Background
Monogenic diabetes is a genetic disease often caused by mutations in genes involved in beta-cell function. Correct sub-categorization of the disease is a prerequisite for appropriate treatment and genetic counseling. Target-region capture sequencing is a combination of genomic region enrichment and next generation sequencing which might be used as an efficient way to diagnose various genetic disorders. We aimed to develop a target-region capture sequencing platform to screen 117 selected candidate genes involved in metabolism for mutations and to evaluate its performance using monogenic diabetes as a study-model.
Conclusions
We hereby demonstrated that the established platform as an accurate and high-throughput gene testing method which might be useful in the clinical diagnosis of monogenic diabetes.
Results
The performance of the assay was evaluated in 70 patients carrying known disease causing mutations previously identified in HNF4A, GCK, HNF1A, HNF1B, INS, or KCNJ11. Target regions with a less than 20-fold sequencing depth were either introns or UTRs. When only considering translated regions, the coverage was 100% with a 50-fold minimum depth. Among the 70 analyzed samples, 63 small size single nucleotide polymorphisms and indels as well as 7 large deletions and duplications were identified as being the pathogenic variants. The mutations identified by the present technique were identical with those previously identified through Sanger sequencing and Multiplex Ligation-dependent Probe Amplification. Conclusions: We hereby demonstrated that the established platform as an accurate and high-throughput gene testing method which might be useful in the clinical diagnosis of monogenic diabetes.