Copy-number variation contributes 9% of pathogenicity in the inherited retinal degenerations
E Zampaglione, B Kinde, EM Place… - Genetics in …, 2020 - nature.com
Genetics in Medicine, 2020•nature.com
Purpose Current sequencing strategies can genetically solve 55–60% of inherited retinal
degeneration (IRD) cases, despite recent progress in sequencing. This can partially be
attributed to elusive pathogenic variants (PVs) in known IRD genes, including copy-number
variations (CNVs), which have been shown as major contributors to unsolved IRD cases.
Methods Five hundred IRD patients were analyzed with targeted next-generation
sequencing (NGS). The NGS data were used to detect CNVs with ExomeDepth and gCNV …
degeneration (IRD) cases, despite recent progress in sequencing. This can partially be
attributed to elusive pathogenic variants (PVs) in known IRD genes, including copy-number
variations (CNVs), which have been shown as major contributors to unsolved IRD cases.
Methods Five hundred IRD patients were analyzed with targeted next-generation
sequencing (NGS). The NGS data were used to detect CNVs with ExomeDepth and gCNV …
Purpose
Current sequencing strategies can genetically solve 55–60% of inherited retinal degeneration (IRD) cases, despite recent progress in sequencing. This can partially be attributed to elusive pathogenic variants (PVs) in known IRD genes, including copy-number variations (CNVs), which have been shown as major contributors to unsolved IRD cases.
Methods
Five hundred IRD patients were analyzed with targeted next-generation sequencing (NGS). The NGS data were used to detect CNVs with ExomeDepth and gCNV and the results were compared with CNV detection with a single-nucleotide polymorphism (SNP) array. Likely causal CNV predictions were validated by quantitative polymerase chain reaction (qPCR).
Results
Likely disease-causing single-nucleotide variants (SNVs) and small indels were found in 55.6% of subjects. PVs in USH2A (11.6%), RPGR (4%), and EYS (4%) were the most common. Likely causal CNVs were found in an additional 8.8% of patients. Of the three CNV detection methods, gCNV showed the highest accuracy. Approximately 30% of unsolved subjects had a single likely PV in a recessive IRD gene.
Conclusion
CNV detection using NGS-based algorithms is a reliable method that greatly increases the genetic diagnostic rate of IRDs. Experimentally validating CNVs helps estimate the rate at which IRDs might be solved by a CNV plus a more elusive variant.
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