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Rapid and efficient human mutation detection using a bench-top next-generation DNA sequencer

Authors

  • Qian Jiang,

    1. Center for Complex Disease Genomics, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
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  • Tychele Turner,

    1. Center for Complex Disease Genomics, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
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  • Maria X. Sosa,

    1. Center for Complex Disease Genomics, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
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  • Ankit Rakha,

    1. Center for Complex Disease Genomics, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
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  • Stacey Arnold,

    1. Center for Complex Disease Genomics, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
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  • Aravinda Chakravarti

    Corresponding author
    1. Center for Complex Disease Genomics, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
    • Center for Complex Disease Genomics, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, 733 N. Broadway, BRB Suite 579, Baltimore, MD 21205.
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  • Communicated by Ian N. M. Day

Abstract

Next-generation sequencing (NGS) technologies can be a boon to human mutation detection given their high throughput: consequently, many genes and samples may be simultaneously studied with high coverage for accurate detection of heterozygotes. In circumstances requiring the intensive study of a few genes, particularly in clinical applications, a rapid turn around is another desirable goal. To this end, we assessed the performance of the bench-top 454 GS Junior platform as an optimized solution for mutation detection by amplicon sequencing of three type 3 semaphorin genes SEMA3A, SEMA3C, and SEMA3D implicated in Hirschsprung disease (HSCR). We performed mutation detection on 39 PCR amplicons totaling 14,014 bp in 47 samples studied in pools of 12 samples. Each 10-hr run was able to generate ∼75,000 reads and ∼28 million high-quality bases at an average read length of 371 bp. The overall sequencing error was 0.26 changes per kb at a coverage depth of ≥20 reads. Altogether, 37 sequence variants were found in this study of which 10 were unique to HSCR patients. We identified five missense mutations in these three genes that may potentially be involved in the pathogenesis of HSCR and need to be studied in larger patient samples. Hum Mutat 33:281–289, 2012. © 2011 Wiley Periodicals, Inc.

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