Dataset Information

Clinical analysis of genome next-generation sequencing data using the Omicia platform.

ABSTRACT: AIMS:Next-generation sequencing is being implemented in the clinical laboratory environment for the purposes of candidate causal variant discovery in patients affected with a variety of genetic disorders. The successful implementation of this technology for diagnosing genetic disorders requires a rapid, user-friendly method to annotate variants and generate short lists of clinically relevant variants of interest. This report describes Omicia's Opal platform, a new software tool designed for variant discovery and interpretation in a clinical laboratory environment. The software allows clinical scientists to process, analyze, interpret and report on personal genome files. MATERIALS & METHODS:To demonstrate the software, the authors describe the interactive use of the system for the rapid discovery of disease-causing variants using three cases. RESULTS & CONCLUSION:Here, the authors show the features of the Opal system and their use in uncovering variants of clinical significance.

SUBMITTER: Coonrod EM

PROVIDER: S-EPMC3828661 | biostudies-literature | 2013 Jul

REPOSITORIES: biostudies-literature

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Clinical analysis of genome next-generation sequencing data using the Omicia platform.

Coonrod Emily M EM Margraf Rebecca L RL Russell Archie A Voelkerding Karl V KV Reese Martin G MG

Expert review of molecular diagnostics 20130701 6

<h4>Aims</h4>Next-generation sequencing is being implemented in the clinical laboratory environment for the purposes of candidate causal variant discovery in patients affected with a variety of genetic disorders. The successful implementation of this technology for diagnosing genetic disorders requires a rapid, user-friendly method to annotate variants and generate short lists of clinically relevant variants of interest. This report describes Omicia's Opal platform, a new software tool designed ...[more]

PMID: 23895124

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Project description:Autoinflammatory diseases occupy one of a group of primary immunodeficiency diseases that are generally thought to be caused by mutation of genes responsible for innate immunity, rather than by acquired immunity. Mutations related to autoinflammatory diseases occur in 12 genes. For example, low-level somatic mosaic NLRP3 mutations underlie chronic infantile neurologic, cutaneous, articular syndrome (CINCA), also known as neonatal-onset multisystem inflammatory disease (NOMID). In current clinical practice, clinical genetic testing plays an important role in providing patients with quick, definite diagnoses. To increase the availability of such testing, low-cost high-throughput gene-analysis systems are required, ones that not only have the sensitivity to detect even low-level somatic mosaic mutations, but also can operate simply in a clinical setting. To this end, we developed a simple method that employs two-step tailed PCR and an NGS system, MiSeq platform, to detect mutations in all coding exons of the 12 genes responsible for autoinflammatory diseases. Using this amplicon sequencing system, we amplified a total of 234 amplicons derived from the 12 genes with multiplex PCR. This was done simultaneously and in one test tube. Each sample was distinguished by an index sequence of second PCR primers following PCR amplification. With our procedure and tips for reducing PCR amplification bias, we were able to analyze 12 genes from 25 clinical samples in one MiSeq run. Moreover, with the certified primers designed by our short program-which detects and avoids common SNPs in gene-specific PCR primers-we used this system for routine genetic testing. Our optimized procedure uses a simple protocol, which can easily be followed by virtually any office medical staff. Because of the small PCR amplification bias, we can analyze simultaneously several clinical DNA samples with low cost and can obtain sufficient read numbers to detect a low level of somatic mosaic mutations.

Dataset Information

Clinical analysis of genome next-generation sequencing data using the Omicia platform.

Publications

Clinical analysis of genome next-generation sequencing data using the Omicia platform.

Similar Datasets

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