High throughput PRIME editing screens identify functional DNA variants in the human genome
Open accessPreprint — published as 10.1016/j.molcel.2023.11.021 · Paper page
Abstract
Despite tremendous progress in detecting DNA variants associated with human disease, interpreting their functional impact in a high-throughput and base-pair resolution manner remains challenging. Here, we develop a novel pooled prime editing screen method, PRIME, which can be applied to characterize thousands of coding and non-coding variants in a single experiment with high reproducibility. To showcase its applications, we first identified essential nucleotides for a 716 bp MYC enhancer via PRIME-mediated saturation mutagenesis. Next, we applied PRIME to functionally characterize 1,304 non-coding variants associated with breast cancer and 3,699 variants from ClinVar. We discovered that 103 non-coding variants and 156 variants of uncertain significance are functional via affecting cell fitness. Collectively, we demonstrate PRIME capable of characterizing genetic variants at base-pair resolution and scale, advancing accurate genome annotation for disease risk prediction, diagnosis, and therapeutic target identification.
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Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764 · see citing works
Massively parallel assessment of human variants with base editor screens
Hanna, R. E., Hegde, M., Fagre, C. R., DeWeirdt, P. C., Sangree, A. K., Szegletes, Z., Griffith, A., Feeley, M. N., Sanson, K. R., Baidi, Y., et al. (2020) · doi:10.1101/2020.05.17.100818 · Cited by 314 · see citing works
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Recent advances in prime editing technologies and their promises for therapeutic applications
Zeng, H., Daniel, T. C., Lingineni, A., Chee, K., Talloo, K., & Gao, X. (2024) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2024.103071 · Cited by 27 · see citing works
- Authors
- Ren, X., Yang, H., Nierenberg, J. L., Sun, Y., Chen, J., Beaman, C., Pham, T., Nobuhara, M., Takagi, M. A., Narayan, V., Li, Y., Ziv, E., & Shen, Y.
- Affiliations
- University of California, San Francisco (US)
- University of North Carolina at Chapel Hill (US)
- Corresponding author
- Shen, Yin
- ORCID
- Venue
- Molecular Cell
- Publisher
- openRxiv
- Published
- 2023-07-12
- Volume
- 83
- Issue
- 24
- Pages
- 4633-4645.e9
- ISSN
- 1097-2765 (ISSN-L)
- PMC
- PMC10766087
- OpenAlex
- W4390063959
- Cited by
- 70
- References
- 2
- Citations by year
- 2026: 15 · 2025: 29 · 2024: 21 · 2023: 5
- FWCI
- 6.24
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- Locations
- Molecular Cell (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion, other-oa)
- eScholarship (California Digital Library) (submittedVersion, cc-by)
- PubMed Central (submittedVersion, cc-by-nc-nd)
- Funders
- National Institutes of Health (1s10od028511-01)
- University of California, San Francisco
- National Institute on Aging (R01AG057497)
- National Institute on Drug Abuse (U01DA052713)
- National Human Genome Research Institute (UM1HG009402, U01HG011720)
- National Eye Institute (R01EY027789)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › CRISPR and Genetic Engineering
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA regulation and disease
- Keywords
- prime editing, non-coding variants, variants of uncertain significance, breast cancer, ClinVar variants, cell fitness, single-base resolution, genome annotation, disease risk prediction
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