Evolution and diversification of the momilactone biosynthetic gene cluster in the genus <i>Oryza</i>
Bibliographic record
Abstract
ABSTRACT Plants are master chemists and collectively are able to produce hundreds of thousands of different organic compounds. The genes underlying the biosynthesis of many specialized metabolites are organized in biosynthetic gene clusters (BGCs), which is hypothesized to ensure their faithful co-inheritance and to facilitate their coordinated expression. In rice, momilactones are diterpenoids that act in plant defence and various organismic interactions. Many of the genes essential for momilactone biosynthesis are grouped in a BGC. Here, we apply comparative genomics of diploid and allotetraploid Oryza species to reconstruct the species-specific architecture, evolutionary trajectory, and sub-functionalisation of the momilactone biosynthetic gene cluster (MBGC) in the Oryza genus. Our data show that the evolution of the MBGC is marked by lineage-specific rearrangements and gene copy number variation, as well as by occasional cluster loss. We identified a distinct cluster architecture in O. coarctata , which represents the first instance of an alternative architecture of the MBGC in Oryza and strengthens the idea of a common origin of the cluster in Oryza and the distantly related genus Echinochloa . Our research illustrates the evolutionary and functional dynamics of a biosynthetic gene cluster within a plant genus.
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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) | 0.000 | 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 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".