Transcriptomics and Genomics Analysis Uncover the Differentially Expressed Chlorophyll and Carotenoid-Related Genes in Celery
Bibliographic record
Abstract
Celery (Apium graveolens L.), a plant from Apiaceae, is one of the most important vegetables and is grown worldwide. Carotenoids can capture light energy and transfer it to chlorophyll, which plays a central role in photosynthesis. Here, by performing transcriptomics and genomics analysis, we identified and conducted a comprehensive analysis of chlorophyll and carotenoid-related genes in celery and six representative species. Significantly, different contents and gene expression patterns were found among three celery varieties. In total, 237 and 290 chlorophyll and carotenoid-related genes were identified in seven species. No notable gene expansion of chlorophyll biosynthesis was detected in examined species. However, the gene encoding ζ-carotene desaturase (ZDS) enzyme in carotenoid was expanded in celery. Comparative genomics and RNA-seq analyses revealed 16 and 5 key genes, respectively, regulating chlorophyll and carotenoid. An intriguing finding is that chlorophyll and carotenoid-related genes were coordinately regulated by transcriptional factors, which could be distinctively classified into positive- and negative-regulation groups. Six CONSTANS (CO)-like transcription factors co-regulated chlorophyll and carotenoid-related genes were identified in celery. In conclusion, this study provides new insights into the regulation of chlorophyll and carotenoid by transcription factors.
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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) | 0.001 | 0.000 |
| 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".