Digenome-seq Off-Target Detection for Programmable Nucleases
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Solution Overview
Problem
Current genome editing technologies using programmable nucleases, such as CRISPR/Cas9, face challenges in accurately targeting specific sites while minimizing off-target effects, which can lead to unintended mutations and genomic instability.
Innovation Solution
A method called Digenome-seq, involving the cleavage of genomic DNA with programmable nucleases followed by next-generation sequencing, is developed to detect and analyze off-target sites, allowing for the identification of specific on-target sites without off-target effects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If programmable nucleases are used for genome editing, then targeted genetic modifications can be achieved, but off-target cleavages cause unintended mutations and genomic instability
Solution Approach 1:
The patent replaces traditional mechanical/chemical detection methods with next-generation sequencing (NGS) technology to detect off-target sites. The NGS system enables comprehensive genomic scanning to identify cleavage sites that would otherwise be undetectable, providing a sophisticated approach to monitoring off-target effects at base-pair resolution across the entire genome.
Solution Approach 2:
The patent implements a feedback mechanism by detecting off-target sites through NGS and using this information to select and optimize guide RNAs. The detected off-target sites are fed back into the selection process to identify guide RNAs with the lowest off-target activity, creating an iterative optimization loop that improves target specificity.
2Adaptability or versatility
If programmable nucleases tolerate mismatches at nucleotide sequences, then binding flexibility is improved, but the number of potential off-target sites increases
Solution Approach 1:
The patent uses next-generation sequencing to replace traditional prediction methods for identifying off-target sites. NGS provides direct experimental evidence of actual cleavage events, allowing researchers to observe the real-world impact of mismatch tolerance and identify specific off-target sites that arise due to binding flexibility.
Solution Approach 2:
The patent creates a comprehensive map of off-target sites by sequencing the genome after nuclease treatment. This copying of the genomic sequence with cleavage markers provides a complete record of all potential off-target sites, enabling researchers to analyze and select guide RNAs based on actual off-target activity rather than theoretical predictions.
3Productivity
If off-target DNA cleavages are allowed, then genome editing efficiency is maintained, but mutations at unintended genes and gross genome recombination occur
Solution Approach 1:
The patent implements a feedback loop where off-target sites detected through NGS are used to select guide RNAs with the lowest off-target activity. This feedback mechanism allows the system to maintain high on-target editing efficiency while simultaneously improving genomic stability by eliminating guide RNAs that cause unwanted mutations and recombination events.
Solution Approach 2:
The patent replaces traditional efficacy assessment methods with comprehensive NGS-based off-target detection. This substitution allows for the simultaneous evaluation of both on-target editing efficiency and off-target genomic stability across the entire genome, providing a complete picture of nuclease performance that enables informed guide RNA selection.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Digenome-seq enables the detection of off-target sites with high reproducibility, enabling the production and study of programmable nucleases with high target specificity, thereby reducing the risk of unintended genomic alterations.
Implementation Method 1
cleaving an isolated genomic DNA with a target-specific programmable nuclease
Implementation Method 2
performing next generation sequencing of the cleaved DNA
Data Source
AI summary
The present disclosure relates to a method for detecting off-target sites of a programmable nuclease in a genome, and specifically, to a method for detecting off-target sites through data analysis by subjecting the genome isolated in vitro to programmable nucleases to cleave the genome and then performing whole genome sequencing or deep sequencing, and to a method for selecting on-target sites of a programmable nuclease, which minimizes the off-target effect, using this method. The Digenome-seq of the present disclosure can detect the off-target sites of a programmable nuclease on the genomic scale at a high degree of reproducibility, and thus can be used in the manufacture of programmable nucleases having high target specificity and the study thereof.