Chasing Sequencing Perfection: Marching Toward Higher Accuracy and Lower Costs.

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Next-generation sequencing (NGS) is crucial for research but has a significant error rate (10-3).
• This error rate limits applications requiring detection of rare mutations, such as somatic mosaicism and microbial heterogeneity.

Purpose of the Study:

• To review high-fidelity sequencing methods developed over the past decade.
• To identify factors contributing to sequencing errors and strategies for mitigation.
• To propose a classification framework for existing methods and analyze development trends.

Main Methods:

• Systematic review of high-fidelity sequencing methods.
• Analysis of error-inducing factors and mitigation strategies.
• Classification of 11 existing methods and extension to 8 long-read sequencing methods.

Main Results:

• Identified three major factors causing sequencing errors and 12 corresponding mitigation strategies.
• Developed a novel framework to classify 11 representative sequencing methods based on error reduction strategies.
• Observed three key trends in the development of sequencing methodologies.
• Extended the analysis to long-read sequencing methods, focusing on error reduction.

Conclusions:

• Current sequencing error rates pose challenges for rare mutation detection.
• A comprehensive understanding of error reduction strategies is essential for advancing sequencing accuracy.
• Future directions aim to achieve higher accuracy and lower costs in both NGS and long-read sequencing.