Tying the knot: occurrence and possible significance of gene fusions in plant metabolism and beyond
Bibliographic record
Abstract
Gene fusions have recently attracted attention especially in the field of plant specialized metabolism. The occurrence of a gene fusion, in which originally separate gene products are combined into a single polypeptide, often corresponds to the functional association of individual components within a single metabolic pathway. Examples include gene fusions implicated in benzylisoquinoline alkaloid (BIA), terpenoid, and amino acid biosynthetic pathways, in which distinct domains within a fusion catalyze consecutive, yet independent reactions. Both genomic and transcriptional mechanisms result in the fusion of gene products, which can include partial or complete domain repeats and extensive domain shuffling as evident in the BIA biosynthetic enzyme norcoclaurine synthase. Artificial gene fusions are commonly deployed in attempts to engineer new or improved pathways in plants or microorganisms, based on the premise that fusions are advantageous. However, a survey of functionally characterized fusions in microbial systems shows that the functional impact of fused gene products is not straightforward. For example, whereas enzyme fusions might facilitate the metabolic channeling of unstable intermediates, this channeling can also occur between tightly associated independent enzymes. The frequent occurrence of both fused and unfused enzymes in plant and microbial metabolism adds additional complexity, in terms of both pathway functionality and evolution.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".