Differential levels of gene expression and molecular mechanisms between red maple (<i>Acer rubrum</i>) genotypes resistant and susceptible to nickel toxicity revealed by transcriptome analysis
Bibliographic record
Abstract
Abstract Knowledge of regulation of genes associated with metal resistance in higher plants is very limited. Many plant species have developed different genetic mechanisms and metabolic pathways to cope with metal toxicity. The main objectives of this study were to 1) assess gene expression dynamics of A. rubrum in response to nickel (Ni) stress and 2) describe gene function based on ontology. Certified A. rubrum genotypes were treated with 1,600 mg of Ni per 1 Kg of soil corresponding to a soil total nickel content in a metal‐contaminated region in Ontario, Canada. Nickel resistant and susceptible genotypes were selected and used for transcriptome analysis. Overall, 223,610,443 bases were generated. Trinity reads were assembled to trinity transcripts. The transcripts were mapped to protein sequences and after quality controls and appropriate trimmings, 66,783 annotated transcripts were selected as expressed among the libraries. The study reveals that nickel treatment at a high dose of 1,600 mg/kg triggers regulation of several genes. When nickel‐resistant genotypes were compared to water controls, 6,263 genes were upregulated and 3,142 were downregulated. These values were 3,308 and 2,176, respectively, when susceptible genotypes were compared to water control. The coping mechanism of A. rubrum to Ni toxicity was elucidated. Upregulation of genes associated with transport in cytosol was prevalent in resistant genotypes compared to controls while upregulation of genes associated with translation in the ribosome was higher in susceptible genotypes when compared to water. The analysis revealed no major gene associated with Ni resistance in A. rubrum. Overall, the results of this study suggest that the genetic mechanism controlling the resistance of this species to nickel is controlled by genes with limited expression. The subtle differences between resistant and susceptible genotypes in gene regulation were detected using water‐treated genotypes as references.
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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) | 0.001 | 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".