Folate metabolic profiling and expression of folate metabolism‐related genes during panicle development in foxtail millet (<scp><i>Setaria italica</i> (L.) P. Beauv</scp>)
Bibliographic record
Abstract
BACKGROUND: Foxtail millet grain has higher folate content than other cereal crops. However, the folate metabolite content and the expression patterns of folate metabolite-related genes are unknown. RESULTS: Liquid chromatography-mass spectrometry was used to investigate 12 folate metabolites in a foxtail millet panicle. The content of total folate and derivatives gradually decreased during panicle development. Polyglutamate 5-formyl-tetrahydrofolate was the major form. Twenty-eight genes involved in the folate metabolic pathway were identified through bioinformatic analysis. These genes in Setaria italica, S. viridis and Zea mays showed genomic collinearity. Phylogenetic analysis revealed that the folate-related genes were closely related among the C4 plants compared to C3 plants. The gene expressions were then studied at three panicle development stages. The gene expression patterns were classified into two groups, namely SiADCL1 and SiGGH as two key enzymes, which are responsible for folate synthesis and degradation; their expression levels were highest at the early panicle development stage, up to 179.11- and 163.88-fold, respectively. Their expression levels had a similar downward trend during panicle development and were significantly positively correlated with the concentration of total folate and folate derivatives. However, SiSHMT3 expression levels were significantly negatively correlated with total folate concentration. CONCLUSION: Besides being the major determinants of folate and folate derivatives accumulation, SiADCL1 and SiGGH expression levels are key limiting factors in the foxtail millet panicle. Therefore, SiADCL1 and SiGGH expression levels can be targeted in genetic modification studies to improve folate content in foxtail millet seeds in the future. © 2021 Society of Chemical Industry.
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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".