Epigenomic Insight of Lingonberry: Health Promoting Trait Under Micropropagation
Bibliographic record
Abstract
Abstract Epigenetic variation plays a role in developmental gene regulation and responses to the environment. An efficient interaction of zeatin induced cytosine methylation and secondary compounds has been displayed for the first time in tissue-culture shoots of lingonberry (Vaccinium vitis-idaea) in vitro, in vivo and its cutting-cultivar Erntedank. Through MSAP assay, we observed highest methylated sites in leaf regenerants (LC1) from all primer combinations (108 bands), with their highest variation in secondary metabolites. We measured that four tissue-culture plants showed higher methylation bands than cutting propagated donor plants (ED) which exhibited 79 bands of methylation, which is comparatively low. On the other hand, we observed the highest total phenolic content in node culture-derived greenhouse grown plants, NC3 but leaf culture-derived greenhouse grown plants, LC1 represented low phenolic content. Our study showed more methylation in micropropagated plants (NC1, NC2, NC3, LC1) than those derived from cutting propagated ED plants, where methylation was not present. On the contrary, we observed higher secondary metabolites in ED plants but comparatively less in micropropagated shoots (NC1, NC2) and plants (NC3, LC1). Our study displayed that higher methylation sites observed in micropropagated plants possessed less amount of secondary metabolites.
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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) | 0.002 | 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".