Coding and long non-coding RNAs provide evidence of distinct transcriptional reprogramming for two ecotypes of the extremophile plant Eutrema salsugineum undergoing water deficit stress
Bibliographic record
Abstract
BACKGROUND: The severity and frequency of drought has increased around the globe, creating challenges in ensuring food security for a growing world population. As a consequence, improving water use efficiency by crops has become an important objective for crop improvement. Some wild crop relatives have adapted to extreme osmotic stresses and can provide valuable insights into traits and genetic signatures that can guide efforts to improve crop tolerance to water deficits. Eutrema salsugineum, a close relative of many cruciferous crops, is a halophytic plant and extremophyte model for abiotic stress research. RESULTS: Using comparative transcriptomics, we show that two E. salsugineum ecotypes display significantly different transcriptional responses towards a two-stage drought treatment. Even before visibly wilting, water deficit led to the differential expression of almost 1,100 genes for an ecotype from the semi-arid, sub-arctic Yukon, Canada, but only 63 genes for an ecotype from the semi-tropical, monsoonal, Shandong, China. After recovery and a second drought treatment, about 5,000 differentially expressed genes were detected in Shandong plants versus 1,900 genes in Yukon plants. Only 13 genes displayed similar drought-responsive patterns for both ecotypes. We detected 1,007 long non-protein coding RNAs (lncRNAs), 8% were only expressed in stress-treated plants, a surprising outcome given the documented association between lncRNA expression and stress. Co-expression network analysis of the transcriptomes identified eight gene clusters where at least half of the genes in each cluster were differentially expressed. While many gene clusters were correlated to drought treatments, only a single cluster significantly correlated to drought exposure in both ecotypes. CONCLUSION: Extensive, ecotype-specific transcriptional reprogramming with drought was unexpected given that both ecotypes are adapted to saline habitats providing persistent exposure to osmotic stress. This ecotype-specific response would have escaped notice had we used a single exposure to water deficit. Finally, the apparent capacity to improve tolerance and growth after a drought episode represents an important adaptive trait for a plant that thrives under semi-arid Yukon conditions, and may be similarly advantageous for crop species experiencing stresses attributed to climate change.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".