Dataset Information

Base editing sensor libraries for high-throughput engineering and functional analysis of cancer-associated single nucleotide variants.

ABSTRACT: Base editing can be applied to characterize single nucleotide variants of unknown function, yet defining effective combinations of single guide RNAs (sgRNAs) and base editors remains challenging. Here, we describe modular base-editing-activity 'sensors' that link sgRNAs and cognate target sites in cis and use them to systematically measure the editing efficiency and precision of thousands of sgRNAs paired with functionally distinct base editors. By quantifying sensor editing across >200,000 editor-sgRNA combinations, we provide a comprehensive resource of sgRNAs for introducing and interrogating cancer-associated single nucleotide variants in multiple model systems. We demonstrate that sensor-validated tools streamline production of in vivo cancer models and that integrating sensor modules in pooled sgRNA libraries can aid interpretation of high-throughput base editing screens. Using this approach, we identify several previously uncharacterized mutant TP53 alleles as drivers of cancer cell proliferation and in vivo tumor development. We anticipate that the framework described here will facilitate the functional interrogation of cancer variants in cell and animal models.

SUBMITTER: Sanchez-Rivera FJ

PROVIDER: S-EPMC9232935 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Base editing sensor libraries for high-throughput engineering and functional analysis of cancer-associated single nucleotide variants.

Sánchez-Rivera Francisco J FJ Diaz Bianca J BJ Kastenhuber Edward R ER Schmidt Henri H Katti Alyna A Kennedy Margaret M Tem Vincent V Ho Yu-Jui YJ Leibold Josef J Paffenholz Stella V SV Barriga Francisco M FM Chu Kevan K Goswami Sukanya S Wuest Alexandra N AN Simon Janelle M JM Tsanov Kaloyan M KM Chakravarty Debyani D Zhang Hongxin H Leslie Christina S CS Lowe Scott W SW Dow Lukas E LE

Nature biotechnology 20220214 6

Base editing can be applied to characterize single nucleotide variants of unknown function, yet defining effective combinations of single guide RNAs (sgRNAs) and base editors remains challenging. Here, we describe modular base-editing-activity 'sensors' that link sgRNAs and cognate target sites in cis and use them to systematically measure the editing efficiency and precision of thousands of sgRNAs paired with functionally distinct base editors. By quantifying sensor editing across >200,000 edit ...[more]

PMID: 35165384

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Dataset Information

Base editing sensor libraries for high-throughput engineering and functional analysis of cancer-associated single nucleotide variants.

Publications

Base editing sensor libraries for high-throughput engineering and functional analysis of cancer-associated single nucleotide variants.

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