Differential expression of candidate salt‐tolerance genes in the halophyte <i>Helianthus paradoxus</i> and its glycophyte progenitors <i>H. annuus</i> and <i>H. petiolaris</i> (Asteraceae)
Bibliographic record
Abstract
Adaptation to different habitats is considered to be a major force in the generation of organismal diversity. Understanding the genetic mechanisms that produce such adaptations will provide insights into long-standing questions in evolutionary biology and, at the same time, improve predictions of plant responses to changing environmental conditions. Here we used semiquantitative RT-PCR to study the expression of eight candidate salt-tolerance genes in leaves of the highly salt-tolerant diploid hybrid species Helianthus paradoxus and its salt-sensitive progenitor species H. annuus and H. petiolaris. Samples were collected after germination and growth under four different treatments: nonsaline (control), near-natural saline, saline with increased K(+), and saline with decreased Mg(2+) and Ca(2+). Three individuals from three populations per species were used. The hybrid species H. paradoxus constitutively under- or overexpressed genes related to potassium and calcium transport (homologues of KT1, KT2, ECA1), suggesting that these genes may contribute to the adaptation of H. paradoxus to salinity. In two other genes, variation between populations within species exceeded species level variation. Furthermore, homologues of the potassium transporter HAK8 and of a transcriptional regulator were generally overexpressed in saline treatments, suggesting that these genes are involved in sustained growth under saline conditions in Helianthus.
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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) | 0.000 | 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 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".