Molecular cloning of stress-induced genes of maize (Zea mays L.) using the pcr-select cdna subtraction technique
Bibliographic record
Abstract
Environmental abiotic stresses, such as drought, high-salinity and low temperature, severely impair plant growth and development and limit crop productivity. In order to survive and adapt to these stresses, plants must induce various physiological, bichemical and molecular changes, including the adaptation of the photosynthetic apparatus, changing in the membrane lipid, the activation of calcium influxes and Ca2+-dependent protein kinase cascades, the accumulation of proline, glycine betaine, soluble sugars and increasing the levels of antioxidants. All these changes are accompanied by notable increases or decreases in the transcript level of specific genes. Hence, transcriptional control of stress-regulated genes is a crucial part of plant responses to abiotic stresses; a further characterization of such gene transcripts in plants may help us to understand the molecular basis of the plant response to abiotic stresses and to identify new targets for manipulating biochemical, physiological and developmental processes in plants. To clarify the process of the response of maize to cold stress and to discover maize genes associated with the response pathway(s), genes induced by cold treatment were isolated according to the PCR-select cDNA subtraction method. 18 cold-induced genes (ZmCOI) were detected at 6°C. They were divided into 6 groups, based on their functions. The cold induction of these genes was confirmed by reverse transcriptase-polymerase chain reaction (RT-PCR) analyses. The sequences of these 18 cold-induced genes have been deposited in GenBank under accesion numbers from DQ078760 to DQ078778.
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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 | 0.000 |
| 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) | 0.000 | 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".