A benchmarked, high-efficiency prime editing platform for multiplexed dropout screening
Year: 2024
Type: article
Abstract: Prime editing installs precise edits into the genome with minimal unwanted byproducts, but low and variable editing efficiencies have complicated application of the approach to high-throughput functional genomics. Here we assembled a prime editing platform capable of high-efficiency substitution editing suitable for functional interrogation of small genetic variants. We benchmarked this platform for pooled, loss-of-function screening using a library of ~240,000 engineered prime editing guide RNAs (epegRNAs) targeting ~17,000 codons with 1-3 bp substitutions. Comparing the abundance of these epegRNAs across screen samples identified negative selection phenotypes for 7,996 nonsense mutations targeted to 1,149 essential genes and for synonymous mutations that disrupted splice site motifs at 3' exon boundaries. Rigorous evaluation of codon-matched controls demonstrated that these phenotypes were highly specific to the intended edit. Altogether, we established a prime editing approach for multiplexed, functional characterization of genetic variants with simple readouts.
Source: Nature Methods
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $12,290
Funders: National Science Foundation, U.S. Department of Health and Human Services, Princeton University, Rutgers Cancer Institute of New Jersey, Searle Scholars Program, China Scholarship Council, National Institutes of Health, National Human Genome Research Institute, National Cancer Institute, National Institute of General Medical Sciences, Eunice Kennedy Shriver National Institute of Child Health and Human Development
Awards: G1052925518, G1648828865, Predoctoral Training in Genetics and Molecular Biology, Predicting and analyzing protein interaction networks, G2157381551, G2802527627, G3218012782, Graduate Research Fellowship Program (GRFP), CAREER Deciphering how enhancers encode tissue-specificity and phenotypes, G3670273158, G4999992106, G5052434461, G5725318212, Mapping the DNA damage response in human cells with high-resolution functional genomics, Quantitative and Computational Biology Graduate Program, G6687326147, G6757922907, G6801109133, G6855349143, Characterizing the interpretation and generation of Erk signaling dynamics using high-throughput genetics, G8441280437, G9000067977, G9000078355, G9000149275, G9000185925, G9000307403, Cancer Center Support Grant
OpenAlex ID: W4404497408