Integration of genome wide association studies and co‐expression networks reveal roles of <i>PtoWRKY</i><i>42‐PtoUGT76C1‐1</i> in <i>trans</i>‐zeatin metabolism and cytokinin sensitivity in poplar
Bibliographic record
Abstract
Cytokinins are important for in vitro shoot regeneration in plants. Cytokinin N-glucosides are produced via an irreversible glycosylation pathway, which regulates the endogenous cytokinin content. Although cytokinin N-glucoside pathways have been uncovered in higher plants, no regulator has been identified to date. We performed a metabolome genome-wide association study (mGWAS), weighted gene co-expression network analysis (WGCNA), and expression quantitative trait nucleotide (eQTN) mappings to build a core triple genetic network (mGWAS-gene expression-phenotype) for the trans-zeatin N-glucoside (ZNG) metabolite using data from 435 unrelated Populus tomentosa individuals. Variation of the ZNG level in poplar is attributed to the differential transcription of PtoWRKY42, a member of WRKY multigene family group IIb. Functional analysis revealed that PtoWRKY42 negatively regulated ZNG accumulation by binding directly to the W-box of the UDP-glycosyltransferase 76C 1-1 (PtoUGT761-1) promoter. Also, PtoWRKY42 was strongly induced by leaf senescence, 6-BA, wounding, and salt stress, resulting in a reduced ZNG level. We identified PtoWRKY42, a negative regulator of cytokinin N-glucosides, which contributes to the natural variation in ZNG level and mediates ZNG accumulation by directly modulating the key glycosyltransferase gene PtoUGT76C1-1.
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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".