Cold induced expression of plant defensin and lipid transfer protein transcripts in winter wheat
Bibliographic record
Abstract
In winter wheat, low temperature hardening induces a non‐specific resistance to snow moulds and other fungi. In a suppressive subtractive hybridization cDNA library between winter wheat unhardened and hardened at 2°C, 17% of 186 sequenced cDNA clones were homologous to the small plant defence related proteins, γ‐thionin, γ‐purothionin or non‐specific lipid transfer proteins (LTPs), based on their nucleotide sequences or deduced from amino acid sequences. Several partial‐ and full‐length cDNA clones homologous to two defensin proteins (γ‐thionin, subfamily B‐2, γ‐purothionin, subfamily I), and non‐specific LTPs were isolated. Regulation of defensin transcripts was clearly different from that of the LTPs under controlled environments in the field. The γ‐thionin and γ‐purothionin transcripts were not expressed in unhardened plants grown at 20°C, strongly upregulated after 1–3 days hardening at 2°C, remained upregulated for 28 days hardening, and disappeared following 1 day of exposure to dehardening conditions at 20°C. The LTPs transcripts were constitutively expressed in plants growing at 20°C, gradually increased to maximum levels following 14–28 days at hardening, and remained upregulated following 1 and 7 days dehardening. In the field, the γ‐thionin and γ‐purothionin transcripts rapidly increased to maximum levels by mid‐November and decreased gradually during the winter until mid‐March LTP transcripts were highly expressed in the early autumn, further increased during December–January, then decreased during late winter and early spring. Differences in the pattern and level of expression of these transcripts were evident among cultivars; γ‐thionin expression was associated with freezing resistance among the genotypes tested under both controlled environment and field 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".