6 research outputs found
Prediction of efficiencies for diverse prime editing systems in multiple cell types
No full textApplications 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.restrictio
Predicting the efficiency of prime editing guide RNAs in human cells
No full textPrime editing enables the introduction of virtually any small-sized genetic change without requiring donor DNA or double-strand breaks. However, evaluation of prime editing efficiency requires time-consuming experiments, and the factors that affect efficiency have not been extensively investigated. In this study, we performed high-throughput evaluation of prime editor 2 (PE2) activities in human cells using 54,836 pairs of prime editing guide RNAs (pegRNAs) and their target sequences. The resulting data sets allowed us to identify factors affecting PE2 efficiency and to develop three computational models to predict pegRNA efficiency. For a given target sequence, the computational models predict efficiencies of pegRNAs with different lengths of primer binding sites and reverse transcriptase templates for edits of various types and positions. Testing the accuracy of the predictions using test data sets that were not used for training, we found Spearman's correlations between 0.47 and 0.81. Our computational models and information about factors affecting PE2 efficiency will facilitate practical application of prime editing.restrictio
Application of prime editing to the correction of mutations and phenotypes in adult mice with liver and eye diseases
No full text© 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
Source Code for SynDesign
No full textMain source code for SynDesign, in press for Web Server publication on Nucleic Acid Research 2024.Instructions for installation and usage can be found on the Support page of the SynDesign page, https://deepcrispr.info/SynDesign/page/help_webSynDesign: Web-based prime editing guide RNA design and evaluation tool for saturation genome editing.</p
Prediction of efficiencies for diverse prime editing systems in multiple cell types
No full textApplications 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
No full textThe 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.restrictio
