Improved thermotolerance in transgenic barley by overexpressing a heat shock factor gene (TaHsfA6b) from wheat
Bibliographic record
Abstract
Temperature is one of the most important abiotic factors defining the yield potential of temperate cereal crops such as barley. The regulators of heat shock response (HSR); Heat shock factors (HSFs) modulate the transcription level of heat responsive genes in order to protect the plants against heat stress. In the present study, a heat shock factor from wheat (TaHSFA6b) is overexpressed in barley for providing thermotolerance. Transgenic barley lines overexpressing TaHSFA6b showed significant improvement in thermotolerance. The constitutive overexpression of TaHSFA6b gene upregulated the expression of major heat shock protein genes as well as other abiotic stress responsive genes. RNA-seq and qRT-PCR analysis showed upregulation of HSPs, chaperonins, DNAJ, LEA proteins and genes related to anti-oxidative enzymes in transgenic lines. Excessive generation and accumulation of ROS occurred in wild type plants during heat stress; however, the transgenic lines reflected improved ROS homeostasis mechanisms in the form of significantly low ROS accumulation under high temperature. There were no negative phenotypic changes in overexpression lines. The present study suggests that TaHSFA6b is one of the major regulators of HSR as it showed the capacity to alter the expression patterns of main defense related genes and enhance the thermotolerance of this cereal crops.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| 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) | 0.011 | 0.006 |
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".