美国宾州州立大学的Howard M. Salis研究团队开发了自动化设计上千个非重复基因片段的技术，可用于建立稳定的遗传系统。 相关论文发表在2020年7月13日出版的《自然—生物技术》。

该课题组研究人员开发了“非重复片段计算器”，用于从特定设计约束位点（包括启动子，核糖体结合位点和终止子）快速生成上千个高度不重复基因片段。作为演示，课题组研究人员设计并实验表征了4350个非重复细菌启动子，其转录率在820,000倍的范围内变化，以及1722个高度非重复性酵母启动子，其转录率在25,000倍的范围内变化。

该课题组人员应用机器学习来解释特定的相互作用如何控制启动子的转录率。研究人员还展示了使用非重复基因片段可以大幅减少同源重组，从而有更好的遗传稳定性。

据悉，当基因部分包含重复序列时，改造基因系统容易失败。设计具有所需功能的许多非重复基因片段有很高计算复杂度，仍然是一个困难的挑战。

附：英文原文

: Automated design of thousands of nonrepetitive parts for engineering stable genetic systems

Author: Ayaan Hossain, Eriberto Lopez, Sean M. Halper, Daniel P. Cetnar, Alexander C. Reis, Devin Strickland, Eric Klavins, Howard M. Salis

Issue&Volume: 2020-07-13

Abstract: Engineered genetic systems are prone to failure when their genetic parts contain repetitive sequences. Designing many nonrepetitive genetic parts with desired functionalities remains a difficult challenge with high computational complexity. To overcome this challenge, we developed the Nonrepetitive Parts Calculator to rapidly generate thousands of highly nonrepetitive genetic parts from specified design constraints, including promoters, ribosome-binding sites and terminators. As a demonstration, we designed and experimentally characterized 4,350 nonrepetitive bacterial promoters with tran ion rates that varied across a 820,000-fold range, and 1,722 highly nonrepetitive yeast promoters with tran ion rates that varied across a 25,000-fold range. We applied machine learning to explain how specific interactions controlled the promoters’ tran ion rates. We also show that using nonrepetitive genetic parts substantially reduces homologous recombination, resulting in greater genetic stability.