Genome-wide identification and transcriptional analysis of folate metabolism-related genes in maize kernels
Bibliographic record
Abstract
BACKGROUND: Maize is a major staple food crop globally and contains various concentrations of vitamins. Folates are essential water-soluble B-vitamins that play an important role as one-carbon (C1) donors and acceptors in organisms. To gain an understanding of folate metabolism in maize, we performed an intensive in silico analysis to screen for genes involved in folate metabolism using publicly available databases, followed by examination of the transcript expression patterns and profiling of the folate derivatives in the kernels of two maize inbred lines. RESULTS: A total of 36 candidate genes corresponding to 16 folate metabolism-related enzymes were identified. The maize genome contains all the enzymes required for folate and C1 metabolism, characterized by highly conserved functional domains across all the other species investigated. Phylogenetic analysis revealed that these enzymes in maize are conserved throughout evolution and have a high level of similarity with those in sorghum and millet. The LC-MS analyses of two maize inbred lines demonstrated that 5-methyltetrahydrofolate was the major form of folate derivative in young seeds, while 5-formyltetrahydrofolate in mature seeds. Most of the genes involved in folate and C1 metabolism exhibited similar transcriptional expression patterns between these two maize lines, with the highest transcript abundance detected on day after pollination (DAP) 6 and the decreased transcript abundance on DAP 12 and 18. Compared with the seeds on DAP 30, 5-methyltetrahydrofolate was decreased and 5-formyltetrahydrofolate was increased sharply in the mature dry seeds. CONCLUSIONS: The enzymes involved in folate and C1 metabolism are conserved between maize and other plant species. Folate and C1 metabolism is active in young developing maize seeds at transcriptional levels.
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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".