Increasing the Yield in Targeted Next-Generation Sequencing by Implicating CNV Analysis, Non-Coding Exons and the Overall Variant Load: The Example of Retinal Dystrophies

Abstract

Retinitis pigmentosa (RP) and Leber congenital amaurosis (LCA) are major causes of blindness. They result from mutations in many genes which has long hampered comprehensive genetic analysis. Recently, targeted next-generation sequencing (NGS) has proven useful to overcome this limitation. To uncover “hidden mutations” such as copy number variations (CNVs) and mutations in non-coding regions, we extended the use of NGS data by quantitative readout for the exons of 55 RP and LCA genes in 126 patients, and by including non-coding 5′ exons. We detected several causative CNVs which were key to the diagnosis in hitherto unsolved constellations, e.g. hemizygous point mutations in consanguineous families, and CNVs complemented apparently monoallelic recessive alleles. Mutations of non-coding exon 1 of EYS revealed its contribution to disease. In view of the high carrier frequency for retinal disease gene mutations in the general population, we considered the overall variant load in each patient to assess if a mutation was causative or reflected accidental carriership in patients with mutations in several genes or with single recessive alleles. For example, truncating mutations in RP1, a gene implicated in both recessive and dominant RP, were causative in biallelic constellations, unrelated to disease when heterozygous on a biallelic mutation background of another gene, or even non-pathogenic if close to the C-terminus. Patients with mutations in several loci were common, but without evidence for di- or oligogenic inheritance. Although the number of targeted genes was low compared to previous studies, the mutation detection rate was highest (70%) which likely results from completeness and depth of coverage, and quantitative data analysis. CNV analysis should routinely be applied in targeted NGS, and mutations in non-coding exons give reason to systematically include 5′-UTRs in disease gene or exome panels. Consideration of all variants is indispensable because even truncating mutations may be misleading.

Next generation sequencing‐based copy number analysis reveals low prevalence of deletions and duplications in 46 genes associated with genetic cardiomyopathies

“…In addition to a higher number of genes, targeting a wider variant spectrum is expected to lead to increased yield, as has been demonstrated for inclusion of CNV testing for many genetic disorders (Eisenberger et al. 2013; Shearer et al. 2014).…”

Solving the molecular diagnostic testing conundrum for Mendelian disorders in the era of next-generation sequencing: single-gene, gene panel, or exome/genome sequencing

“…There have been reports on limitations and challenges in the clinical application of ES, including some that showed the likelihood of this approach missing variants and diagnoses. 11,12 From technical and reporting perspectives, there are significant differences between these two NGS-based tests ( Table 2).…”

Expanding the clinical, allelic, and locus heterogeneity of retinal dystrophies

“…This homozygous variant is absent in 615 Saudi exomes and in the ExAC browser (Supplementary Figure S2 online). ABCA4 [13] TULP1 [10] MERTK [8] CRB1 [7] RPE65 [7] RPGRIP1 [7] I MPG2 [6] KCNV2 [6] NR2E3 [6] RP1 [6] ALMS1 [5] CNGA3 [5] RDH12 [5] AIPL1 [4] CNGB1 [4] CRX [4] GUCY2D [4] SPATA7 [4] BBS2 [3] BBS4 [3] C8orf37 [3] CDHR1 [3] FAM161A [3] PDE6C [3] RLBP1 [3] USH2A [3] BBS10 [2] BBS5 [2] BBS7 [2] CERKL [2] CNNM4 [2] GRP179 [2] LRP5 [2] PDE6B [2] P ROM1 [2] PRPH2 [2] RP2 [2] SNRNP200 [2] ADAM9 [1] ADAMTS18 [1] ARL6 [1] BBS9 [1] BEST1 [1] C2ORF71 [1] CACNA1F [1] CEP290 [1] CHM [1] EFEMP1 [1] EYS …”

“…This technology is particularly suited for such a genetically and clinically heterogeneous condition as RD, and this has been demonstrated by several studies. [7][8][9][10][11][12][13] In this study, we describe the application of a next-generation sequencing-based gene panel strategy to study a very large cohort of RD patients in the diagnostic phase. In the discovery phase, we genotyped all familial cases that tested negative on the assay and identified three that mapped to a single locus and subjected them to whole-exome sequencing, which led us to identify AGBL5 and CDH16 as two novel RD candidate disease genes.…”