Genome expression profile analysis reveals important transcripts in maize roots responding to the stress of heavy metal Pb
Bibliographic record
Abstract
Lead (Pb) has become one of the most abundant heavy metal pollutants of the environment. With its large biomass, maize could be an important object for studying the phytoremediation of Pb-contaminated soil. In our previous research, we screened 19 inbred lines of maize for Pb concentration, and line 178 was identified to be a hyperaccumulator for Pb in both the roots and aboveground parts. To identify important genes and metabolic pathways related to Pb accumulation and tolerance, line 178 was underwent genome expression profile under Pb stress and a control (CK). A total of approximately 11 million cDNA tags were sequenced and 4 665 539 and 4 936 038 clean tags were obtained from the libraries of the test and CK, respectively. In comparison to CK, 2379 and 1832 genes were identified up- or downregulated, respectively, more than fivefolds under Pb stress. Interestingly, all the genes were related to cellular processes and signaling, information storage and processing or metabolism functions. Particularly, the genes involved in posttranslational modification, protein turnover and chaperones; signal transduction, carbohydrate transport and metabolism; and lipid transport and metabolism significantly changed under the treatment. In addition, seven pathways including ribosome, photosynthesis, and carbon fixation were affected significantly, with 118, 12, 34, 21, 18, 72 and 43 differentially expressed genes involved. The significant upregulation of the ribosome pathway may reveal an important secret for Pb tolerance of line 178. And the sharp increase of laccase transcripts and metal ion transporters were suggested to account in part for Pb hyperaccumulation in the line.
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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".