Design of Synthetic Mammalian Promoters Using Highly Palindromic Subsequences
Bibliographic record
Abstract
To express transgenes in specific cell types and states, promoters for endogenous genes are commonly created by truncating the sequence upstream of the transcriptional start site until the promoter is no longer functional. In this paper, we developed a method to design shorter synthetic mammalian promoters for endogenous genes by concatenating only its highly palindromic subsequences with a minimal core promoter. After developing metrics for palindromic density, analysis across all the human and mouse promoters showed higher palindromic density than expected by random. As experimental demonstrations, we applied the method to the CMV promoter (reduced to 432 nucleotides) and the mouse synapsin-1 promoter (383 nucleotides) to express fluorescent protein as reporters. Remarkably, the highly palindromic subsequences of these synthetic promoters contained sites important for strong constitutive expression and neuron-specific expression. As a resource to the community, we created enhancer sequences for all the human and mouse promoters.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".