Evidence for Epigenetic Maintenance of <i>Ly49a</i> Monoallelic Gene Expression
Bibliographic record
Abstract
Although structurally unrelated, the human killer cell Ig-like (KIR) genes and the rodent lectin-like Ly49 genes serve similar functional roles in NK cells. Moreover, both gene families display variegated, monoallelic expression patterns established at the transcriptional level. DNA methylation has been shown to play an important role in maintenance of expression patterns of KIR genes, which have CpG island promoters. The potential role of DNA methylation in expression of Ly49 genes, which have CpG-poor promoters, is unknown. In this study, we show that hypomethylation of the region encompassing the Pro-2 promoter of Ly49a and Ly49c in primary C57BL/6 NK cells correlates with expression of the gene. Using C57BL/6 x BALB/c F1 hybrid mice, we demonstrate that the expressed allele of Ly49a is hypomethylated while the nonexpressed allele is heavily methylated, indicating a role for epigenetics in maintaining monoallelic Ly49 gene expression. Furthermore, the Ly49a Pro-2 region is heavily methylated in fetal NK cells but variably methylated in nonlymphoid tissues. Finally, in apparent contrast to the KIR genes, we show that DNA methylation and the histone acetylation state of the Pro-2 region are strictly linked with Ly49a expression status.
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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) | 0.002 | 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".