Gene expression profiling of Jack Pine (Pinus banksiana) under copper stress: Identification of genes associated with copper resistance
Bibliographic record
Abstract
Understanding the genetic response of plants to copper stress is a necessary step to improving the utility of plants for environmental remediation and restoration. The objectives of this study were to: 1) characterize the transcriptome of Jack Pine (Pinus banksiana) under copper stress, 2) analyze the gene expression profile shifts of genotypes exposed to copper ion toxicity, and 3) identify genes associated with copper resistance. Pinus banksiana seedlings were treated with 10 mmoles of copper and screened in a growth chamber. There were 6,213 upregulated and 29,038 downregulated genes expressed in the copper resistant genotypes compared to the susceptible genotypes at a high stringency based on the false discovery rate (FDR). Overall, 25,552 transcripts were assigned gene ontology. Among the top upregulated genes, the response to stress, the biosynthetic process, and the response to chemical stimuli terms represented the highest proportion of gene expression for the biological processes. For the molecular function category, the majority of expressed genes were associated with nucleotide binding followed by transporter activity, and kinase activity. The majority of upregulated genes were located in the plasma membrane while half of the total downregulated genes were associated with the extracellular region. Two candidate genes associated with copper resistance were identified including genes encoding for heavy metal-associated isoprenylated plant proteins (AtHIP20 and AtHIP26) and a gene encoding the pleiotropic drug resistance protein 1 (NtPDR1). This study represents the first report of transcriptomic responses of a conifer species to copper ions.
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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".