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

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. © 2023 Elsevier Inc.11Nsciescopu

Application of prime editing to the correction of mutations and phenotypes in adult mice with liver and eye diseases

© 2021, The Author(s), under exclusive licence to Springer Nature Limited.The use of prime editing—a gene-editing technique that induces small genetic changes without the need for donor DNA and without causing double strand breaks—to correct pathogenic mutations and phenotypes needs to be tested in animal models of human genetic diseases. Here we report the use of prime editors 2 and 3, delivered by hydrodynamic injection, in mice with the genetic liver disease hereditary tyrosinemia, and of prime editor 2, delivered by an adeno-associated virus vector, in mice with the genetic eye disease Leber congenital amaurosis. For each pathogenic mutation, we identified an optimal prime-editing guide RNA by using cells transduced with lentiviral libraries of guide-RNA-encoding sequences paired with the corresponding target sequences. The prime editors precisely corrected the disease-causing mutations and led to the amelioration of the disease phenotypes in the mice, without detectable off-target edits. Prime editing should be tested further in more animal models of genetic diseases.11Nsciescopu