ExsgRNA: reduce off-target efficiency by on-target mismatched sgRNA

Author:

Hu Wei-Xin1,Rong Yu1,Guo Yan1,Jiang Feng1,Tian Wen1,Chen Hao1,Dong Shan-Shan12,Yang Tie-Lin1ORCID

Affiliation:

1. Biomedical Informatics & Genomics Center, Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi’an Jiaotong University , Xi’an 710049, P.R. China

2. Research Institute of Xi’an Jiaotong University , Zhejiang, China

Abstract

Abstract Clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 gene editing technology has been widely used to facilitate efficient genome editing. Current popular sgRNA design tools only consider the sgRNA perfectly matched to the target site and provide the results without any on-target mismatch. We suppose taking on-target gRNA-DNA mismatches into consideration might provide better sgRNA with similar binding activity and reduced off-target sites. Here, we trained a seq2seq-attention model with feedback-loop architecture, to automatically generate sgRNAs with on-target mismatches. Dual-luciferase reporter experiment showed that multiple sgRNAs with three mismatches could achieve the 80% of the relative activity of the perfect matched sgRNA. Meanwhile, it could reduce the number of off-target sites using sgRNAs with on-target mismatches. Finally, we provided a freely accessible web server sgRNA design tool named ExsgRNA. Users could submit their target sequence to this server and get optimal sgRNAs with less off-targets and similar on-target activity compared with the perfect-matched sgRNA.

Funder

National Natural Science Foundation of China

Natural Science Basic Research Program of Shaanxi Province

Innovation Capability Support Program of Shaanxi Province

China Postdoctoral Science Foundation

Natural Science Foundation of Zhejiang Province

Fundamental Research Funds for the Central Universities

High-Performance Computing Platform and Instrument Analysis Center

Publisher

Oxford University Press (OUP)

Subject

Molecular Biology,Information Systems

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