The WRKY Transcription Factor Genes in Eggplant (Solanum melongena L.) and Turkey Berry (Solanum torvum Sw.)
Bibliographic record
Abstract
WRKY transcription factors, which play critical roles in stress responses, have not been characterized in eggplant or its wild relative, turkey berry. The recent availability of RNA-sequencing data provides the opportunity to examine WRKY genes from a global perspective. We identified 50 and 62 WRKY genes in eggplant (SmelWRKYs) and turkey berry (StorWRKYs), respectively, all of which could be classified into three groups (I-III) based on the WRKY protein structure. The SmelWRKYs and StorWRKYs contain ~76% and ~95% of the number of WRKYs found in other sequenced asterid species, respectively. Positive selection analysis revealed that different selection constraints could have affected the evolution of these groups. Positively-selected sites were found in Groups IIc and III. Branch-specific selection pressure analysis indicated that most WRKY domains from SmelWRKYs and StorWRKYs are conserved and have evolved at low rates since their divergence. Comparison to homologous WRKY genes in Arabidopsis revealed several potential pathogen resistance-related SmelWRKYs and StorWRKYs, providing possible candidate genetic resources for improving stress tolerance in eggplant and probably other Solanaceae plants. To our knowledge, this is the first report of a genome-wide analyses of the SmelWRKYs and StorWRKYs.
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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 | 0.000 |
| 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".