Isolation of tagged INUIT gene by establishment of TAIL-PCR in Tobacco
Bibliographic record
Abstract
Chilling injury is one of the key factors restraining plant growth in tropical and subtropical crop species. It is recognized that stability of microtubules is directly linked to systemic cold resistance of entire organism. We used a mutant approach in order to examine a possible function of microtubules in cold resistance. For this reason we characterized a mutant called inuit generated by T-DNA activation tagging (Koncz et al. 1994; Ahad et al. 2003). Inuit mutants were directly screened for long term cold resistance. The analysis of these mutants is targeted to isolate new components of so far hardly known pathway that links cold sensing to microtubular response. A mutant called ATER was screened for resistance to anti microtubular herbicide EPC are altered in microtubular dynamics and are cross resistant to chilling stress (Ahad et al. 2002; 2003). From one of these mutant lines a novel member of cytochrome-P450 oxidase superfamily was identified by a tag. This gene might represent a central element of environmental signaling towards cytoskeleton. Although plasmid rescue technique works very well in Arabidopsis, it seems in tobacco does not work in same extent. Therefore we established a technique called TAIL-PCR in tobacco which is an efficient method to amplify unknown sequences adjacent to known insertion sites was applied here in this study to isolate INUIT gene.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.004 |
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".