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Record W4405743554 · doi:10.1186/s12864-024-11108-1

Yield increment and transcriptome response caused by blue light treatment in Hericium coralloides

2024· article· en· W4405743554 on OpenAlexaff
Yan Zhu, Chuanwen Jia, Chao Wang, Shurui Zhang, Xue-Yan Yuan, H. J. Yang, Tom Hsiang, Qi Bao, Zhanwu Peng, Yu Li, Shuyan Liu

Bibliographic record

VenueBMC Genomics · 2024
Typearticle
Languageen
FieldMedicine
TopicFungal Biology and Applications
Canadian institutionsUniversity of Guelph
FundersJilin Agricultural University
KeywordsBiologyTranscriptomeBlue lightLight intensityBotanyGeneGene expressionGenetics

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.624
Threshold uncertainty score0.329

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.031
GPT teacher head0.276
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2024
Admission routes1
Has abstractyes

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