Amplicon-Based Off-Target Site Verification

Amplicon-Based Off-Target Site Verification

1. Background

According to the latest FDA guidance document on gene therapy products (January 2024), regulatory agencies have put forward comprehensive requirements for the safety evaluation of gene therapy products incorporating human genome editing. The guidance particularly emphasizes the importance of identification and verification of off-target editing events, including full analysis of type, frequency, and location. The regulatory requirement states: "Verification of off-target sites should be conducted using methods with adequate sensitivity to detect low frequency events" and that off-target site sources should employ multiple methods (e.g., bioinformatic prediction, biochemical analysis, and cell-based analysis) for genome-wide analysis to reduce bias in the identification of potential off-target sites.

Figure 1. FDA guidance document Human Gene Therapy Products Incorporating Human Genome Editing: requirements for off-target site verification

Under this regulatory landscape, amplicon-based off-target verification has emerged as a highly sensitive off-target detection method. Through site-specific primer design and high-throughput sequencing technology, precise detection and quantification of low-frequency off-target events (≥0.1%) can be achieved. The amplicon-based approach offers advantages including high sensitivity and quantifiability, and is particularly well-suited for deep analysis of multiple samples and multiple sites. It effectively meets regulatory requirements for precise verification of off-target events. To ensure technical reliability and accuracy, ZhuHai GeneRulor has conducted comprehensive method validation in strict accordance with ICH Q2(R1) guidelines and the FDA Guidance for Industry on Analytical Procedures and Methods Validation for Drugs and Biologics, establishing a complete technical evaluation framework. ZhuHai GeneRulor has successfully provided gene-editing safety evaluation services compliant with regulatory standards to numerous domestic and international gene therapy companies, fully supporting IND submissions and clinical translation.

2. Amplicon Detection Principle

Amplicon-based off-target detection focuses on the genomic regions surrounding off-target sites. Genomic DNA is first extracted from samples; site-specific primers are then designed. Following the first round of site-specific PCR amplification, magnetic bead purification removes impurities. A second round of indexed PCR is then performed to add sample-specific barcodes. High-throughput sequencing is subsequently used to acquire target region sequence information, and finally bioinformatics analysis is applied to identify sequence characteristics and quantify off-target editing efficiency. The detailed detection workflow comprises the following steps:

(1) Based on sequence information of the potential off-target regions, design site-specific primers with complementary binding;

(2) Using the extracted genomic DNA as a template, employ the designed site-specific primers to specifically amplify the target genomic loci by PCR;

(3) Exploit the property of magnetic beads binding DNA in specific buffers to adsorb PCR-product DNA, removing primer dimers and other impurities to purify the PCR products;

(4) The second-round indexed PCR amplifies the purified PCR products using primers carrying sample-specific barcodes (indices);

(5) Apply NGS technology to perform high-throughput sequencing of the target genomic regions from both rounds of PCR amplification, rapidly obtaining large quantities of DNA sequence information;

(6) Finally, bioinformatics analysis processes and interprets the massive dataset obtained from NGS.

Figure 2. Amplicon-based off-target verification library construction workflow

3. Amplicon Off-Target Site Verification Advantages

3.1 Comprehensive and Precise Detection of Off-Target Editing Events

(1) Precise quantitative analysis: the CRISPResso2 analysis tool enables highly accurate quantification of different types of editing events (substitutions, insertions, deletions, etc.), providing a comprehensive off-target characterization analysis;

(2) Low-frequency off-target detection: capable of detecting rare off-target events at frequencies as low as 0.01%, substantially improving the sensitivity of gene-editing safety evaluation;

(3) Intuitive visualization: editing event visualizations are provided in the report, directly displaying editing loci and editing types, facilitating researchers in understanding off-target characteristics in greater depth.

