Transposon diversity in <i>Arabidopsis thaliana</i>
Bibliographic record
Abstract
Recent availability of extensive genome sequence information offers new opportunities to analyze genome organization, including transposon diversity and accumulation, at a level of resolution that was previously unattainable. In this report, we used sequence similarity search and analysis protocols to perform a fine-scale analysis of a large sample ( approximately 17.2 Mb) of the Arabidopsis thaliana (Columbia) genome for transposons. Consistent with previous studies, we report that the A. thaliana genome harbors diverse representatives of most known superfamilies of transposons. However, our survey reveals a higher density of transposons of which over one-fourth could be classified into a single novel transposon family designated as Basho, which appears unrelated to any previously known superfamily. We have also identified putative transposase-coding ORFs for miniature inverted-repeat transposable elements (MITEs), providing clues into the mechanism of mobility and origins of the most abundant transposons associated with plant genes. In addition, we provide evidence that most mined transposons have a clear distribution preference for A + T-rich sequences and show that structural variation for many mined transposons is partly due to interelement recombination. Taken together, these findings further underscore the complexity of transposons within the compact genome of A. thaliana.
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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 | 0.001 | 0.001 |
| 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".