Genome-wide identification of genes involved in raffinose metabolism in Maize
Bibliographic record
Abstract
The raffinose family oligosaccharides (RFOs), such as raffinose and stachyose, are synthesized by a set of distinct galactosyltransferases, which sequentially add galactose units to sucrose. The accumulation of RFOs in plant cells are closely associated with the responses to environmental factors, such as cold, heat and drought stresses. Systematic analysis of genes involved in the raffinose metabolism has not been reported to date. Searching the recently available working draft of the maize genome, six kinds of enzyme genes were speculated, which should encode all the enzymes involved in the raffinose metabolism in maize. Expression patterns of some related putative genes were analyzed. The conserved domains and phylogenetic relationships among the deduced maize proteins and their homologs isolated from other plant species were revealed. It was discovered that some of the key enzymes, such as galactinol synthase (ZmGolS5, ZmGolS45 and ZmGolS37), raffinose synthase (ZmRS1, ZmRS2, ZmRS3 and ZmRS10), stachyose synthase (ZmRS8) and β-fructofuranosidase, are encoded by multiple gene members with different expression patterns. These results reveal the complexity of the raffinose metabolism and the existence of metabolic channels for diverse RFOs in maize and provide useful information for improving maize stress tolerance through genetic engineering.
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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 | 0.001 |
| 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".