<i>GOLD HULL AND INTERNODE2</i> Encodes a Primarily Multifunctional Cinnamyl-Alcohol Dehydrogenase in Rice
Bibliographic record
Abstract
Lignin content and composition are two important agronomic traits for the utilization of agricultural residues. Rice (Oryza sativa) gold hull and internode phenotype is a classical morphological marker trait that has long been applied to breeding and genetics study. In this study, we have cloned the GOLD HULL AND INTERNODE2 (GH2) gene in rice using a map-based cloning approach. The result shows that the gh2 mutant is a lignin-deficient mutant, and GH2 encodes a cinnamyl-alcohol dehydrogenase (CAD). Consistent with this finding, extracts from roots, internodes, hulls, and panicles of the gh2 plants exhibited drastically reduced CAD activity and undetectable sinapyl alcohol dehydrogenase activity. When expressed in Escherichia coli, purified recombinant GH2 was found to exhibit strong catalytic ability toward coniferaldehyde and sinapaldehyde, while the mutant protein gh2 completely lost the corresponding CAD and sinapyl alcohol dehydrogenase activities. Further phenotypic analysis of the gh2 mutant plants revealed that the p-hydroxyphenyl, guaiacyl, and sinapyl monomers were reduced in almost the same ratio compared to the wild type. Our results suggest GH2 acts as a primarily multifunctional CAD to synthesize coniferyl and sinapyl alcohol precursors in rice lignin biosynthesis.
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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".