CIRCLE-seq: A Novel Method for Genome-Wide CRISPR Off-Target Effect Detection

Development and Application of CIRCLE-seq for Detection of CRISPR-Cas9 Off-Targets

In June 2017, Nature Methods published a paper titled "CIRCLE-seq: a highly sensitive in vitro screen for genome-wide CRISPR-Cas9 nuclease off-targets," detailing the development of CIRCLE-seq, a highly sensitive method for detecting CRISPR-Cas9 induced off-target effects through sequencing. This novel approach presents a significant advancement in the field of CRISPR technology by offering higher sensitivity and efficiency compared to previously established methods such as Digenome-seq. Notably, CIRCLE-seq demonstrates an improved signal-to-noise ratio and a substantial reduction in the number of sequencing reads required due to its heightened sensitivity.

CRISPR-Cas9 technology has gained widespread application due to its simplicity and versatility. However, the potential for off-target editing remains a critical concern. Identifying the locations and frequencies of nuclease-induced off-target mutations is essential for assessing the precision of CRISPR-Cas9 applications. Existing methods for in vivo genome-wide off-target identification may miss low-frequency (less than 0.1%) off-target mutations. Additionally, these methods often require efficient cell transfection, which poses challenges regarding their feasibility, reproducibility, and scalability, particularly when applied to therapeutically relevant normal cells.

For lean more about CIRCLE-seq, refer to: Comprehensive Review of Circle Sequencing.

For further details about Digenome-seq, please refer to Analysis of Genome-Wide CRISPR-Cas9 Off-Target in Human Cells Using Digenome-seq.

Current Techniques

To date, Digenome-seq represents the only in vitro method for genome-wide off-target identification based on whole-genome sequencing (WGS). However, Digenome-seq analyses demand extensive read coverage and are hampered by high background noise, complicating the detection of low-frequency off-target mutations. Consequently, the development of a novel strategy for identifying low-frequency CRISPR/Cas9 off-target mutations across the entire genome is imperative.

Overview of CIRCLE-seq Technology

The CIRCLE-seq library preparation process is outlined as follows:

Figure 1. Overview of CIRCLE-seq methods for detection of genome-wide CRISPR-Cas9 nuclease cleavage

The process begins with the circularization of the target DNA. Subsequently, linear DNA molecules that are not required are degraded by nucleic acid exonucleases. Circular DNA molecules containing cleavage sites are then linearized using CRISPR-Cas9. After ligation of adaptors, high-throughput sequencing is performed to identify CRISPR/Cas9 off-target mutations across the entire genome.

Comparative Analysis of CIRCLE-seq with GUIDE-seq and HTGTS Methods

The research team conducted a comparative analysis between CIRCLE-seq and GUIDE-seq, the latter of which was previously developed by the team as a method for identifying off-target sites across the whole genome in vivo. A total of six single guide RNAs (sgRNAs) were tested. CIRCLE-seq detected nearly all off-target sites identified by GUIDE-seq. Furthermore, the two off-target sites not detected by CIRCLE-seq were found to occur at frequencies close to the detection limit of GUIDE-seq. An increase in sequencing depth for CIRCLE-seq would enable the detection of these two off-target sites. Additionally, CIRCLE-seq confirmed 50 out of 53 off-target sites identified through high-throughput genome-wide translocation sequencing (HTGTS), and detected a greater number of off-target sites beyond those identified by HTGTS.

Figure 2. Comparisons of CIRCLE-seq with cell-based GUIDE-seq and HTGTS methods

Association of CIRCLE-seq Off-Target Sites with Single Nucleotide Polymorphisms (SNPs)

The research team employed CIRCLE-seq to analyze genomic DNA from K562 human cell lines. Subsequent analyses revealed that among the six sgRNAs tested, eight of the off-target sites identified by CIRCLE-seq corresponded to SNPs outside of the reference SNP sites. This finding potentially elucidates the specificity of cell type effects on cleavage efficiency. Notably, these SNPs were located within the target sequences and adjacent to the protospacer adjacent motif (PAM).

Further investigation into the 1,247 off-target sites identified by CIRCLE-seq for the six sgRNAs indicated that approximately 2.5% of these sites exhibited genetic variation, which aligns with expectations. Additionally, the study observed an increased range of mismatches at off-target sites. Collectively, these results underscore the necessity of considering individual genetic variation when detecting off-target editing events.

Figure 3. CIRCLE-seq detected off-target cleavage sites can also be cleaved in human cells

Figure 4. Using CIRCLE-seq to assess the impacts of personalized SNPs on off-target site analysis

Conclusions

CIRCLE-seq represents a highly sensitive and efficient in vitro method for off-target detection, facilitating automation and scalability. Compared to the results obtained with Digenome-seq, CIRCLE-seq demonstrates a superior signal-to-noise ratio. Unlike previous in vitro methods, CIRCLE-seq relies on next-generation sequencing (NGS) and does not necessitate a reference genome sequence. Notably, this method is capable of identifying off-target edits associated with cell-type-specific SNPs, demonstrating its ability to perform personalized analysis of off-target events across the entire genome. In summary, CIRCLE-seq provides a rapid and comprehensive approach for identifying off-target mutations on a genome-wide scale.