Dehydration response in <scp><i>Stylosanthes scabra</i></scp>: Transcriptional, biochemical, and physiological modulations
Bibliographic record
Abstract
Stylosanthes scabra, popularly known as stylo, is native to the Brazilian Caatinga semiarid region and stands out as a drought-tolerant shrub forage crop. This work provides information about the plant response during the first 48 h of water deficit, followed by a rehydration treatment. Besides root transcriptomics data, 13 physiological or biochemical parameters were scrutinized. Additionally, RNA-Seq annotated transcripts not associated with the "Viridiplantae" clade were taxonomically categorized. It was found that S. scabra quickly perceives and recovers from the oscillations of the imposed water regime. Physiologically, mechanisms that minimize evapotranspiration or protect the photosynthetic apparatus stood out. Biochemically, it was found that the root tissue invests in synthesizing compounds that can act as osmolytes (proline and sugars), emphasizing the importance of osmoregulation to water deficit acclimation. Consistently, transcriptome and qPCR analyses showed that a set of enriched biological processes with upregulated (UR) transcripts were involved in protective functions against reactive oxygen species or encoding enzymes of important metabolic pathways, which might contribute to S. scabra response to water deficit. Additionally, several UR kinases and transcription factors were identified. Finally, in an innovative approach, some naturally occurring microbial groups (such as Schizosaccharomyces, Bradyrhizobium, etc.) were identified in the S. scabra roots. This study reveals insights into the physiological, biochemical, and molecular mechanisms underlying the S. scabra response to water deficit and provides candidate genes that may be useful in developing drought-tolerant crop varieties through biotechnological applications.
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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 | 0.001 |
| 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".