Email updates

Keep up to date with the latest news and content from BMC Genomics and BioMed Central.

Open Access Highly Accessed Research article

Performance comparison of four exome capture systems for deep sequencing

Chandra Sekhar Reddy Chilamakuri13*, Susanne Lorenz134, Mohammed-Amin Madoui14, Daniel Vodák15, Jinchang Sun134, Eivind Hovig1235, Ola Myklebost13 and Leonardo A Meza-Zepeda134*

Author Affiliations

1 Department of Tumor Biology, Oslo University Hospital, Norwegian Radium Hospital, 0310 Oslo, Norway

2 Department of Medical Informatics, Oslo University Hospital, Norwegian Radium Hospital, Oslo, Norway

3 Norwegian Cancer Genomics Consortium, Oslo, Norway

4 Genomics Core Facility, Oslo University Hospital, Oslo, Norway

5 Department of Informatics, University of Oslo, Oslo, Norway

For all author emails, please log on.

BMC Genomics 2014, 15:449  doi:10.1186/1471-2164-15-449

Published: 9 June 2014

Abstract

Background

Recent developments in deep (next-generation) sequencing technologies are significantly impacting medical research. The global analysis of protein coding regions in genomes of interest by whole exome sequencing is a widely used application. Many technologies for exome capture are commercially available; here we compare the performance of four of them: NimbleGen’s SeqCap EZ v3.0, Agilent’s SureSelect v4.0, Illumina’s TruSeq Exome, and Illumina’s Nextera Exome, all applied to the same human tumor DNA sample.

Results

Each capture technology was evaluated for its coverage of different exome databases, target coverage efficiency, GC bias, sensitivity in single nucleotide variant detection, sensitivity in small indel detection, and technical reproducibility. In general, all technologies performed well; however, our data demonstrated small, but consistent differences between the four capture technologies. Illumina technologies cover more bases in coding and untranslated regions. Furthermore, whereas most of the technologies provide reduced coverage in regions with low or high GC content, the Nextera technology tends to bias towards target regions with high GC content.

Conclusions

We show key differences in performance between the four technologies. Our data should help researchers who are planning exome sequencing to select appropriate exome capture technology for their particular application.

Keywords:
Exome capture technology; Next-generation sequencing; Coverage efficiency; Enrichment efficiency; GC bias; Single nucleotide variant; Indel