Changes in Soybean Global Gene Expression after Application of Lipo-Chitooligosaccharide from Bradyrhizobium japonicum under Sub-Optimal Temperature
Bibliographic record
Abstract
Lipo-chitooligosaccharides (LCOs), signal compounds produced by N(2)-fixing rhizobacteria after isoflavone induction, initiate nodule formation in host legumes. Given LCOs' structural similarity to pathogen-response-eliciting chitin oligomers, foliar application of LCOs was tested for ability to induce stress-related genes under optimal growth conditions. In order to study the effects of LCO foliar spray under stressed conditions, soybean (Glycine max) seedlings grown at optimal temperature were transferred to sub-optimal temperature. After a 5-day acclimation period, the first trifoliate leaves were sprayed with 10(-7) M LCO (NodBj-V (C(18:1), MeFuc)) purified from genistein-induced Bradyrhizobium japonicum culture, and harvested at 0 and 48 h following treatment. Microarray analysis was performed using Affymetrix GeneChip® Soybean Genome Arrays. Compared to the control at 48 h after LCO treatment, a total of 147 genes were differentially expressed as a result of LCO treatment, including a number of stress-related genes and transcription factors. In addition, during the 48 h time period following foliar spray application, over a thousand genes exhibited differential expression, including hundreds of those specific to the LCO-treated plants. Our results indicated that the dynamic soybean foliar transcriptome was highly responsive to LCO treatment. Quantitative real-time PCR (qPCR) validated the microarray data.
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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".