Prediction of base editor off-targets by deep learning.

Journal: Nature communications
PMID: 37660097

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.

Authors

  • Chengdong Zhang
    State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Hospital/Cancer Institute, Fudan University, Shanghai 200438, China.
  • Yuan Yang
    The Ministry of Education Key Laboratory of Contemporary Design and Integrated Manufacturing Technology, Northwestern Polytechnical University, No. 127, Youyi Road (West), Xi'an 710072, China.
  • Tao Qi
    Department of Laboratory Medicine, Nangfang Hospital, Southern Medical University, GuangDong, 510515, China.
  • Yuening Zhang
    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.
  • Linghui Hou
    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.
  • Jingjing Wei
    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.
  • Jingcheng Yang
    State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Hospital/Cancer Institute, Fudan University, Shanghai 200438, China.
  • Leming Shi
    State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Hospital/Cancer Institute, Fudan University, Shanghai 200438, China.
  • Sang-Ging Ong
    Department of Pharmacology and Regenerative Medicine, University of Illinois College of Medicine, Illinois, USA.
  • Hongyan Wang
    State Key Laboratory of Genetic Engineering, School of Life Sciences, Zhongshan Hospital, Fudan University, Shanghai, 200432, China.
  • Hui Wang
    Department of Vascular Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China.
  • Bo Yu
    Department of Cardiology, The 2nd Affiliated Hospital of Harbin Medical University, Harbin, China.
  • Yongming Wang
    State Key Laboratory of Genetic Engineering, School of Life Sciences, Zhongshan Hospital, Fudan University, Shanghai, 200432, China. ymw@fudan.edu.cn.

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