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Single duplex DNA sequencing with CODEC detects mutations with high sensitivity

delete2023-04-27
delete24
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OA
AI
J
Jin H. Bae
R
Ruolin Liu
E
Eugenia Roberts
E
Erica Nguyen
S
Shervin Tabrizi
J
Justin Rhoades
T
Timothy Blewett
K
Kan Xiong
G
Gregory Gydush
D
Douglas Shea
Z
Zhenyi An
S
Sahil Patel
J
Ju Cheng
S
Sainetra Sridhar
M
Mei Hong Liu
E
Emilie Lassen
A
Anne‐Bine Skytte
M
Marta Grońska-Pęski
J
Jonathan E. Shoag
G
Gilad D. Evrony
H
Heather A. Parsons
E
Erica L. Mayer
G
G. Mike Makrigiorgos
T
Todd R. Golub
V
Viktor A. Adalsteinsson *
DOI:10.1038/s41588-023-01376-0delete
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摘要

摘要

En 中文
Concatenating Original Duplex for Error Correction (CODEC) is a method that concatenates both strands of each DNA duplex to enable highly sensitive mutation detection in a range of analytes with fewer reads and lower error rates than current methods. Detecting mutations from single DNA molecules is crucial in many fields but challenging. Next-generation sequencing (NGS) affords tremendous throughput but cannot directly sequence double-stranded DNA molecules ('single duplexes') to discern the true mutations on both strands. Here we present Concatenating Original Duplex for Error Correction (CODEC), which confers single duplex resolution to NGS. CODEC affords 1,000-fold higher accuracy than NGS, using up to 100-fold fewer reads than duplex sequencing. CODEC revealed mutation frequencies of 2.72 x 10(-8) in sperm of a 39-year-old individual, and somatic mutations acquired with age in blood cells. CODEC detected genome-wide, clonal hematopoiesis mutations from single DNA molecules, single mutated duplexes from tumor genomes and liquid biopsies, microsatellite instability with 10-fold greater sensitivity and mutational signatures, and specific tumor mutations with up to 100-fold fewer reads. CODEC enables more precise genetic testing and reveals biologically significant mutations, which are commonly obscured by NGS errors.
Keyword:
RARE MUTATIONS
QUANTIFICATION
EVOLUTION
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期刊

Nature Reviews Endocrinology 封面图
Nature Reviews Endocrinology
IF:
40
论文数:
1.0W
被引数:
10.5W

机构

M
Massachusetts General Hospital
学者数:
3.4W
论文数: 2.6W
被引数: 8.6W
H
Harvard University
学者数:
26.5W
论文数: 22.0W
被引数: 28.7W
N
New York University
学者数:
4.4W
论文数: 3.9W
被引数: 5.8W
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