Yield increment and transcriptome response caused by blue light treatment in Hericium coralloides
Bibliographic record
Abstract
BACKGROUND: Hericium coralloides is a traditional edible and medicinal mushroom. Light is a key factor in forming fruiting bodies of fungi; however, the effects of different light on the yield and morphogenesis of H. coralloides are still unknown. Therefore, the morphology, yield, and transcriptome of H. coralloides under blue, red, and white light conditions were investigated. RESULT: Fruiting bodies under blue light exhibited superior morphological traits, such as milky white color, larger size, elongated stalks, and higher spine count, leading to higher yields. Different light treatments led to dramatic transcriptome changes ranging from 10,827 differentially expressed genes (DEGs) induced by blue light in Blue-4d to 11,375 DEGs induced by red light in Red-4d and accounted for 64.56% to 67.81% of all expressed genes. This massive amount of light-responsive genes has never been reported in fungi. Gene Ontology analysis showed that light affected nearly all aspects of life in H. coralloides; suggesting that the influence of light on fungi may have been underestimated. Blue light-induced yield increment may be achieved by specifically upregulating the growth-related processes such as DNA replication, chromosomes, and cell division. CONCLUSIONS: This study offers preliminary insights into the potential role of blue light in modulating gene expression and yield stimulation in H. coralloides, potentially improving cultivation practice.
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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 | 0.000 | 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".