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Ensemble of nucleic acid absolute quantitation modules for copy number variation detection and RNA profiling

Author

Listed:
  • Lucia Ruojia Wu

    (Rice University
    Capital Medical University)

  • Peng Dai

    (Rice University
    NuProbe USA)

  • Michael Xiangjiang Wang

    (Rice University)

  • Sherry Xi Chen

    (Rice University
    NuProbe USA)

  • Evan N. Cohen

    (The University of Texas MD Anderson Cancer Center)

  • Gitanjali Jayachandran

    (The University of Texas MD Anderson Cancer Center)

  • Jinny Xuemeng Zhang

    (NuProbe USA)

  • Angela V. Serrano

    (NuProbe USA)

  • Nina Guanyi Xie

    (Rice University)

  • Naoto T. Ueno

    (The University of Texas MD Anderson Cancer Center)

  • James M. Reuben

    (The University of Texas MD Anderson Cancer Center)

  • Carlos H. Barcenas

    (The University of Texas MD Anderson Cancer Center)

  • David Yu Zhang

    (NuProbe USA)

Abstract

Current gold standard for absolute quantitation of a specific DNA sequence is droplet digital PCR (ddPCR), which has been applied to copy number variation (CNV) detection. However, the number of quantitation modules in ddPCR is limited by fluorescence channels, which thus limits the CNV sensitivity due to sampling error following Poisson distribution. Here we develop a PCR-based molecular barcoding NGS approach, quantitative amplicon sequencing (QASeq), for accurate absolute quantitation scalable to over 200 quantitation modules. By attaching barcodes to individual target molecules with high efficiency, 2-plex QASeq exhibits higher and more consistent conversion yield than ddPCR in absolute molecule count quantitation. Multiplexed QASeq improves CNV sensitivity allowing confident distinguishment of 2.05 ploidy from normal 2.00 ploidy. We apply multiplexed QASeq to serial longitudinal plasma cfDNA samples from patients with metastatic ERBB2+ (HER2+ ) breast cancer seeking association with tumor progression. We further show an RNA QASeq panel for targeted expression profiling.

Suggested Citation

  • Lucia Ruojia Wu & Peng Dai & Michael Xiangjiang Wang & Sherry Xi Chen & Evan N. Cohen & Gitanjali Jayachandran & Jinny Xuemeng Zhang & Angela V. Serrano & Nina Guanyi Xie & Naoto T. Ueno & James M. Re, 2022. "Ensemble of nucleic acid absolute quantitation modules for copy number variation detection and RNA profiling," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-29487-y
    DOI: 10.1038/s41467-022-29487-y
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    References listed on IDEAS

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    1. Li Chen & Liu Yang & Ling Yao & Xia-Ying Kuang & Wen-Jia Zuo & Shan Li & Feng Qiao & Yi-Rong Liu & Zhi-Gang Cao & Shu-Ling Zhou & Xiao-Yan Zhou & Wen-Tao Yang & Jin-Xiu Shi & Wei Huang & Xin Hu & Zhi-, 2018. "Characterization of PIK3CA and PIK3R1 somatic mutations in Chinese breast cancer patients," Nature Communications, Nature, vol. 9(1), pages 1-17, December.
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    1. Michael X. Wang & Esther G. Lou & Nicolae Sapoval & Eddie Kim & Prashant Kalvapalle & Bryce Kille & R. A. Leo Elworth & Yunxi Liu & Yilei Fu & Lauren B. Stadler & Todd J. Treangen, 2024. "Olivar: towards automated variant aware primer design for multiplex tiled amplicon sequencing of pathogens," Nature Communications, Nature, vol. 15(1), pages 1-12, December.

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