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Updated: Feb 15, 2026

Detection of Rare Mutations in CtDNA Using Next Generation Sequencing
Published on: August 24, 2017
URMD-Seq: A high-throughput method for scalable detection of ultra-rare mutations in the human mitochondrial genome
Zeshuo E S Li1, Rachel Dunn1, Loïc C Caloren1
1Department of Pathology & Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada.
Abstract:
The study of mitochondrial genetics has long been limited to polymorphisms and high frequency mutations owing in part to technical and technological limitations in reliably detecting and quantifying rare somatic mutations. Over the past decade or so, the study of rare somatic mitochondrial DNA (mtDNA) variants has expanded and continues to garner increasing interest in a wide range of research fields. Here, we describe Ultra-Rare Mutation Detection-Sequencing (URMD-Seq), a high-throughput method that combines unique molecular identifier (UMI)-based library preparation and Next Generation Sequencing (NGS) for the accurate and scalable detection of ultra-rare mutations in the mtDNA control region. Our method exploits degenerate primers to label individual mtDNA molecules. This is followed by several purification, quantification and amplification steps, to obtain high quality amplicons for sequencing on the Illumina MiSeq platform. Our approach enables the use of total genomic DNA extract as starting point for the assay, overcoming the need for organelle isolation and/or mtDNA enrichment, hence broadening the type of specimen that can be studied, while offering cost and time benefits. The assay described herein has been demonstrated to reliably measure variants present at on average 0.09%, but as low as 0.03%, variant allele frequency in a variety of tissues, including fresh and frozen biobanked specimens. Using this protocol, library preparation of 300 specimens can be completed by a single individual with general nucleic acid handling experience in approximately 20 days. Given its flexibility and scalability, URMD-Seq is particularly well suited for epidemiological studies using a large number of specimens.
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