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Background: The high error rate of next generation sequencing (NGS) restricts some of its applications, such as monitoring virus mutations and detecting rare mutations in tumors. There are two commonly employed sequencing library preparation strategies to improve sequencing accuracy by correcting sequencing errors: read-pairing method and tag-clustering method (i.e. primer ID or UID). Here, we constructed a homogeneous library from a single clone, and compared the variant calling accuracy of these error-correction methods., Result: We comprehensively described the strengths and pitfalls of these methods. We found that both read-pairing and tag-clustering methods significantly decreased sequencing error rate. While the read-pairing method was more effective than the tag-clustering method at correcting insertion and deletion errors, it was not as effective as the tag-clustering method at correcting substitution errors. In addition, we observed that when the read quality was poor, the tag-clustering method led to huge coverage loss. We also tested the effect of applying quality score filtering to the error-correction methods and demonstrated that quality score filtering was able to impose a minor, yet statistically significant improvement to the error-correction methods tested in this study., Conclusion: Our study provides a benchmark for researchers to select suitable error-correction methods based on the goal of the experiment by balancing the trade-off between sequencing cost (i.e. sequencing coverage requirement) and detection sensitivity.

Background: Epistasis is one of the central themes in viral evolution due to its importance in drug resistance, immune escape, and interspecies transmission. However, there is a lack of experimental approach to systematically probe for epistatic residues., Results: By utilizing the information from natural occurring sequences and high-throughput genetics, this study established a novel strategy to identify epistatic residues. The rationale is that a substitution that is deleterious in one strain may be prevalent in nature due to the presence of a naturally occurring compensatory substitution. Here, high-throughput genetics was applied to influenza A virus M segment to systematically identify deleterious substitutions. Comparison with natural sequence variation showed that a deleterious substitution M1 Q214H was prevalent in circulating strains. A coevolution analysis was then performed and indicated that M1 residues 121, 207, 209, and 214 naturally coevolved as a group. Subsequently, we experimentally validated that M1 A209T was a compensatory substitution for M1 Q214H., Conclusions: This work provided a proof-of-concept to identify epistatic residues by coupling high-throughput genetics with phylogenetic information. In particular, we were able to identify an epistatic interaction between M1 substitutions A209T and Q214H. This analytic strategy can potentially be adapted to study any protein of interest, provided that the information on natural sequence variants is available.