Expansin Gene Family in Legumes: Structural Diversity and Expression Dynamics
Bibliographic record
Abstract
Expansins are plant-specific proteins that play crucial roles in cell wall loosening and are essential for various developmental processes and stress responses. This study comprehensively analyzes the expansin gene family in legumes, focusing on its structural diversity, evolutionary patterns, expression dynamics, and functional relevance. We classify expansins into α-expansin, β-expansin, and expansin-like A and B subfamilies and discuss their gene duplication events, chromosomal localization, and conserved domain structures in major legume species. Phylogenetic relationships and Ka/Ks ratio analyses provide new insights into their evolutionary trajectories and selective pressures. Furthermore, we investigate tissue-specific and developmental stage-specific expression patterns, highlighting the roles of expansins in root growth, nodulation, and pod formation. Expression profiles under various abiotic and biotic stress conditions reveal their involvement in stress adaptation mediated by hormone signaling pathways. Functional studies involving gene overexpression, gene knockout, and omics-based analyses highlight their contributions to cell expansion, stress tolerance, and the regulation of root system architecture. A case study focusing on soybean illustrates how differential expression and transgenic validation of expansin genes influence drought resistance and nodulation. This study lays the foundation for understanding the functions of expansin genes in legumes and provides prospects for their application in molecular breeding, genome editing, and improving stress tolerance in legume crops.
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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) | 0.000 | 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 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".