Transcriptional profiling of hexaploid wheat (<i>Triticum aestivum</i> L.) roots identifies novel, dehydration‐responsive genes
Bibliographic record
Abstract
We used a long-oligonucleotide microarray to identify transcripts that increased or decreased in abundance in roots of dehydration-tolerant hexaploid bread wheat, in response to withholding of water. We observed that the major classes of dehydration-responsive genes (e.g. osmoprotectants, compatible solutes, proteases, glycosyltransferases/hydrolases, signal transducers components, ion transporters) were generally similar to those observed previously in other species and osmotic stresses. More specifically, we highlighted increases in transcript expression for specific genes including those putatively related to the synthesis of asparagine, trehalose, oligopeptide transporters, metal-binding proteins, the gamma-aminobutyric acid (GABA) shunt and transcription factors. Conversely, we noted a decrease in transcript abundance for diverse classes of glutathione and sulphur-related enzymes, specific amino acids, as well as MATE-efflux carrier proteins. From these data, we identified a novel, dehydration-induced putative AP2/ERF transcription factor, which we predict to function as a transcriptional repressor. We also identified a dehydration-induced 'little protein' (LitP; predicted mass: 8 kDa) that is highly conserved across spermatophytes. Using qRT-PCR, we compared the expression patterns of selected genes between two related wheat genotypes that differed in their susceptibility to dehydration, and confirmed that these novel genes were highly inducible by water limitation in both genotypes, although the magnitude of induction differed.
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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".