Calibration-free NGS quantitation of mutations below 0.01% VAF

Peng Dai, Lucia Ruojia Wu, Sherry Xi Chen, Michael Xiangjiang Wang, Lauren Yuxuan Cheng, Jinny Xuemeng Zhang, Pengying Hao, Weijie Yao, Jabra Zarka, Ghayas C. Issa, Lawrence Kwong and David Yu Zhang ()
Additional contact information
Peng Dai: Rice University
Lucia Ruojia Wu: Rice University
Sherry Xi Chen: Rice University
Michael Xiangjiang Wang: Rice University
Lauren Yuxuan Cheng: Rice University
Jinny Xuemeng Zhang: NuProbe USA
Pengying Hao: NuProbe USA
Weijie Yao: NuProbe USA
Jabra Zarka: The University of Texas MD Anderson Cancer Center
Ghayas C. Issa: The University of Texas MD Anderson Cancer Center
Lawrence Kwong: The University of Texas MD Anderson Cancer Center
David Yu Zhang: Rice University

Nature Communications, 2021, vol. 12, issue 1, 1-9

Abstract: Abstract Quantitation of rare somatic mutations is essential for basic research and translational clinical applications including minimal residual disease (MRD) detection. Though unique molecular identifier (UMI) has suppressed errors for rare mutation detection, the sequencing depth requirement is high. Here, we present Quantitative Blocker Displacement Amplification (QBDA) which integrates sequence-selective variant enrichment into UMI quantitation for accurate quantitation of mutations below 0.01% VAF at only 23,000X depth. Using a panel of 20 genes recurrently altered in acute myeloid leukemia, we demonstrate quantitation of various mutations including single base substitutions and indels down to 0.001% VAF at a single locus with less than 4 million sequencing reads, allowing sensitive MRD detection in patients during complete remission. In a pan-cancer panel and a melanoma hotspot panel, we detect mutations down to 0.1% VAF using only 1 million reads. QBDA provides a convenient and versatile method for sensitive mutation quantitation using low-depth sequencing.

Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.nature.com/articles/s41467-021-26308-6 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-26308-6

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-021-26308-6

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().