Evaluation of a target region capture sequencing platform using monogenic diabetes as a study-model
1 BGI-Shenzhen, Shenzhen, China
2 The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
3 XiangYa Medical School, Central South University, Changsha, China
4 Steno Diabetes Center, Gentofte, Denmark
5 Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark
6 Department of Biology, University of Copenhagen, Copenhagen, Denmark
BMC Genetics 2014, 15:13 doi:10.1186/1471-2156-15-13Published: 29 January 2014
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.
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.
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.