RNA-Seq analysis of nodule development at five different developmental stages of soybean (Glycine max) inoculated with Bradyrhizobium japonicum strain 113-2
Bibliographic record
Abstract
Nodule development directly affects nitrogen fixation efficiency during soybean growth. Although abundant genome-based information related to nodule development has been released and some studies have reported the molecular mechanisms that regulate nodule development, information on the way nodule genes operate in nodule development at different developmental stages of soybean is limited. In this report, notably different nodulation phenotypes in soybean roots inoculated with Bradyrhizobium japonicum strain 113-2 at five developmental stages (branching stage, flowering stage, fruiting stage, pod stage and harvest stage) were shown, and the expression of nodule genes at these five stages was assessed quantitatively using RNA-Seq. Ten comparisons were made between these developmental periods, and their differentially expressed genes were analysed. Some important genes were identified, primarily encoding symbiotic nitrogen fixation-related proteins, cysteine proteases, cystatins and cysteine-rich proteins, as well as proteins involving plant-pathogen interactions. There were no significant shifts in the distribution of most GO functional annotation terms and KEGG pathway enrichment terms between these five development stages. A cystatin Glyma18g12240 was firstly identified from our RNA-seq, and was likely to promote nodulation and delay nodule senescence. This study provides molecular material for further investigations into the mechanisms of nitrogen fixation at different soybean developmental stages.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".