ArticleNature biotechnology2021
Predicting the efficiency of prime editing guide RNAs in human cells.
Article in Nature biotechnology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 174 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
174 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- From RNA design to delivery: Computational strategies for functional RNA therapeutics.Bioactive materials · 2027Review
- Gene editing of hematopoietic stem cells: applications and advances.International journal of hematology · 2026Review
- Advances in prime editing: Molecular innovations, Large-fragment engineering, and AI-driven design.Biodesign research · 2026Review
- Mechanistic machine learning for prediction of prime editing outcomes.Nature biotechnology · 2026Article
- Prime Editing Mediated Generation and Correction of the mdx5cv Mutation Restores Dystrophin Expression in Myoblasts.International journal of molecular sciences · 2026Article
- A highly penetrantbioRxiv : the preprint server for biology · 2026Article
- The use of artificial intelligence in advancing molecular biology in Africa: a narrative review.Molecular genetics and genomics : MGG · 2026Review
- Efficient in vivo cytosine base editing using virus-like particles with uracil DNA glycosylase inhibition.Nature biotechnology · 2026Article
- Protocol for generating multiplexed prime-edited monoclonal cell lines in porcine fetal fibroblasts.STAR protocols · 2026Article
- Lineage tracing from cellular heritage to disease destiny.Nature genetics · 2026Review
- High-throughput evaluation of in vitro CRISPR activities enables optimized large-scale multiplex enrichment of rare variants.Nature biomedical engineering · 2026Article
- Adapting prime editing with split prime editors in Escherichia coli and its application to Staphylococcus aureus genome editing.Applied microbiology and biotechnology · 2026Article
- A primer on prime: A prime editing update from advances to first-in-human trial.Molecular therapy : the journal of the American Society of Gene Therapy · 2026Review
- Harnessing Deep Learning Models for Guide RNA Optimization and Off-Target Prediction in CRISPR Systems.Biotechnology journal · 2026Review
- Prime Editing, CRISPR-Cas9, and NanoCas Genome Editing for Cancer Treatment.Molecular biotechnology · 2026Review
- Prime editing updates: technological evolution, methodological expansion, and delivery strategies for in vivo applications.BMB reports · 2026Review
- CRISPR Screening in Hepatocellular Carcinoma: From Tumor Progression to Immune Evasion and Therapeutic Resistance.International journal of molecular sciences · 2026Review
- Prime editor-based high-throughput screening reveals functional synonymous mutations in human cells.Nature biotechnology · 2026Article
- Disrupting pegRNA intramolecular complementarity via PBS and spacer sequence alterations can enhance prime editing efficiency.Nucleic acids research · 2026Article
114 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Prime 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.
Indexed as
Identifiers
32958957What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.