A proteome analysis of freezing tolerance in red clover (Trifolium pratense L.)
Bibliographic record
Abstract
BACKGROUND: Improvement of freezing tolerance of red clover (Trifolium pratense L.) would increase its persistence under cold climate. In this study, we assessed the freezing tolerance and compared the proteome composition of non-acclimated and cold-acclimated plants of two initial cultivars of red clover: Endure (E-TF0) and Christie (C-TF0) and of populations issued from these cultivars after three (TF3) and four (TF4) cycles of phenotypic recurrent selection for superior freezing tolerance. Through this approach, we wanted to identify proteins that are associated with the improvement of freezing tolerance in red clover. RESULTS: Freezing tolerance expressed as the lethal temperature for 50 % of the plants (LT50) increased markedly from approximately -2 to -16 °C following cold acclimation. Recurrent selection allowed a significant 2 to 3 °C increase of the LT50 after four cycles of recurrent selection. Two-dimensional difference gel electrophoresis (2D-DIGE) was used to study variations in protein abundance. Principal component analysis based on 2D-DIGE revealed that the largest variability in the protein data set was attributable to the cold acclimation treatment and that the two genetic backgrounds had differential protein composition in the acclimated state only. Vegetative storage proteins (VSP), which are essential nitrogen reserves for plant regrowth, and dehydrins were among the most striking changes in proteome composition of cold acclimated crowns of red clovers. A subset of proteins varied in abundance in response to selection including a dehydrin that increased in abundance in TF3 and TF4 populations as compared to TF0 in the Endure background. CONCLUSION: Recurrent selection performed indoor is an effective approach to improve the freezing tolerance of red clover. Significant improvement of freezing tolerance by recurrent selection was associated with differential accumulation of a small number of cold-regulated proteins that may play an important role in the determination of the level of freezing tolerance.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 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".