DNA methylation polymorphism in annual wild soybean (<i>Glycine soja</i> Sieb. et Zucc.) and cultivated soybean (<i>G. max</i> L. Merr.)
Bibliographic record
Abstract
To study DNA methylation polymorphism in soybean, 20 and 27 lines of annual wild and cultivated soybeans, respectively, were selected from previously established “Soybean Core Collections in China”, and subjected to methylation-sensitive amplified polymorphism (MSAP) analysis. Twenty-seven primer pairs generated 984 CG/CNG methylation sites across the 47 lines, and the data were dissected into methylation-sensitive (MS) and methylation-insensitive(MIS) polymorphisms. The calculated MSP vs. MISP for wild soybeans were 34.65 vs. 34.76%, while corresponding results for the cultivated soybeans were 47.05 vs. 47.15%, indicating higher levels of MSP and MISP in cultivated than in wild soybeans. These results were incongruent with the amplified fragment length polymorphism (AFLP) analysis of the same soybean lines, and suggested enhanced DNA methylation polymorphism due to human selection. All three markers, MSP, MISP and AFLP, enabled clustering of the soybean lines into two distinct groups each predominantly containing wild or cultivated ones. Homology search indicated that 12 out of 24 sequenced MSPs had significant similarities to known-function or predicated genes, suggesting possible functional relevance of the methylation polymorphism. No significant association between MSP and MISP or MSP and AFLP was detected. Our results suggest that DNA methylation polymorphism in soybean has been under both natural and human selections, implicating possible roles of this epigenetic modification in genome evolution and domestication.Key words: Annual wild soybean (Glycine soja), cultivated soybean (G. max), DNA methylation polymorphism, epigenetic variation, evolution, domestication
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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 | 0.001 | 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) | 0.000 | 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 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".