PR-10, defensin and cold dehydrin genes are among those over expressed in Oxytropis (Fabaceae) species adapted to the arctic
Bibliographic record
Abstract
In many studied plants, typical responses to cold treatment include up-regulating the hydrophilic COR/LEA genes and down-regulating photosynthesis-related genes, carbohydrate metabolism, GDSL-motif lipase, hormone metabolism and oxidative regulation genes. However, next to nothing is known about gene expression in arctic plants, which are actually adapted to a harsh, cold environment. The molecular mechanisms behind the many specific adaptations of arctic plants, such as slow growth, well-developed root systems and short stature, are not well understood. In this study, we examine whole plantlet transcriptome differences between two arctic and two temperate Oxytropis (Fabaceae) species, grown under their respective controlled environmental conditions. Gene expression differences are analyzed using cDNA library subtraction followed by expressed sequence tags sequencing and annotation. Sequences from a total of nearly 2,000 clones cluster into 121 and 368 unique genes from the arctic and from the temperate plants, respectively. The predominant biological process for genes from the arctic-enriched library is "response to stimulus". A concurrent overexpression of pathogenesis-related class 10 proteins (PR-10), plant defensin and cold dehydrin genes is a novel feature for species adapted to stressful growth environment. The temperate-enriched genes are involved in photosynthesis, translation and nucleosome assembly. Interestingly, both arctic and temperate-enriched libraries also contain genes involved in ribosome biogenesis and assembly, however of different types. Real-time reverse transcription PCR of cold dehydrin and two PR-10 genes, as well as the light harvesting complex b1 genes demonstrates that the gene expression is dependent on species and growth conditions.
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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) | 0.001 | 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".