Genome‐Wide Identification and Characterization of the Wheat Remorin ( <i>Ta</i> REM) Family during Cold Acclimation
Bibliographic record
Abstract
Remorins (REMs) are plant-specific proteins that play an essential role in plant-microbe interactions. However, their roles in vernalization and abiotic stress responses remain speculative. Most remorins have a variable proline-rich -half and a more conserved -half that is predicted to form coils. A search of the wheat ( L.) database revealed the existence of 20 different genes, which we classified into six groups on the basis of whether they shared a common phylogenetic and structural origin. Analysis of the physical genomic distributions demonstrated that genes are dispersed in the wheat genome and have one to seven introns. Promoter analysis of genes revealed the presence of putative -elements related to diverse functions like development, hormonal regulation, and biotic and abiotic stress responsiveness. Expression levels of genes were measured in plants grown under field and controlled conditions and in response to hormone treatment. Our analyses revealed that 12 members of the REM family are regulated during cold acclimation in wheat in four different tissues (roots, crowns, stems, and leaves), with the highest expression in roots. Differential gene expression was found between wheat cultivars with contrasting degrees of cold tolerance, suggesting the implication of genes in cold response and tolerance. Additionally, eight genes were induced in response to abscisic acid and methyl jasmonate treatment. This genome-wide analysis of genes provides valuable resources for functional analysis aimed at understanding their role in stress adaptation.
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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".