Transcriptomic analysis of Asparagus officinalis cultivars with varying levels of freezing tolerance over fall acclimation and spring deacclimation periods
Bibliographic record
Abstract
Asparagus ( Asparagus officinalis L. ) is an important vegetable crop in southern Ontario, Canada, where winter air and soil temperatures below 0°C are common. Consequently, cultivars growing in this area must possess winterhardiness and freezing tolerance for survival. Asparagus acquires freezing tolerance in the fall through cold acclimation and loses freezing tolerance in the spring through deacclimation. To understand the molecular bases of these processes, transcriptomic analysis (RNA-Seq) was conducted on two cultivars, one adapted, ‘Guelph Millennium’ (GM), and one unadapted, ‘UC157’ (UC), to the winter conditions of southern Ontario. RNA extracted from bud and rhizome tissues, sampled on three dates during early spring and late fall, was subjected to sequencing. In the fall, the numbers of differentially expressed (DE) genes at the second and third harvests increased, relative to the first harvest, in dormant buds and rhizomes as freezing tolerance of cultivars increased, and the majority of DE genes were downregulated. In spring, freezing tolerance decreased as plants deacclimated and most genes DE at second and third harvests were upregulated in both cultivars. GM had lower LT 50 (lethal temperature at which 50% of plants die) values and hence higher freezing tolerance than UC on specific sampling dates during both spring and fall, and expression patterns of specific genes were correlated with LT 50 differences. Functional analysis revealed that these genes were involved in carbohydrate metabolic process, plant hormone signal transduction (auxin and gibberellin), proline metabolism, biosynthesis of secondary metabolites, circadian rhythm, and late embryogenesis abundant proteins and could be associated with cold acclimation and deacclimation processes. These findings will help researchers understand the molecular mechanisms of freezing tolerance in asparagus, leading to breeding and genetic strategies to improve the trait.
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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".