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Ultrasensitive and high-efficiency screen of de novo low-frequency mutations by o2n-seq

Author

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  • Kaile Wang

    (Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences
    Key Laboratory of Genomics and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Shujuan Lai

    (Key Laboratory of Genomics and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences)

  • Xiaoxu Yang

    (Center for Bioinformatics, State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University)

  • Tianqi Zhu

    (Institute of Applied Mathematics, Academy of Mathematics and Systems Science, Chinese Academy of Sciences
    Key Laboratory of Random Complex Structures and Data Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences)

  • Xuemei Lu

    (Key Laboratory of Genomics and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences)

  • Chung-I Wu

    (Key Laboratory of Genomics and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences
    State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University
    University of Chicago)

  • Jue Ruan

    (Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences)

Abstract

Detection of de novo, low-frequency mutations is essential for characterizing cancer genomes and heterogeneous cell populations. However, the screening capacity of current ultrasensitive NGS methods is inadequate owing to either low-efficiency read utilization or severe amplification bias. Here, we present o2n-seq, an ultrasensitive and high-efficiency NGS library preparation method for discovering de novo, low-frequency mutations. O2n-seq reduces the error rate of NGS to 10−5–10−8. The efficiency of its data usage is about 10–30 times higher than that of barcode-based strategies. For detecting mutations with allele frequency (AF) 1% in 4.6 Mb-sized genome, the sensitivity and specificity of o2n-seq reach to 99% and 98.64%, respectively. For mutations with AF around 0.07% in phix174, o2n-seq detects all the mutations with 100% specificity. Moreover, we successfully apply o2n-seq to screen de novo, low-frequency mutations in human tumours. O2n-seq will aid to characterize the landscape of somatic mutations in research and clinical settings.

Suggested Citation

  • Kaile Wang & Shujuan Lai & Xiaoxu Yang & Tianqi Zhu & Xuemei Lu & Chung-I Wu & Jue Ruan, 2017. "Ultrasensitive and high-efficiency screen of de novo low-frequency mutations by o2n-seq," Nature Communications, Nature, vol. 8(1), pages 1-11, August.
  • Handle: RePEc:nat:natcom:v:8:y:2017:i:1:d:10.1038_ncomms15335
    DOI: 10.1038/ncomms15335
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