Comprehensive gene panels provide advantages over clinical exome sequencing for Mendelian diseases

Abstract

BackgroundTo understand the contribution of Mendelian mutations to the burden of undiagnosed diseases that are suspected to be genetic in origin, we developed a next-generation sequencing-based multiplexing assay that encompasses the ~3000 known Mendelian genes. This assay, which we term the Mendeliome, comprises 13 gene panels based on clinical themes, covering the spectrum of pediatric and adult clinical genetic medicine. We explore how these panels compare with clinical whole exome sequencing (WES).ResultsWe tested 2357 patients referred with suspected genetic diagnoses from virtually every medical specialty. A likely causal mutation was identified in 1018 patients, with an overall clinical sensitivity of 43 %, comparing favorably with WES. Furthermore, the cost of clinical-grade WES is high (typically more than 4500 US dollars), whereas the cost of running a sample on one of our panels is around 75–150 US dollars, depending on the panel. Of the “negative” cases, 11 % were subsequently found by WES to harbor a likely causal mutation in a known disease gene (largely in genes identified after the design of our assay), as inferred from a representative sample of 178. Although our study population is enriched for consanguinity, 245 (24 %) of solved cases were autosomal dominant and 35 (4 %) were X-linked, suggesting that our assay is also applicable to outbred populations.ConclusionsDespite missing a significant number of cases, the current version of the Mendeliome assay can account for a large proportion of suspected genetic disorders, and provides significant practical advantages over clinical WES.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-015-0693-2) contains supplementary material, which is available to authorized users.

Novel phenotypes and loci identified through clinical genomics approaches to pediatric cataract

“…A panel of 322 genes known to be mutated in various genetic eye conditions, including those involving cataract was designed as described before (Group SM 2015). All index cases were initially run on this panel as a first-tier test.…”

“…All index cases were initially run on this panel as a first-tier test. Details of the bioinformatics analysis are published elsewhere (Group SM 2015). Variants were called according to the ACMG guidelines on variant interpretation.…”

“…All cases in which the multi-gene panel failed to identify a likely causal mutation were exome sequenced as described before (Group SM 2015). The surviving variants were analyzed based on zygosity (depending on family pedigree), predicted pathogenicity based on SIFT, Polyphen and combined annotation-dependent depletion (CADD) scores (for missense variants), prioritizing truncating variants, location within the autozygome (for AR cases) and frequency below 0.01 within in-house (2200 exomes), and ExAC databases.…”

Next-generation sequencing in neuromuscular diseases

“…It has been an invaluable tool in gene discovery, with around 100 genes linked with neuromuscular disorders discovered in this way (38) such as the identification of ADCK3 mutations using exome sequencing as shown in Figure 3 and 5. However, less-reachable regions of the genome with low sequence complexity restrict the ability to design useful WES capture baits, and differences in the hybridization efficiency of WES capture probes can result in off target capture effects as well as regions of the genome such as in exon 1, or GC-rich regions, with little or no coverage (33, 37, 39–41). …”

Advantages and pitfalls of an extended gene panel for investigating complex neurometabolic phenotypes

“…An alternative NGS method, gene panel testing, has recently become available in clinical services and offers targeted testing of candidate genes. An extended genetic panel approach to investigating IEM might be advantageous (Saudi Mendeliome Group, 2015) due to reduced times required for data processing and increased coverage depth compared to WES and WGS. Our objective was to investigate the utility of this approach by designing an IEM gene panel and applying it to patients presenting with a wide array of neurometabolic phenotypes.…”