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Published on: April 11, 2016
Ultrasensitive and high-efficiency screen of de novo low-frequency mutations by o2n-seq
Kaile Wang1,2,3, Shujuan Lai2, Xiaoxu Yang4
1Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences, Pengfei Road No. 7, Dapeng New District, Shenzhen, Guangdong 518120, China.
Abstract:
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.
Insights
A new method, o2n-seq, enhances next-generation sequencing (NGS) for detecting rare mutations in cancer genomes. This ultrasensitive approach improves efficiency and accuracy for characterizing cell populations.
Area of Science:
- Genomics
- Molecular Biology
- Cancer Research
Background:
- Detecting de novo, low-frequency mutations is critical for cancer genome and cell population characterization.
- Current next-generation sequencing (NGS) methods face limitations in screening capacity due to inefficient read utilization and amplification bias.
Purpose of the Study:
- To introduce o2n-seq, an ultrasensitive and high-efficiency NGS library preparation method.
- To enable the discovery of de novo, low-frequency mutations with improved sensitivity and specificity.
Main Methods:
- Developed o2n-seq, an NGS library preparation technique.
- Evaluated o2n-seq's error rate, data usage efficiency, sensitivity, and specificity.
- Applied o2n-seq to screen for de novo mutations in human tumors.
Main Results:
- O2n-seq reduces NGS error rates to 10-5-10-8.
- Achieved 10-30 times higher data usage efficiency compared to barcode-based strategies.
- Demonstrated high sensitivity (99%) and specificity (98.64%) for detecting 1% allele frequency mutations and 100% specificity for 0.07% allele frequency mutations.
Conclusions:
- O2n-seq is a powerful tool for ultrasensitive detection of low-frequency mutations.
- The method significantly improves upon existing NGS techniques for genomic analysis.
- O2n-seq will advance the characterization of somatic mutations in both research and clinical settings.
