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 raise concerns in research and medical applications.
Innovation Solution
A method called Digenome-seq, involving the cleavage of isolated genomic DNA with target-specific programmable nucleases followed by next-generation sequencing, allows for the detection and analysis of off-target sites on a genomic scale, enabling the identification of specific on-target sites without off-target activity.
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 mutations occur at homologous sequences
Solution Approach 1:
The patent applies preliminary action by performing in vitro cleavage of genomic DNA with programmable nucleases before sequencing. This pre-cleavage step allows identification of potential off-target sites through Digenome-seq analysis, enabling researchers to select guide RNAs that minimize off-target effects before actual genome editing experiments are conducted.
Solution Approach 2:
The patent implements feedback by using Digenome-seq to generate data on nuclease cleavage patterns across the genome. This information feeds back into the guide RNA selection process, allowing iterative optimization of targeting specificity. The system continuously improves targeting precision by incorporating empirical off-target data into future experimental designs.
2Measurement precision
If whole genome sequencing is performed to detect off-target sites, then comprehensive detection capability is achieved, but analysis complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the complex whole genome sequencing data into manageable components. The Digenome-seq methodology segments the analysis into distinct steps: in vitro cleavage, adapter ligation, sequencing, and bioinformatic analysis of cleavage sites. This segmentation simplifies the overall process by breaking down the complex task of off-target detection into systematic, analyzable units.
Solution Approach 2:
The patent uses an intermediary approach by introducing artificial adapters with known sequences that ligate to the cleaved DNA ends. These adapters serve as mediators that facilitate the sequencing process and enable precise mapping of cleavage sites. The adapters act as intermediaries between the cleaved genomic DNA and the sequencing platform, simplifying data analysis.
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 effectively detects off-target sites with high reproducibility, facilitating the development of programmable nucleases that can specifically work at intended sites, thereby reducing the risk of unintended mutations and enhancing the precision of genome editing.
Implementation Method 1
cleaving genome by treating the genome (cell-free genomic DNA) isolated in vitro with programmable nucleases
Implementation Method 2
performing next generation sequencing, and determining a cleaved site in a sequence read obtained by the sequencing
Data Source
Figure 1a
Figure 1b
Figure 1c~1d
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.