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 transcription rates that varied across a 820,000-fold range, and 1,722 highly nonrepetitive yeast promoters with transcription rates that varied across a 25,000-fold range. We applied machine learning to explain how specific interactions controlled the promoters’ transcription rates. We also show that using nonrepetitive genetic parts substantially reduces homologous recombination, resulting in greater genetic stability.
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All characterized genetic part sequences and measurements are provided in the Supplementary Information.
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This project was supported by funds from the Air Force Office of Scientific Research (grant no. FA9550-14-1-0089), the Defense Advanced Research Projects Agency (grant nos. FA8750-17-C-0254 and HR001117C0095), the Department of Energy (grant no. DE-SC0019090), and a Graduate Research Innovation award to A.H. from the Huck Institutes of the Life Sciences.
The authors declare no competing interests.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Existing genetic parts and their repetitiveness.
Toolboxes of nonrepetitive genetic parts.
Sequences and measurements for nonrepetitive bacterial and yeast promoters.
Model features for the nonrepetitive yeast promoters.
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Hossain, A., Lopez, E., Halper, S.M. et al. Automated design of thousands of nonrepetitive parts for engineering stable genetic systems. Nat Biotechnol 38, 1466–1475 (2020). https://doi.org/10.1038/s41587-020-0584-2
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