Functional divergence of BnaWRKY7 homologs drives phytosterol variations in polyploid Brassica napus
Bibliographic record
Abstract
• GWAS, temporal transcriptome and phytosterol profiles were used to identify key genes. • Two WRKY7 homologs as key TF regulators of phytosterol biosynthesis. • BnaC07.WRKY7 improve phytosterol content by interacting with four biosynthesis genes. Gene duplication and subsequent functional divergence drive species evolution, adaptability, and biodiversity, particularly in polyploids. The polyploid Brassica napus has abundant phytosterols, which are crucial for plant growth and development, and human health. However, the regulatory mechanism of phytosterol biosynthesis remains poorly understood in polyploid systems. This study aims to provide a novel method for analyzing the functions of multi-copy homologous genes and to dissect the genetic and molecular basis of phytosterol biosynthesis in B. napus . Genome-wide association studies (GWAS), temporal transcriptome and phytosterol metabolomics were employed to identify phytosterol-regulatory genes. Transgenic validation ( B. napus ) combined with yeast one-hybrid assay, dual-luciferase reporter assay and electrophoretic mobility shift assay were used to reveal phytosterol biosynthesis mechanisms. Through dynamic gene expression analysis and phytosterol profiles, 103 transcription factors (TFs) were preliminarily screened out by coordinating an intricate transcriptional program. Then, GWAS revealed two highly significant loci on chromosomes A03 and C07, located in syntenic regions between the A n - and C n -subgenomes. By integrating synteny-based candidate gene identification approach and comparative expression analysis, we pinpointed two WRKY7 homologs as key TF regulators of phytosterol biosynthesis. The sequences, structures, and expression patterns of these two WRKY7 homologs were highly similar but significantly different from other homologs, indicating that the functional divergence of WRKY7 homologs drives natural variation in phytosterols. Transgenic validation, combined with phytosterol rate calculations and molecular interaction assays, mechanistically confirmed their regulatory roles in shaping phytosterol variations. In this study, we established a multi-copy gene co-screening strategy and elucidated the molecular mechanism by which BnaWRKY7 regulates phytosterol variations interacting with four key phytosterol biosynthesis genes. The findings enhance our understanding of the temporal regulation of phytosterols in polyploids, establish a foundation for future research on duplicated genes and genome evolution, and propose targets for high-phytosterol crops.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".