ArticleNature biotechnology2025
High-throughput evaluation of genetic variants with prime editing sensor libraries.
Article in Nature biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
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Who cites it
40 citing papers in PubMed.
- Article
- Deciphering protein mutation-phenotype linkages from CRISPR-based tiling mutagenesis screens.Cell systems · 2026Article
- Compound delivery of eVLPs enhances prime editing for targeted genome engineering and high-throughput screening.Cell genomics · 2026Article
- Mechanistic machine learning for prediction of prime editing outcomes.Nature biotechnology · 2026Article
- eVLP compound delivery breaks the prime editing efficiency ceiling.Cell genomics · 2026Article
- Combining multiplexed functional data to improve variant classification.Genome medicine · 2026Article
- Uncovering functional variants using a high-efficiency PE3-based screening platform.Science advances · 2026Article
- Advances in multiplex precision genome editing in eukaryotic and prokaryotic systems.Current opinion in biotechnology · 2026Review
- AI-guided redesign of laboratory-evolved reverse transcriptases enhances prime editing.Nature biotechnology · 2026Article
- A multiplex, prime editing framework for identifying drug resistance variants at scale.Cell genomics · 2026Article
- Systematic pegRNA design with PRIDICT2.0 and ePRIDICT for efficient prime editing.Nature protocols · 2026Review
- A SLiM view of the human proteome.Nature structural & molecular biology · 2026Article
- Mechanistic machine learning enables interpretable and generalizable prediction of prime editing outcomes.bioRxiv : the preprint server for biology · 2026Article
- Prime Editing Driven Functional Genomics: Bridging Genotype to Phenotype in the Post-Genomic Era.International journal of molecular sciences · 2026Review
- Computational prediction of human genetic variants in the mouse genome.Nature biotechnology · 2025Article
- LDLR variant classification through activity-normalized prime editing screening.bioRxiv : the preprint server for biology · 2025Article
- Endogenous fine-mapping and prioritization of functional regulatory elements in complex genetic loci.Cell genomics · 2025Article
- A functional map of CDK-drug interactions at single amino acid resolution.bioRxiv : the preprint server for biology · 2025Article
- Fueling chromosomal gene diversification and artificial evolution with CRISPR.Genome biology · 2025Review
- Cloning and functional analysis of the TERE1 gene using the Gal4-UaS system in S2 cells: A streamlined approach for human gene functional genomics.Journal, genetic engineering & biotechnology · 2025Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Tumor genomes often harbor a complex spectrum of single nucleotide alterations and chromosomal rearrangements that can perturb protein function. Prime editing has been applied to install and evaluate genetic variants, but previous approaches have been limited by the variable efficiency of prime editing guide RNAs. Here we present a high-throughput prime editing sensor strategy that couples prime editing guide RNAs with synthetic versions of their cognate target sites to quantitatively assess the functional impact of endogenous genetic variants. We screen over 1,000 endogenous cancer-associated variants of TP53-the most frequently mutated gene in cancer-to identify alleles that impact p53 function in mechanistically diverse ways. We find that certain endogenous TP53 variants, particularly those in the p53 oligomerization domain, display opposite phenotypes in exogenous overexpression systems. Our results emphasize the physiological importance of gene dosage in shaping native protein stoichiometry and protein-protein interactions, and establish a framework for studying genetic variants in their endogenous sequence context at scale.
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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.