Genome-wide identification and analysis of the aldehyde dehydrogenase gene superfamily in Chinese cabbage (<i>Brassica rapa</i> subsp. <i>pekinensis</i>)
Bibliographic record
Abstract
Aldehyde dehydrogenases (ALDHs) encode a class of enzymes that dehydrooxidize aldehydes into corresponding carboxylic acids, which are involved in the growth and development of plants and in the response to various biological and abiotic stresses. In this study, we identified 27 ALDH genes in the Chinese cabbage genome and grouped them into 10 different families. Chromosomal mapping revealed that, except for one gene distributed on Scaffold, the remaining 26 genes were unevenly distributed on 10 chromosomes of Chinese cabbage. Based on a comparison of the homologous relationship between BrALDHs and ALDH genes in Arabidopsis thaliana, duplicated patterns of the ALDH gene family in Chinese cabbage were analyzed. The exon–intron structures, conserved protein motifs, and phylogenetic relationship with ALDH in six other species were also predicted and analyzed. Finally, we used available RNA-Seq data and real-time quantitative PCR to analyze the expression of ALDH genes in different tissues of Chinese cabbage including the roots, stems, leaves, flowers, and siliques. The results showed the tissue specificity and differential expression in different tissues of BrALDHs. The analysis of ALDH gene transcriptome data of Chinese cabbage under different stress conditions (cold, heat, drought, and salinity) showed that the response levels of different genes varied under different stresses, suggesting the function of some genes in these processes. Details of the ALDH gene family in Chinese cabbage has enriched studies on the ALDH gene family in plants and animals and is crucial for understanding ALDH function during plant growth and development.
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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 | 0.001 | 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".