Transcriptomic analysis reveals anthocyanin biosynthesis regulation in blueberry (<i>Vaccinium ashei</i>) fruit
Bibliographic record
Abstract
Blueberry (Vaccinium ashei) is a popular fruit due to its high anthocyanin content. This study aimed to analyze the transcriptome profile of V. ashei cv. ‘Brightwell’ fruits at different stages of development. A total of 314.26 GB of clean data were obtained and de novo assembled into 254 196 unigenes. In comparisons between the early and late stages of fruit ripening, 27 genes (including PAL, CHS, F3H, F3′H, F3′5′H, LDOX, etc.) were found to cover the main steps in the anthocyanin biosynthesis pathway. Most of these genes were highly expressed in the late stage of fruit development, suggesting that anthocyanins mainly accumulate in the late stage. During the late stage of fruit development, most structural and regulatory genes such as F3′5′H and F3′H, which are involved in the anthocyanin biosynthetic pathway, were upregulated, causing the fruit to turn blue. Decreased expression of a large number of chloroplast-related genes during the fruit ripening period could explain why the green fruit color fades over time. Additionally, abscisic acid and ethylene may play positive roles in promoting fruit ripening and anthocyanin accumulation. This research reveals the transcriptomic characteristics of immature and mature fruits and enhances our understanding of the molecular mechanisms of anthocyanin biosynthesis and accumulation in blueberry fruit.
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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".