Part:BBa_K5102065:Design
5' synthetic UTR
- 10COMPATIBLE WITH RFC[10]
- 12COMPATIBLE WITH RFC[12]
- 21COMPATIBLE WITH RFC[21]
- 23COMPATIBLE WITH RFC[23]
- 25COMPATIBLE WITH RFC[25]
- 1000COMPATIBLE WITH RFC[1000]
Design Notes
The synthetic UTR was designed utilizing the deep learning model developed by Castillo-Hair et al., which optimizes 5’ UTRs for efficient mRNA translation using generative neural networks and gradient descent (refer to the model wiki for more details). This model was trained on polysome profiling data from randomized 5’ UTR libraries across multiple cell types, allowing it to learn sequence features that enhance translation efficiency. The model was validated by calculation of the mean ribosome load (MRL) and minimum free energy (MFE) for each designed UTR.
Source
The part has been ordered as an oligo from a DNA synthesis provider.
References
Castillo-Hair, S. et al. Optimizing 5’UTRs for mRNA-delivered gene editing using deep learning. Nat Commun 15, 5284 (2024).