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Calibration-free NGS quantitation of mutations below 0.01% VAF
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. Her...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8531361/ https://www.ncbi.nlm.nih.gov/pubmed/34675197 http://dx.doi.org/10.1038/s41467-021-26308-6 |
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author | Dai, Peng Wu, Lucia Ruojia Chen, Sherry Xi Wang, Michael Xiangjiang Cheng, Lauren Yuxuan Zhang, Jinny Xuemeng Hao, Pengying Yao, Weijie Zarka, Jabra Issa, Ghayas C. Kwong, Lawrence Zhang, David Yu |
author_facet | Dai, Peng Wu, Lucia Ruojia Chen, Sherry Xi Wang, Michael Xiangjiang Cheng, Lauren Yuxuan Zhang, Jinny Xuemeng Hao, Pengying Yao, Weijie Zarka, Jabra Issa, Ghayas C. Kwong, Lawrence Zhang, David Yu |
author_sort | Dai, Peng |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8531361 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-85313612021-11-15 Calibration-free NGS quantitation of mutations below 0.01% VAF Dai, Peng Wu, Lucia Ruojia Chen, Sherry Xi Wang, Michael Xiangjiang Cheng, Lauren Yuxuan Zhang, Jinny Xuemeng Hao, Pengying Yao, Weijie Zarka, Jabra Issa, Ghayas C. Kwong, Lawrence Zhang, David Yu Nat Commun Article 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. Nature Publishing Group UK 2021-10-21 /pmc/articles/PMC8531361/ /pubmed/34675197 http://dx.doi.org/10.1038/s41467-021-26308-6 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Dai, Peng Wu, Lucia Ruojia Chen, Sherry Xi Wang, Michael Xiangjiang Cheng, Lauren Yuxuan Zhang, Jinny Xuemeng Hao, Pengying Yao, Weijie Zarka, Jabra Issa, Ghayas C. Kwong, Lawrence Zhang, David Yu Calibration-free NGS quantitation of mutations below 0.01% VAF |
title | Calibration-free NGS quantitation of mutations below 0.01% VAF |
title_full | Calibration-free NGS quantitation of mutations below 0.01% VAF |
title_fullStr | Calibration-free NGS quantitation of mutations below 0.01% VAF |
title_full_unstemmed | Calibration-free NGS quantitation of mutations below 0.01% VAF |
title_short | Calibration-free NGS quantitation of mutations below 0.01% VAF |
title_sort | calibration-free ngs quantitation of mutations below 0.01% vaf |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8531361/ https://www.ncbi.nlm.nih.gov/pubmed/34675197 http://dx.doi.org/10.1038/s41467-021-26308-6 |
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