Genome-wide characterization of the <i>PDI</i> gene family in <i>Medicago truncatula</i> and their roles in response to endoplasmic reticulum stress
Bibliographic record
Abstract
Protein disulfide isomerases (PDIs) are pivotal protein folding catalysts in the endoplasmic reticulum (ER) through formation of disulfide bond, isomerization, and inhibition of misfolded protein aggregation. When protein folding capacity is overwhelmed by the demands during transitions between growth phases or under environmental changes, the accumulation of unfolded or misfolded proteins in the ER triggers ER stress. However, little is known about the PDI gene family in the model legume Medicago truncatula, especially the responses to ER stress. Therefore, we identified 17 putative PDI genes from the genome of M. truncatula and present their gene and protein structures, phylogenetic relationships, chromosomal distributions, and synteny analysis with the orthologs in four other eudicot species, including Arabidopsis thaliana, Glycine max, Brassica rapa, and Vitis vinifera. Moreover, expression profiles derived from transcriptome data showed distinct expression patterns of MtPDI genes among plant organs, while real-time quantitative PCR analysis and data from the proteome revealed the potential roles of MtPDI genes in response to ER stress. Our study provides a foundation for further investigations of the biological roles of PDI genes in Medicago, especially their roles in response to ER stress.
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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 | 0.000 | 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 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".