Application of next-generation sequencing in the detection of low-abundance mutations

Abstract

Mutation accumulation in somatic cells contributes to cancer development, aging and many non-malignant diseases. The true mutation frequency in normal cells is extremely low, which presents a challenge in detecting these mutations at such low frequencies. The emergence of next-generation sequencing (NGS) technology enables direct detection of rare mutations across the entire genome of any species. This breakthrough overcomes numerous limitations of traditional mutation detection techniques that rely on specific detection models and sites. However, conventional NGS is limited in its application for detecting low-frequency mutations due to its high sequencing error rate. To address this challenge, high-accuracy NGS sequencing techniques based on molecular consensus sequencing strategies have been developed. These techniques have the ability to correct sequencing errors, resulting in error rates lower than 10^-7, are expected to serve as effective tools for low-frequency mutation detection. Error-corrected NGS (ecNGS) techniques hold great potential in various areas, including safety evaluation and research on environmental mutagens, risk assessment of cell and gene therapy drugs, population health risk monitoring, and fundamental research in life sciences. This review highlights a comprehensive review of the research progress in low-frequency mutation detection techniques based on NGS, and provides a glimpse into their potential applications. It also offers an outlook on the potential applications of these techniques, thereby providing valuable insights for further development, research, and application of this technology in relevant fields.

Keywords: low-abundance mutations; molecular consensus sequencing; mutagenesis; next-generation sequencing; risk assessment.