Assessment of Target Enrichment Platforms Using Massively Parallel Sequencing for the Mutation Detection for Congenital Muscular Dystrophy

Autor: Anne Rutkowski, Devin Rhodenizer, Madhuri Hegde, Lisa Mari Keong, Carsten G. Bönnemann, Shruti Bhide, C. Alexander Valencia, Martin Robert Littlejohn, Ephrem L H Chin
Jazyk: angličtina
Rok vydání: 2012
Předmět:
Popis: Sequencing individual genes by Sanger sequencing is a time-consuming and costly approach to resolve clinically heterogeneous genetic disorders. Panel testing offers the ability to efficiently and cost-effectively screen all of the genes for a particular genetic disorder. We assessed the analytical sensitivity and specificity of two different enrichment technologies, solution-based hybridization and microdroplet-based PCR target enrichment, in conjunction with next-generation sequencing (NGS), to identify mutations in 321 exons representing 12 different genes involved with congenital muscular dystrophies. Congenital muscular dystrophies present diagnostic challenges due to phenotypic variability, lack of standard access to and inherent difficulties with muscle immunohistochemical stains, and a general lack of clinician awareness. NGS results were analyzed across several parameters, including sequencing metrics and genotype concordance with Sanger sequencing. Genotyping data showed that both enrichment technologies produced suitable calls for use in clinical laboratories. However, microdroplet-based PCR target enrichment is more appropriate for a clinical laboratory, due to excellent sequence specificity and uniformity, reproducibility, high coverage of the target exons, and the ability to distinguish the active gene versus known pseudogenes. Regardless of the method, exons with highly repetitive and high GC regions are not well enriched and require Sanger sequencing for completeness. Our study demonstrates the successful application of targeted sequencing in conjunction with NGS to screen for mutations in hundreds of exons in a genetically heterogeneous human disorder.
Databáze: OpenAIRE