Tuned for Transposition: Molecular Determinants Underlying the Hyperactivity of a <i>Stowaway</i> MITE
Bibliographic record
Abstract
Miniature inverted repeat transposable elements (MITEs) are widespread in eukaryotic genomes, where they can attain high copy numbers despite a lack of coding capacity. However, little is known about how they originate and amplify. We performed a genome-wide screen of functional interactions between Stowaway MITEs and potential transposases in the rice genome and identified a transpositionally active MITE that possesses key properties that enhance transposition. Although not directly related to its autonomous element, the MITE has less affinity for the transposase than does the autonomous element but lacks a motif repressing transposition in the autonomous element. The MITE contains internal sequences that enhance transposition. These findings suggest that MITEs achieve high transposition activity by scavenging transposases encoded by distantly related and self-restrained autonomous elements.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".