RNA-Seq analysis identifies genes associated with differential reproductive success under drought-stress in accessions of wild barley Hordeum spontaneum
Bibliographic record
Abstract
BACKGROUND: The evolutionary basis of reproductive success in different environments is of major interest in the study of plant adaptation. Since the reproductive stage is particularly sensitive to drought, genes affecting reproductive success during this stage are key players in the evolution of adaptive mechanisms. We used an ecological genomics approach to investigate the reproductive response of drought-tolerant and sensitive wild barley accessions originating from different habitats in the Levant. RESULTS: We sequenced mRNA extracted from spikelets at the flowering stage in drought-treated and control plants. The barley genome was used for a reference-guided assembly and differential expression analysis. Our approach enabled to detect biological processes affecting grain production under drought stress. We detected novel candidate genes and differentially expressed alleles associated with drought tolerance. Drought associated genes were shown to be more conserved than non-associated genes, and drought-tolerance genes were found to evolve more rapidly than other drought associated genes. CONCLUSIONS: We show that reproductive success under drought stress is not a habitat-specific trait but a shared physiological adaptation that appeared to evolve recently in the evolutionary history of wild barley. Exploring the genomic basis of reproductive success under stress in crop wild progenitors is expected to have considerable ecological and economical applications.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".