Prediction of efficiencies for diverse prime editing systems in multiple cell types.

Cell

Department of Pharmacology, Yonsei University College of Medicine, Seoul 03722, Republic of Korea; Graduate School of Medical Science, Brain Korea 21 Plus Project for Medical Sciences, Yonsei University College of Medicine, Seoul 03722, Republic of Korea; Yonsei University College of Medicine, Seoul 03722, Republic of Korea; Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul 03722, Republic of Korea; Center for Nanomedicine, Institute for Basic Science (IBS), Seoul 03722, Republic of Korea; Yonsei-IBS Institute, Yonsei University, Seoul 03722, Republic of Korea; Institute for Immunology and Immunological Diseases, Yonsei University College of Medicine, Seoul 03722, Republic of Korea; Department of Otolaryngology, University of California, San Francisco, San Francisco, CA 94115, USA. Electronic address:

Published: May 2023

Applications of prime editing are often limited due to insufficient efficiencies, and it can require substantial time and resources to determine the most efficient pegRNAs and prime editors (PEs) to generate a desired edit under various experimental conditions. Here, we evaluated prime editing efficiencies for a total of 338,996 pairs of pegRNAs including 3,979 epegRNAs and target sequences in an error-free manner. These datasets enabled a systematic determination of factors affecting prime editing efficiencies. Then, we developed computational models, named DeepPrime and DeepPrime-FT, that can predict prime editing efficiencies for eight prime editing systems in seven cell types for all possible types of editing of up to 3 base pairs. We also extensively profiled the prime editing efficiencies at mismatched targets and developed a computational model predicting editing efficiencies at such targets. These computational models, together with our improved knowledge about prime editing efficiency determinants, will greatly facilitate prime editing applications.

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http://dx.doi.org/10.1016/j.cell.2023.03.034DOI Listing

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