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<p>Molecular barcoding methods enable high-sensitivity detection of circulating tumor DNA that is rarely present in liquid biopsy samples. Many methods involve ligation of molecular barcodes to DNA prior to hybridization capture, enabling recovery of starting molecules. Development of polymerase chain reaction (PCR)-based methods could facilitate more cost- and labor- effective detection; however, tracking molecular identity can be difficult, as new barcodes overwrite old barcodes in each cycle. Here, we present a sensitive genotyping method based on a peer-to-peer network-derived identifier for error reduction in amplicon sequencing (SPIDER-seq) and enable molecular identity tracking with PCR-derived libraries using overwritten barcodes. SPIDER-seq detected mutations at frequences as low as 0.125% after only two consecutive general PCR cycles and systematically analyzed the error pattern in the peer-to-peer network. Our method could facilitate the rapid detection of mutations associated with various cancers.</p>

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Correcting errors in PCR-derived libraries for rare allele detection by reconstructing parental and daughter strand information

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月24日

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  • Hyeonseob Lim,
  • Soyeong Jun,
  • Taehoon Kim,
  • Ji Hyun Lee,
  • Duhee Bang

摘要

Molecular barcoding methods enable high-sensitivity detection of circulating tumor DNA that is rarely present in liquid biopsy samples. Many methods involve ligation of molecular barcodes to DNA prior to hybridization capture, enabling recovery of starting molecules. Development of polymerase chain reaction (PCR)-based methods could facilitate more cost- and labor- effective detection; however, tracking molecular identity can be difficult, as new barcodes overwrite old barcodes in each cycle. Here, we present a sensitive genotyping method based on a peer-to-peer network-derived identifier for error reduction in amplicon sequencing (SPIDER-seq) and enable molecular identity tracking with PCR-derived libraries using overwritten barcodes. SPIDER-seq detected mutations at frequences as low as 0.125% after only two consecutive general PCR cycles and systematically analyzed the error pattern in the peer-to-peer network. Our method could facilitate the rapid detection of mutations associated with various cancers.