The Significance Of
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Understanding the CRISPR performance in various cellular environments is crucial to enhancing its application in biological studies and therapies. Empowered by the high throughput gRNA-target paired library, we comprehensively depicted the on-target editing efficiency, off-target editing specificity, and DSB repairing profiles of 929,180 gRNAs across two human cell lines (K562 and Jurkat), covering all protein-coding genes and 17,177 non-coding genes. Based on this high-quality and largest-ever gRNA-target pair dataset and machine learning algorithms, we developed corresponding computational models that outperformed current stategies, namely AIdit_ON for on-target prediction, AIdit_OFF for off-target prediction and AIdit_DSB for prediction of SpCas9-induced DSB repair outcomes. Together, this study will provide basic research and gene therapy support for more effective and accurate applications of CRISPR/Cas9.