Sexual epigenetics: gender-specific methylation of a gene in the sex determining region of Populus balsamifera
Bibliographic record
Abstract
Methylation has frequently been implicated in gender determination in plants. The recent discovery of the sex determining region (SDR) of balsam poplar, Populus balsamifera, pinpointed 13 genes with differentiated X and Y copies. We tested these genes for differential methylation using whole methylome sequencing of xylem tissue of multiple individuals grown under field conditions in two common gardens. The only SDR gene to show a marked pattern of gender-specific methylation is PbRR9, a member of the two component response regulator (type-A) gene family, involved in cytokinin signalling. It is an ortholog of Arabidopsis genes ARR16 and ARR17. The strongest patterns of differential methylation (mostly male-biased) are found in the putative promoter and the first intron. The 4th intron is strongly methylated in both sexes and the 5th intron is unmethylated in both sexes. Using a statistical learning algorithm we find that it is possible accurately to assign trees to gender using genome-wide methylation patterns alone. The strongest predictor is the region coincident with PbRR9, showing that this gene stands out against all genes in the genome in having the strongest sex-specific methylation pattern. We propose the hypothesis that PbRR9 has a direct, epigenetically mediated, role in poplar sex determination.
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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".