High-throughput PRIME-editing screens identify functional DNA variants in the human genome.

disease variants enhancer high-throughput screens prime editing single-base resolution

Journal

Molecular cell
ISSN: 1097-4164
Titre abrégé: Mol Cell
Pays: United States
ID NLM: 9802571

Informations de publication

Date de publication:
21 Dec 2023
Historique:
received: 12 05 2023
revised: 07 10 2023
accepted: 16 11 2023
medline: 23 12 2023
pubmed: 23 12 2023
entrez: 22 12 2023
Statut: ppublish

Résumé

Despite tremendous progress in detecting DNA variants associated with human disease, interpreting their functional impact in a high-throughput and single-base resolution manner remains challenging. Here, we develop a pooled prime-editing screen method, PRIME, that 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 single-base resolution analysis. Next, we applied PRIME to functionally characterize 1,304 genome-wide association study (GWAS)-identified 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 that PRIME is capable of characterizing genetic variants at single-base resolution and scale, advancing accurate genome annotation for disease risk prediction, diagnosis, and therapeutic target identification.

Identifiants

DOI: 10.1016/j.molcel.2023.11.021 PMID: 38134886
pubmed: 38134886
pii: S1097-2765(23)00966-8
doi: 10.1016/j.molcel.2023.11.021
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

4633-4645.e9

Informations de copyright

Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of interests X.R., H.Y., and Yin Shen have filed a patent application related to pooled prime-editing screens.

Auteurs

Xingjie Ren (X)

Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA.

Han Yang (H)

Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA.

Jovia L Nierenberg (JL)

Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA.

Yifan Sun (Y)

Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA.

Jiawen Chen (J)

Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.

Cooper Beaman (C)

Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA.

Thu Pham (T)

Pharmaceutical Sciences and Pharmacogenomics Graduate Program, University of California, San Francisco, San Francisco, CA, USA.

Mai Nobuhara (M)

Pharmaceutical Sciences and Pharmacogenomics Graduate Program, University of California, San Francisco, San Francisco, CA, USA.

Maya Asami Takagi (MA)

Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA.

Vivek Narayan (V)

Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA.

Yun Li (Y)

Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Genetics, University of North Carolina, Chapel Hill, NC, USA; Department of Computer Science, University of North Carolina, Chapel Hill, NC, USA.

Elad Ziv (E)

Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA; Division of General Internal Medicine, Department of Medicine, and Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA.

Yin Shen (Y)

Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA; Department of Neurology, University of California, San Francisco, San Francisco, CA, USA; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA. Electronic address: yin.shen@ucsf.edu.

Classifications MeSH