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; Yongming Wang

doi:10.1038/s41467-023-41004-3

Prediction of base editor off-targets by deep learning

Nat Commun. 2023 Sep 2;14(1):5358. doi: 10.1038/s41467-023-41004-3.

Authors

Chengdong Zhang^#^{1

2

3}, Yuan Yang^#^{1

2}, Tao Qi¹, Yuening Zhang⁴, Linghui Hou¹, Jingjing Wei¹, Jingcheng Yang¹, Leming Shi¹, Sang-Ging Ong^{5

6}, Hongyan Wang¹, Hui Wang⁷, Bo Yu⁸, Yongming Wang^{9

10

11}

Affiliations

¹ Center for Medical Research and Innovation, Shanghai Pudong Hospital, Fudan University Pudong Medical Center; State Key Laboratory of Genetic Engineering, School of Life Sciences, Zhongshan Hospital, Fudan University, Shanghai, 200438, China.
² State Key Laboratory of Oncogenes and Related Genes, Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, 200025, Shanghai, China.
³ Department of Clinical Oncology, Taihe Hospital, Hubei University of Medicine, Shiyan, China.
⁴ SJTU-Yale Joint Center for Biostatistics and Data Science, (Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology) Shanghai Jiao Tong University, Shanghai, 200240, China.
⁵ Department of Pharmacology and Regenerative Medicine, University of Illinois College of Medicine, Illinois, USA.
⁶ Division of Cardiology, Department of Medicine, University of Illinois College of Medicine, Illinois, USA.
⁷ State Key Laboratory of Oncogenes and Related Genes, Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, 200025, Shanghai, China. huiwang@sibs.ac.cn.
⁸ Center for Medical Research and Innovation, Shanghai Pudong Hospital, Fudan University Pudong Medical Center; State Key Laboratory of Genetic Engineering, School of Life Sciences, Zhongshan Hospital, Fudan University, Shanghai, 200438, China. paul.yubo@gmail.com.
⁹ Center for Medical Research and Innovation, Shanghai Pudong Hospital, Fudan University Pudong Medical Center; State Key Laboratory of Genetic Engineering, School of Life Sciences, Zhongshan Hospital, Fudan University, Shanghai, 200438, China. ymw@fudan.edu.cn.
¹⁰ Department of Cardiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China. ymw@fudan.edu.cn.
¹¹ Shanghai Engineering Research Center of Industrial Microorganisms, Shanghai, China. ymw@fudan.edu.cn.

^# Contributed equally.

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.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Adenine
Cytosine
Deep Learning*
Gene Editing*

Substances

Adenine
Cytosine