memo-eQTL: DNA methylation modulated genetic variant effect on gene transcriptional regulation
Bibliographic record
Abstract
Abstract Expression quantitative trait locus (eQTL) analysis has become an important tool in understanding the link between genetic variants and gene expression, ultimately helping to bridge the gap between risk SNPs and associated diseases. Recently, we identified and validated a specific case where the methylation of a CpG site can affect the relationship between the genetic variant and gene expression. To systematically evaluate this regulatory mechanism, we developed an extended eQTL mapping method named DNA methylation modulated eQTL (memo-eQTL). We performed memo-eQTL mapping in 128 normal prostate samples and discovered 1,731 memo-eQTLs, a vast majority of which have not been reported as eQTLs. We found that the methylation of the memo-eQTL CpG sites can either enhance or insulate the interaction between SNP and Gene expression by altering CTCF-based chromatin 3D structure. This study demonstrated the prevalence of memo-eQTLs, which can enable the identification of novel causal genes for traits or diseases associated with genetic variations.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".