Target Capture during Mos1 Transposition
Bibliographic record
Abstract
DNA transposition contributes to genomic plasticity. Target capture is a key step in the transposition process, because it contributes to the selection of new insertion sites. Nothing or little is known about how eukaryotic mariner DNA transposons trigger this step. In the case of Mos1, biochemistry and crystallography have deciphered several inverted terminal repeat-transposase complexes that are intermediates during transposition. However, the target capture complex is still unknown. Here, we show that the preintegration complex (i.e., the excised transposon) is the only complex able to capture a target DNA. Mos1 transposase does not support target commitment, which has been proposed to explain Mos1 random genomic integrations within host genomes. We demonstrate that the TA dinucleotide used as the target is crucial both to target recognition and in the chemistry of the strand transfer reaction. Bent DNA molecules are better targets for the capture when the target DNA is nicked two nucleotides apart from the TA. They improve strand transfer when the target DNA contains a mismatch near the TA dinucleotide.
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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 | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".