3.2 Outstanding Analytical Performance

ZhuHai GeneRulor rigorously follows ICH Q2(R1) guidelines, conducting systematic method validation of the amplicon-based off-target verification approach. Validation results are as follows:

3.3 Service Advantages

(1) Comprehensive method validation: amplicon-based off-target verification has undergone systematic validation with a full 0.001%–50% linear dynamic range demonstrating high sensitivity and precision;

(2) Regulatory compliance assurance: strictly adheres to ICH Q2(R1) and FDA guidance requirements, ensuring detection results comply with international regulatory standards;

(3) Leading technology platform: capable of comprehensive detection of multiple off-target mutation types induced by gene editing, including substitutions, insertions, and deletions, meeting safety evaluation needs at all stages of biological research;

(4) Rich success case portfolio: services have been successfully delivered to numerous domestic and international gene therapy companies, supporting smooth IND submissions;

(5) Rapid report turnaround: a standardized data processing workflow enables rapid transformation from sequencing data to analytical report, shortening project cycle time.

4. Application Scenarios for Amplicon Off-Target Verification

(1) Gene therapy IND submission: provision of off-target safety evaluation data compliant with regulatory requirements for gene-editing product development;

(2) Gene-editing tool optimization: quantification of the off-target effects of differently designed sgRNAs to guide the development of safer gene-editing tools;

(3) Cell product quality control: off-target detection for cell therapy products based on gene editing such as CAR-T to ensure product safety.

5. Case Studies

The amplicon-based off-target verification analytical reports provided by ZhuHai GeneRulor adopt a standardized format to ensure professional and comprehensive data presentation. The introductory section covers project background, experimental rationale, technical principles, library construction workflow description, and bioinformatics analysis pipeline overview, providing clients with the necessary technical context. This is followed by sample information and sequencing data statistics, which include sample metadata (sample ID, experimental/control group classification, sgRNA sequences, and nucleic acid type), raw sequencing data quality metrics, and control group alignment result statistics, ensuring data quality and reliability. In addition, the report includes the following key components:

(1) Provision of a comprehensive gene-editing efficiency analysis table displaying key metrics including: total aligned read count, ensuring statistical reliability of the analysis; modified read count, for precise quantification of editing event frequency; editing efficiency percentage, for a direct visual representation of editing efficiency. This high-precision quantitative analysis capability provides a clear understanding of the actual off-target effects of gene-editing tools and supplies reliable evidence for product safety evaluation.

Figure 3. Gene-editing efficiency statistics table

(2) Provision of a multi-dimensional editing event analysis table, including: single-event analysis — independent occurrence rates of Substitution (Sub), Insertion (Ins), and Deletion (Del); complex event statistics — proportions of complex editing events such as Ins+Del, Ins+Sub, and Del+Sub; and InDel comprehensive analysis. This refined classification analysis provides deep insight into gene-editing tool specificity.

Figure 4. Gene-editing classification statistics table

(3) Provision of single-nucleotide-resolution visualization analysis: precise alignment between reference sequence and edited sequence; clear marking of sgRNA binding sites and cleavage sites; direct visualization of editing types. This molecular-level precise analysis enables decision-makers to directly understand the specific changes at editing sites.

Figure 5. Editing product visualization

6. Service Content

* Service turnaround: standard workflow 20–30 business days.

7. Sample Requirements

* Notes: (1) All samples must meet the above standards to ensure the accuracy and reliability of detection results. (2) Clients may also submit tissue or cell pellet samples for DNA extraction; tissue requirement: >50 mg; cell pellet requirement: >1×10⁵ cells per site. (3) For special sample types, please contact the ZhuHai GeneRulor technical team in advance (Tel: 400-6309596; Order/Technical Support: service@generulor.com).

8. References

[1] International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH). (2005). ICH Harmonised Tripartite Guideline: Validation of Analytical Procedures: Text and Methodology Q2(R1) [current 4th edition].

[2] U.S. Food and Drug Administration. (May 2018). Bioanalytical Method Validation: Guidance for Industry. U.S. Department of Health and Human Services, FDA Center for Drug Evaluation and Research (CDER) and Center for Veterinary Medicine (CVM).

[3] FDA. Human Gene Therapy Products Incorporating Human Genome Editing – Guidance for Industry. 2024.

[4] Bennett EP, Petersen BL, Johansen IE, Niu Y, Yang Z, Chamberlain CA, Met Ö, Wandall HH, & Frødin M. (2020). INDEL detection, the 'Achilles heel' of precise genome editing: a survey of methods for accurate profiling of gene editing induced indels. Nucleic Acids Research, 48(21), 11958–11981.