Comparative transcriptome analysis reveals relationship of three major domesticated varieties of Auricularia auricula-judae
Bibliographic record
Abstract
Auricularia auricula-judae is an edible mushroom and a traditional medicine in China as well as the fourth largest cultivated mushroom species in the world. Here for the first time, we present comparative transcriptome analyses of the fruiting bodies of three morphologically distinguishable A. auricula-judae cultivated varieties (Wujin, smooth; Banjin, partially wrinkled; and Quanjin, fully wrinkled) collected from Jilin Province, China. Biological triplicates were performed to determine the expression levels of 13,937 unigenes. Among them, only 13 unigenes were annotated to A. auricula-judae, highlighting the lack of publicly available reference sequences for this economically important species. Principal component analysis (PCA) determined that the gene expression profile of Quanjin was unique when compared to those of Banjin and Wujin. Such relationships were further supported by analyses of annotated and unannotated unigenes, differentially expressed unigenes, gene ontology functions, and the family of peroxidase genes. Using the KEGG database, significant alternations in biological pathways were detected among the three cultivars. This work contributes a large set of A. auricula-judae sequences to public database, establishes the relationships among major cultivars, and provides molecular guidance for breeding and cultivation.
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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 | 0.001 | 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".