Effect of Transgenes on Global Gene Expression in Soybean Is within the Natural Range of Variation of Conventional Cultivars
Bibliographic record
Abstract
Current safety assessment for novel crops, including transgenic crops, uses a targeted approach, which relies on compositional analysis. The possibility that transgene expression could lead to unintended effects remains a debated issue. This study used transcriptome profiling as a nontargeted approach to evaluate overall molecular changes in transgenic soybean cultivars. Global gene expression was measured in the first trifoliate leaves of two transgenic and three conventional soybean cultivars using the soybean Affymetrix GeneChip. It was found that gene expression differs more between the two conventional cultivars than between the transgenics and their closest conventional cultivar investigated and that the magnitudes of differences measured in gene expression and genotype (determined by SSR analysis) do not necessarily correlate. A MySQL database coupled with a CGI Web interface was developed to store and present the results (http://soyxpress.agrenv.mcgill.ca/). By integrating the microarray data with gene annotations and other soybean data, a comprehensive view of differences in gene expression is explored between cultivars.
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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 | 0.000 |
| 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) | 0.011 | 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".