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High-throughput clinical research testing use a large inherited retinal dystrophy

A research report of the first clinically validated high-throughput next gene sequencing (NGS) technology indicates that sensitivity and specificity had 100% used with the caveat of unclear zygosity calling for one large duplication case. The researchers demonstrated that a reliable NGS-based diagnosis showed by the retinitis pigmentosa GTPase regulator (RPGR) ORF15 mutations. The researchers previously indicated that RPGR mutations can account for >70% of X-linked retinitis pigmentosa (RP) cases. The report stated that the first clinically validated NGS method for the sequencing of ORF15 is “one of the most difficult-to-sequence regions in the genome”.


The collaboration between both US and Australian research teams used as part of a blind-test, 145 research samples previously tested by Sanger sequencing, and 81 clinical samples evaluated using NGS of long-range PCR products fragmented using an ORF15-specific in-silico array. Results of a Nextera library produced 24 cases of discordance due to false-negatives, incorrectly called variants, and a false positive. The research report stated results that, “subsequent use of a new, OneTube NGS library preparation method, supplemented with duplication analyses, resolved discordance between Sanger and NGS data in all cases. This improvement in variant detection accuracy was largely attributed to improvement in random fragmentation offered by the enzymatic OneTube method, resulting in more complete coverage of the highly repetitive ORF15 region. Minimum coverage was roughly 320 reads for Nextera and 6800 reads for OneTube (normalized for total read counts)”.


In analysis of the research the authors for the study concluded that, “the efficacy of the new OneTube sample preparation method, supplemented with duplication analysis, in achieving robust coverage of the entire ORF15 region, with 100% mutation detection sensitivity and specificity for our sample population within a standardized clinical pipeline. A key outcome of this study is the evidence that clinical validation should include previously tested samples in the development of new variant detection methods.”