Controlled Growth of DNA Structures From Repeating Units Using the Vernier Mechanism
Bibliographic record
Abstract
In this report, we demonstrate the assembly of length-programmed DNA nanostructures using a single 16 base sequence and its complement as building blocks. To achieve this, we applied the Vernier mechanism to DNA assembly, which uses a mismatch in length between two monomers to dictate the final length of the product. Specifically, this approach relies on the interaction of two DNA strands containing a different number (n, m) of complementary binding sites: these two strands will keep binding to each other until they come into register, thus generating a larger assembly whose length (n × m) is encoded by the number of binding sites in each strand. While the Vernier mechanism has been applied to other areas of supramolecular chemistry, here we present an application of its principles to DNA nanostructures. Using a single 16 base repeat and its complement, and varying the number of repeats on a given DNA strand, we show the consistent construction of duplexes up to 228 base pairs (bp) in length. Employing specific annealing protocols, strand capping, and intercalator chaperones allows us to further grow the duplex to 392 base pairs. We demonstrate that the Vernier method is not only strand-efficient, but also produces a cleaner, higher-yielding product than conventional designs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".