Integrating machine learning and genome editing for crop improvement

IF 4.6 4区 农林科学 Q1 BIOTECHNOLOGY & APPLIED MICROBIOLOGY
Long Chen, Guanqing Liu, Tao Zhang
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引用次数: 0

Abstract

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.

将机器学习与基因组编辑相结合,促进作物改良
基因组编辑是一项前景广阔的技术,已被广泛用于基础基因功能研究和性状改良。与此同时,计算能力和大数据的指数级增长促进了机器学习在生物学研究中的应用。在这方面,机器学习在完善基因组编辑系统和作物改良方面显示出巨大潜力。在此,我们回顾了机器学习在基因组编辑优化方面的进展,重点是编辑效率和特异性的提高。此外,我们还展示了机器学习如何通过精确的关键位点检测和导向 RNA 设计,在基因组编辑和作物育种之间架起桥梁。最后,我们讨论了这两种技术在作物改良中目前面临的挑战和前景。通过将先进的基因组编辑技术与机器学习相结合,未来将进一步加快作物育种的进展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
7.70
自引率
2.80%
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0
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