Frequency of cytosine methylation in the adjacent regions of soybean retrotransposon <i>SORE-1</i> depends on chromosomal location
Bibliographic record
Abstract
Mobilization of transposable elements (TEs) is suppressed by epigenetic mechanisms involving cytosine methylation. However, few studies have focused on clarifying relationships between epigenetic influences of TEs on the adjacent DNA regions and time after insertion of TEs into the genome and/or their chromosomal location. Here we addressed these issues using soybean retrotransposon SORE-1. We analyzed SORE-1, inserted in exon 1 of the GmphyA2 gene, one of the newest insertions in this family so far identified. Cytosine methylation was detected in this element but was barely present in the adjacent regions. These results were correlated, respectively, with the presence and absence of the production of short interfering RNAs. Cytosine methylation profiles of 74 SORE-1 elements in the Williams 82 reference genome indicated that methylation frequency in the adjacent regions of SORE-1 was profoundly higher in pericentromeric regions than in euchromatic chromosome arms and was only weakly correlated with the length of time after insertion into the genome. Notably, the higher level of methylation in the 5′ adjacent regions of SORE-1 coincided with the presence of repetitive elements in pericentromeric regions. Together, these results suggest that epigenetic influence of SORE-1 on the adjacent regions is influenced by its location on the chromosome.
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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".