Detection of Low-Frequency Mutations and Identification of Heat-Induced Artifactual Mutations Using Duplex Sequencing

We present a genome-wide comparative and comprehensive analysis of three different sequencing methods (conventional next generation sequencing (NGS), tag-based single strand sequencing (e.g., SSCS), and Duplex Sequencing for investigating mitochondrial mutations in human breast epithelial cells. Duplex Sequencing produces a single strand consensus sequence (SSCS) and a duplex consensus sequence (DCS) analysis, respectively. Our study validates that although high-frequency mutations are detectable by all the three sequencing methods with the similar accuracy and reproducibility, rare (low-frequency) mutations are not accurately detectable by NGS and SSCS. Even with conservative bioinformatical modification to overcome the high error rate of NGS, the NGS frequency of rare mutations is 7.0 × 10^-4. The frequency is reduced to 1.3 × 10^-4 with SSCS and is further reduced to 1.0 × 10^-5 using DCS. Rare mutation context spectra obtained from NGS significantly vary across independent experiments, and it is not possible to identify a dominant mutation context. In contrast, rare mutation context spectra are consistently similar in all independent DCS experiments. We have systematically identified heat-induced artifactual variants and corrected the artifacts using Duplex Sequencing. Specific sequence contexts were analyzed to examine the effects of neighboring bases on the accumulation of heat-induced artifactual variants. All of these artifacts are stochastically occurring rare mutations. C > A/G > T, a signature of oxidative damage, is the most increased (170-fold) heat-induced artifactual mutation type. Our results strongly support the claim that Duplex Sequencing accurately detects low-frequency mutations and identifies and corrects artifactual mutations introduced by heating during DNA preparation.