genetic, and physiologic characterization

“…For in‐house testing, we performed a comprehensive exome‐based sequencing and copy number analysis of 100 epilepsy‐associated genes. Genomic DNA was extracted from peripheral blood to obtain DNA material for sequencing and an in‐house bioinformatics pipeline was used for analysis . After filtering, variants were classified using published guidelines from the American College of Medical Genetics and Genomics …”

Use of a Dynamic Genetic Testing Approach for Childhood-Onset Epilepsy

“…Genomic DNA was obtained from peripheral blood or other patient tissues following standard DNA extraction protocols and was prepared for ES using previously described procedures. 14 An in-house bioinformatics pipeline 15 was used for NGS data analysis, including variant filtration and annotation. Only variants in the epilepsy panel regions of interest were retained (eMethods 1 in the Supplement ).…”

“…The minor allele frequency cutoffs were calculated as previously described. 15 Variants were then filtered based on their frequencies in the Exome Aggregation Consortium database.…”

A mutation update for the PCDH19 gene causing early-onset epilepsy in females with an unusual expression pattern

“…For that we made several safe assumptions. We conservatively assumed a PCDH19 ‐related epilepsy prevalence of 1/10,000, which is an overestimate exceeding that of SCN1A ‐related epilepsy prevalence of 1/22,000 (Bayat, Hjalgrim, & Moller, ; Niazi et al, ). Assuming only one pathogenic PCDH19 variant (although several are known to cause disease in this gene) with only 50% penetrance, and using a dominant inheritance model, we calculate, using Hardy–Weinberg equation (Whiffin et al., ), the allele frequency of this variant to be 1 × 10 −4 .…”