摘要
Genome editing is a promising technique that has been broadly utilized for basic gene function studies and trait improvements.Simultaneously,the exponential growth of computational power and big data now promote the application of machine learning for biological research.In this regard,machine learning shows great potential in the refinement of genome editing systems and crop improvement.Here,we review the advances of machine learning to genome editing optimization,with emphasis placed on editing efficiency and specificity enhancement.Additionally,we demonstrate how machine learning bridges genome editing and crop breeding,by accurate key site detection and guide RNA design.Finally,we discuss the current challenges and prospects of these two techniques in crop improvement.By integrating advanced genome editing techniques with machine learning,progress in crop breeding will be further accelerated in the future.
出处
《aBIOTECH》
EI
CAS
CSCD
2024年第2期262-277,共16页
生物技术通报(英文版)
基金
supported by the National Natural Science Foundation of China(grant no.32270585)
Key R&D Program of Jiangsu Province(Modern Agriculture)(BE2022335)
the Project of Zhongshan Biological Breeding Laboratory(BM2022008-02)
the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD).