Systematic Comparison of Computational Tools for Sanger Sequencing-Based Genome Editing Analysis

Abstract

Successful genome editing depends on the cleavage efficiency of programmable nucleases (PNs) such as the CRISPR–Cas system. Various methods have been developed to assess the efficiency of PNs, most of which estimate the occurrence of indels caused by PN-induced double-strand breaks. In these methods, PN genomic target sites are amplified through PCR, and the resulting PCR products are subsequently analyzed using Sanger sequencing, high-throughput sequencing, or mismatch detection assays. Among these methods, Sanger sequencing of PCR products followed by indel analysis using online web tools has gained popularity due to its user-friendly nature. This approach estimates indel frequencies by computationally analyzing sequencing trace data. However, the accuracy of these computational tools remains uncertain. In this study, we compared the performance of four web tools, TIDE, ICE, DECODR, and SeqScreener, using artificial sequencing templates with predetermined indels. Our results demonstrated that these tools were able to estimate indel frequency with acceptable accuracy when the indels were simple and contained only a few base changes. However, the estimated values became more variable among the tools when the sequencing templates contained more complex indels or knock-in sequences. Moreover, although these tools effectively estimated the net indel sizes, their capability to deconvolute indel sequences exhibited variability with certain limitations. These findings underscore the importance of judiciously selecting and using an appropriate tool with caution, depending on the type of genome editing being performed.

Keywords

• ICE
• CRISPR–Cas
• DECODR
• indel analysis
• SeqScreener
• TIDE