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

Area of Science:

• Molecular Biology
• Genetics
• Bioinformatics

Background:

• Genome editing relies on programmable nucleases (PNs), like CRISPR-Cas, for efficient DNA cleavage.
• Assessing PN efficiency typically involves analyzing indels resulting from double-strand breaks.
• Sanger sequencing coupled with web tools offers a user-friendly method for estimating indel frequencies.

Purpose of the Study:

• To evaluate the accuracy of four popular web tools (TIDE, ICE, DECODR, SeqScreener) for analyzing genome editing outcomes.
• To compare the performance of these tools with varying indel complexities and knock-in sequences.
• To identify limitations in computational indel analysis for programmable nuclease efficiency assessment.

Main Methods:

• Utilized artificial sequencing templates with predetermined indels to benchmark web tool performance.
• Compared indel frequency and sequence deconvolution accuracy across TIDE, ICE, DECODR, and SeqScreener.
• Analyzed the impact of simple versus complex indels and knock-in sequences on tool estimations.

Main Results:

• Web tools accurately estimated indel frequencies for simple indels with minor base changes.
• Increased variability in indel frequency estimations was observed with complex indels and knock-in sequences.
• While net indel sizes were estimated reliably, sequence deconvolution capabilities varied among the tools.

Conclusions:

• The accuracy of web-based indel analysis tools is dependent on the complexity of genome editing outcomes.
• Users must exercise caution and select tools judiciously based on the specific genome editing application.
• Further development may be needed to improve the deconvolution of complex indel sequences in genome editing analysis.