Prediction of base editor off-targets by deep learning

Chengdong Zhang, Yuan Yang, Tao Qi, Yuening Zhang, Linghui Hou, Jingjing Wei, Jingcheng Yang, Leming Shi, Sang-Ging Ong, Hongyan Wang, Hui Wang (), Bo Yu () and Yongming Wang ()
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Chengdong Zhang: Fudan University Pudong Medical Center; State Key Laboratory of Genetic Engineering, School of Life Sciences, Zhongshan Hospital, Fudan University
Yuan Yang: Fudan University Pudong Medical Center; State Key Laboratory of Genetic Engineering, School of Life Sciences, Zhongshan Hospital, Fudan University
Tao Qi: Fudan University Pudong Medical Center; State Key Laboratory of Genetic Engineering, School of Life Sciences, Zhongshan Hospital, Fudan University
Yuening Zhang: School of Life Sciences and Biotechnology) Shanghai Jiao Tong University
Linghui Hou: Fudan University Pudong Medical Center; State Key Laboratory of Genetic Engineering, School of Life Sciences, Zhongshan Hospital, Fudan University
Jingjing Wei: Fudan University Pudong Medical Center; State Key Laboratory of Genetic Engineering, School of Life Sciences, Zhongshan Hospital, Fudan University
Jingcheng Yang: Fudan University Pudong Medical Center; State Key Laboratory of Genetic Engineering, School of Life Sciences, Zhongshan Hospital, Fudan University
Leming Shi: Fudan University Pudong Medical Center; State Key Laboratory of Genetic Engineering, School of Life Sciences, Zhongshan Hospital, Fudan University
Sang-Ging Ong: University of Illinois College of Medicine
Hongyan Wang: Fudan University Pudong Medical Center; State Key Laboratory of Genetic Engineering, School of Life Sciences, Zhongshan Hospital, Fudan University
Hui Wang: Shanghai Jiao Tong University School of Medicine
Bo Yu: Fudan University Pudong Medical Center; State Key Laboratory of Genetic Engineering, School of Life Sciences, Zhongshan Hospital, Fudan University
Yongming Wang: Fudan University Pudong Medical Center; State Key Laboratory of Genetic Engineering, School of Life Sciences, Zhongshan Hospital, Fudan University

Nature Communications, 2023, vol. 14, issue 1, 1-11

Abstract: Abstract Due to the tolerance of mismatches between gRNA and targeting sequence, base editors frequently induce unwanted Cas9-dependent off-target mutations. Here, to develop models to predict such off-targets, we design gRNA-off- target pairs for adenine base editors (ABEs) and cytosine base editors (CBEs) and stably integrate them into the human cells. After five days of editing, we obtain valid efficiency datasets of 54,663 and 55,727 off-targets for ABEs and CBEs, respectively. We use the datasets to train deep learning models, resulting in ABEdeepoff and CBEdeepoff, which can predict off-target sites. We use these tools to predict off-targets for a panel of endogenous loci and achieve Spearman correlation values varying from 0.710 to 0.859. Finally, we develop an integrated tool that is freely accessible via an online web server http://www.deephf.com/#/bedeep/bedeepoff . These tools could facilitate minimizing the off-target effects of base editing.

Date: 2023
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DOI: 10.1038/s41467-023-41004-3

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