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

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. Reuben, Carlos H. Barcenas () and David Yu Zhang ()
Additional contact information
Lucia Ruojia Wu: Rice University
Peng Dai: Rice University
Michael Xiangjiang Wang: Rice University
Sherry Xi Chen: Rice University
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

Nature Communications, 2022, vol. 13, issue 1, 1-9

Abstract: 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.

Date: 2022
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/s41467-022-29487-y 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:13:y:2022:i:1:d:10.1038_s41467-022-29487-y

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

DOI: 10.1038/s41467-022-29487-y

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 ().