TY - JOUR
T1 - Ultrasensitive and high-efficiency screen of de novo low-frequency mutations by o2n-seq
AU - Wang, Kaile
AU - Lai, Shujuan
AU - Yang, Xiaoxu
AU - Zhu, Tianqi
AU - Lu, Xuemei
AU - Wu, Chung I.
AU - Ruan, Jue
N1 - Funding Information:
We are grateful to Yuxiao Chang for discussions of this manuscript. This work was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB13040300), National key research and development program of China (2016YFC1200602), Fund of Key Laboratory of Shenzhen (ZDSYS20141118170111640), National Key Basic Research Program of China (2014CB542006), the Natural Science Foundation of China (91531305, 31571353) and Agricultural Science and Technology Innovation Program (ASTIP).
Publisher Copyright:
© The Author(s) 2017.
PY - 2017/5/22
Y1 - 2017/5/22
N2 - Detection of de novo, low-frequency mutations is essential for characterizing cancer genomes and heterogeneous cell populations. However, the screening capacity of current ultrasensitive NGS methods is inadequate owing to either low-efficiency read utilization or severe amplification bias. Here, we present O2n-seq, an ultrasensitive and high-efficiency NGS library preparation method for discovering de novo, low-frequency mutations. O2n-seq reduces the error rate of NGS to 10-5-10-8. The efficiency of its data usage is about 10-30 times higher than that of barcode-based strategies. For detecting mutations with allele frequency (AF) 1% in 4.6 Mb-sized genome, the sensitivity and specificity of O2n-seq reach to 99% and 98.64%, respectively. For mutations with AF around 0.07% in phix174, o2n-seq detects all the mutations with 100% specificity. Moreover, we successfully apply o2n-seq to screen de novo, low-frequency mutations in human tumours. O2n-seq will aid to characterize the landscape of somatic mutations in research and clinical settings.
AB - Detection of de novo, low-frequency mutations is essential for characterizing cancer genomes and heterogeneous cell populations. However, the screening capacity of current ultrasensitive NGS methods is inadequate owing to either low-efficiency read utilization or severe amplification bias. Here, we present O2n-seq, an ultrasensitive and high-efficiency NGS library preparation method for discovering de novo, low-frequency mutations. O2n-seq reduces the error rate of NGS to 10-5-10-8. The efficiency of its data usage is about 10-30 times higher than that of barcode-based strategies. For detecting mutations with allele frequency (AF) 1% in 4.6 Mb-sized genome, the sensitivity and specificity of O2n-seq reach to 99% and 98.64%, respectively. For mutations with AF around 0.07% in phix174, o2n-seq detects all the mutations with 100% specificity. Moreover, we successfully apply o2n-seq to screen de novo, low-frequency mutations in human tumours. O2n-seq will aid to characterize the landscape of somatic mutations in research and clinical settings.
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U2 - 10.1038/ncomms15335
DO - 10.1038/ncomms15335
M3 - Article
C2 - 28530222
AN - SCOPUS:85020243737
SN - 2041-1723
VL - 8
JO - Nature communications
JF - Nature communications
M1 - 15335
ER -