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Open Access Research article

Pre-capture multiplexing improves efficiency and cost-effectiveness of targeted genomic enrichment

A Eliot Shearer12, Michael S Hildebrand1, Harini Ravi3, Swati Joshi3, Angelica C Guiffre3, Barbara Novak4, Scott Happe3, Emily M LeProust4 and Richard JH Smith125*

Author Affiliations

1 Department of Otolaryngology – Head & Neck Surgery, University of Iowa Carver College of Medicine, Iowa City, IA, 52242, USA

2 Department of Molecular Physiology & Biophysics, University of Iowa Carver College of Medicine, Iowa City, IA, 52242, USA

3 Agilent Technologies, Cedar Creek, TX, USA

4 Agilent Technologies, Santa Clara, CA, USA

5 Interdepartmental PhD Program in Genetics, University of Iowa Carver College of Medicine, Iowa City, IA, 52242, USA

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BMC Genomics 2012, 13:618  doi:10.1186/1471-2164-13-618

Published: 14 November 2012

Abstract

Background

Targeted genomic enrichment (TGE) is a widely used method for isolating and enriching specific genomic regions prior to massively parallel sequencing. To make effective use of sequencer output, barcoding and sample pooling (multiplexing) after TGE and prior to sequencing (post-capture multiplexing) has become routine. While previous reports have indicated that multiplexing prior to capture (pre-capture multiplexing) is feasible, no thorough examination of the effect of this method has been completed on a large number of samples. Here we compare standard post-capture TGE to two levels of pre-capture multiplexing: 12 or 16 samples per pool. We evaluated these methods using standard TGE metrics and determined the ability to identify several classes of genetic mutations in three sets of 96 samples, including 48 controls. Our overall goal was to maximize cost reduction and minimize experimental time while maintaining a high percentage of reads on target and a high depth of coverage at thresholds required for variant detection.

Results

We adapted the standard post-capture TGE method for pre-capture TGE with several protocol modifications, including redesign of blocking oligonucleotides and optimization of enzymatic and amplification steps. Pre-capture multiplexing reduced costs for TGE by at least 38% and significantly reduced hands-on time during the TGE protocol. We found that pre-capture multiplexing reduced capture efficiency by 23 or 31% for pre-capture pools of 12 and 16, respectively. However efficiency losses at this step can be compensated by reducing the number of simultaneously sequenced samples. Pre-capture multiplexing and post-capture TGE performed similarly with respect to variant detection of positive control mutations. In addition, we detected no instances of sample switching due to aberrant barcode identification.

Conclusions

Pre-capture multiplexing improves efficiency of TGE experiments with respect to hands-on time and reagent use compared to standard post-capture TGE. A decrease in capture efficiency is observed when using pre-capture multiplexing; however, it does not negatively impact variant detection and can be accommodated by the experimental design.

Keywords:
Massively parallel sequencing; Next-generation sequencing; Genomics; Targeted genomic enrichment; Sequence capture; Pre-capture multiplexing; Post-capture multiplexing; Indexing