Methods to improve the accuracy of next-generation sequencing - Cheng, Chu; Fei, Zhongjie; Xiao, Pengfeng (Frontiers in Bioengineering and Biotechnology, 2023)
Next-generation sequencing (NGS) is present in all fields of life science, which has greatly promoted the development of basic research while being gradually applied in clinical diagnosis. However, the cost and throughput advantages of NGS are offset by large tradeoffs with respect to read length and accuracy. Specifically, its high error rate makes it extremely difficult to detect SNPs or low-abundance mutations, limiting its clinical applications, such as pharmacogenomics studies primarily based on SNP and early clinical diagnosis primarily based on low abundance mutations. Currently, Sanger sequencing is still considered to be the gold standard due to its high accuracy, so the results of NGS require verification by Sanger sequencing in clinical practice. In order to maintain high quality NGS data, a variety of improvements at the levels of template preparation, sequencing strategy and data processing have been developed. This study summarized the general procedures of NGS platforms, highlighting the improvements involved in eliminating errors at each step. Furthermore, the challenges and future development of NGS in clinical application was discussed.