Decrypting Molecular Mechanisms Involved in Counteracting Copper and Nickel Toxicity in Jack Pine (Pinus banksiana) Based on Transcriptomic Analysis
Bibliographic record
Abstract
The remediation of copper and nickel-afflicted sites is challenged by the different physiological effects imposed by each metal on a given plant system. Pinus banksiana is resilient against copper and nickel, providing an opportunity to build a valuable resource to investigate the responding gene expression toward each metal. The objectives of this study were to (1) extend the analysis of the Pinus banksiana transcriptome exposed to nickel and copper, (2) assess the differential gene expression in nickel-resistant compared to copper-resistant genotypes, and (3) identify mechanisms specific to each metal. The Illumina platform was used to sequence RNA that was extracted from seedlings treated with each of the metals. There were 449 differentially expressed genes (DEGs) between copper-resistant genotypes (RGs) and nickel-resistant genotypes (RGs) at a high stringency cut-off, indicating a distinct pattern of gene expression toward each metal. For biological processes, 19.8% of DEGs were associated with the DNA metabolic process, followed by the response to stress (13.15%) and the response to chemicals (8.59%). For metabolic function, 27.9% of DEGs were associated with nuclease activity, followed by nucleotide binding (27.64%) and kinase activity (10.16%). Overall, 21.49% of DEGs were localized to the plasma membrane, followed by the cytosol (16.26%) and chloroplast (12.43%). Annotation of the top upregulated genes in copper RG compared to nickel RG identified genes and mechanisms that were specific to copper and not to nickel. NtPDR, AtHIPP10, and YSL1 were identified as genes associated with copper resistance. Various genes related to cell wall metabolism were identified, and they included genes encoding for HCT, CslE6, MPG, and polygalacturonase. Annotation of the top downregulated genes in copper RG compared to nickel RG revealed genes and mechanisms that were specific to nickel and not copper. Various regulatory and signaling-related genes associated with the stress response were identified. They included UGT, TIFY, ACC, dirigent protein, peroxidase, and glyoxyalase I. Additional research is needed to determine the specific functions of signaling and stress response mechanisms in nickel-resistant plants.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".