Transcriptomic analysis of the heat-stress response in <i>Boechera depauperata</i> and <i>Arabidopsis</i> reveals a distinct and unusual heat-stress response in <i>Boechera</i>
Bibliographic record
Abstract
Global surface temperatures are expected to rise throughout the 21st century, and negatively impact plant growth and reproduction. Thus, it is imperative that we deepen our understanding of plant thermotolerance. The examination of native plant species that have evolved tolerance to high temperatures can provide crucial information on how plants can adapt to climate change. Boechera (Brassicaceae), a large genus that is native to North America, is highly thermotolerant, and can maintain photosynthetic activity at high temperatures. Here we report results of transcriptomic studies that seek to reveal possible thermotolerance mechanisms in B. depauperata (A.Nelson & P.B.Kenn.) Windham & Al-Shehbaz. Analysis of RNA-seq datasets from heat stressed B. depauperata and Arabidopsis thaliana (L.) Heynh. plants identified significant differences in how each of these species responds to identical heat stress conditions. The most highly upregulated heat-stress genes in A. thaliana includes the well-characterized heat-shock genes. In contrast, the Boechera heat-stress response is composed of: novel genes that lack orthologs in other genomes; genes coding for proteins of uncharacterized function; and genes coding for proteins associated with the unfolded protein and endoplasmic reticulum stress responses. In addition, genes that are protective of photosynthetic capacity are also differentially upregulated in B. depauperata.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".