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Hi-Plex for Simple, Accurate, and Cost-Effective Amplicon-based Targeted DNA Sequencing

  • Bernard J. Pope
  • Fleur Hammet
  • Tu Nguyen-Dumont
  • Daniel J. Park
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1712)

Abstract

Hi-Plex is a suite of methods to enable simple, accurate, and cost-effective highly multiplex PCR-based targeted sequencing (Nguyen-Dumont et al., Biotechniques 58:33–36, 2015). At its core is the principle of using gene-specific primers (GSPs) to “seed” (or target) the reaction and universal primers to “drive” the majority of the reaction. In this manner, effects on amplification efficiencies across the target amplicons can, to a large extent, be restricted to early seeding cycles. Product sizes are defined within a relatively narrow range to enable high-specificity size selection, replication uniformity across target sites (including in the context of fragmented input DNA such as that derived from fixed tumor specimens (Nguyen-Dumont et al., Biotechniques 55:69–74, 2013; Nguyen-Dumont et al., Anal Biochem 470:48–51, 2015), and application of high-specificity genetic variant calling algorithms (Pope et al., Source Code Biol Med 9:3, 2014; Park et al., BMC Bioinformatics 17:165, 2016). Hi-Plex offers a streamlined workflow that is suitable for testing large numbers of specimens without the need for automation.

Key words

Amplicon sequencing Targeted sequencing Massively parallel sequencing Next-generation sequencing Multiplex PCR Hi-Plex Sequence screening Mutation screening 

Notes

Acknowledgments

The development of Hi-Plex has been supported by the Australian National Health and Medical Research Council (NHMRC) project grants 1025879 and 1108179, Cancer Council Victoria project grant 1066612 and the Victorian Life Sciences Computation Initiative (VLSCI) resource allocation VR0182.

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Copyright information

© Springer Science+Business Media, LLC 2018

Authors and Affiliations

  • Bernard J. Pope
    • 1
  • Fleur Hammet
    • 2
  • Tu Nguyen-Dumont
    • 2
  • Daniel J. Park
    • 1
    • 2
  1. 1.Melbourne BioinformaticsThe University of MelbourneParkvilleAustralia
  2. 2.Genomic Technologies Group, Genetic Epidemiology Laboratory, Department of MedicineThe University of MelbourneParkvilleAustralia

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