ArticleScientific reports2017
CRISPR-Cas9 cleavage efficiency correlates strongly with target-sgRNA folding stability: from physical mechanism to off-target assessment.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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Who cites it
39 citing papers in PubMed.
- Machine-learning in optimization of CRISPR technology.Machine learning. Health · 2026Review
- Mesoscopic Calculation of Single Mismatches in RNA/DNA Hybrids: Strong Hydrogen Bonds of dTrG Affect CRISPR Off-Target Binding.The journal of physical chemistry. B · 2026Article
- Whitening fruit by CRISPR/Cas9-mediated homoeolog-specific gene editing ofHorticulture research · 2026Article
- Off-target interactions in the CRISPR-Cas9 Machinery: mechanisms and outcomes.Biochemistry and biophysics reports · 2025Review
- High-fidelity Cas9-mediated targeting of KRAS driver mutations restrains lung cancer in preclinical models.Nature communications · 2025Article
- Insights into pegRNA design from editing of the cardiomyopathy-associated phospholamban R14del mutation.FEBS letters · 2025Article
- Article
- Rescue of the disease-associated phenotype in CRISPR-corrected hiPSCs as a therapeutic approach for inherited retinal dystrophies.Molecular therapy. Nucleic acids · 2025Article
- CRISPRlnc: a machine learning method for lncRNA-specific single-guide RNA design of CRISPR/Cas9 system.Briefings in bioinformatics · 2024Article
- Elevated expression of exogenous RAD51 enhances the CRISPR/Cas9-mediated genome editing efficiency.BMB reports · 2023Article
- Online Databases of Genome Editing in Cardiovascular and Metabolic Diseases.Advances in experimental medicine and biology · 2023Article
- Accounting for small variations in the tracrRNA sequence improves sgRNA activity predictions for CRISPR screening.Nature communications · 2022Article
- A Machine Learning Approach to Identify the Importance of Novel Features for CRISPR/Cas9 Activity Prediction.Biomolecules · 2022Article
- Machine learning in the estimation of CRISPR-Cas9 cleavage sites for plant system.Frontiers in genetics · 2022Article
- CoRe: a robustly benchmarked R package for identifying core-fitness genes in genome-wide pooled CRISPR-Cas9 screens.BMC genomics · 2021Article
- Engineering of the genome editing protein Cas9 to slide along DNA.Scientific reports · 2021Article
- Impact of CRISPR-Cas9-Based Genome Engineering in Farm Animals.Veterinary sciences · 2021Review
- Massively parallel kinetic profiling of natural and engineered CRISPR nucleases.Nature biotechnology · 2021Article
- Improved nearest-neighbor parameters for the stability of RNA/DNA hybrids under a physiological condition.Nucleic acids research · 2020Article
- Technologies and Computational Analysis Strategies for CRISPR Applications.Molecular cell · 2020Review
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
The CRISPR/Cas9 complex, a bacterial immune response system, has been widely adopted for RNA-guided genome editing and transcription regulation in applications such as targeted genome modification and site-directed mutagenesis. However, the physical basis for its target specificity is not fully understood. In this study, based on a statistical mechanical analysis for the whole ensemble of sgRNA-target complex conformations, we identify a strong correlation between Cas9 cleavage efficiency and the stability of the DNA-RNA (R-loop) complex structures, with a Pearson correlation coefficient ranging from 0.775 to 0.886 for the tested systems. The finding leads to quantitative insights into important experimental results, such as the greater Cas9 tolerance to single-base mismatches in PAM-distal region than to PAM-proximal region and the high specificity and efficiency for shorter protospacers. Moreover, the results from the genome-wide off-target assessments, compared with other off-target scoring tools, indicate that the statistical mechanics-based approach provides more reliable off-target analyses and sgRNA design. To facilitate the genome engineering applications, a new web-based tool for genome-wide off-target assessment is established.
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Registered trials
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