Chromatin modification of the human imprinted <i>NDN</i> (necdin) gene detected by in vivo footprinting
Bibliographic record
Abstract
Allele-specific transcription is a characteristic feature of imprinted genes. Many imprinted genes are also transcribed in a tissue- or cell type-specific manner. Overlapping epigenetic signals must, therefore, modulate allele-specific and tissue-specific expression at imprinted loci. In addition, long-range interactions with an Imprinting Center (IC) may influence transcription, in an allele-specific or cell-type specific manner. The IC on human chromosome 15q11 controls parent-of-origin specific allelic identity of a set of genes located in cis configuration within 2 Mb. We have now examined the chromatin accessibility of the promoter region of one of the Imprinting Centre-controlled genes, NDN encoding necdin, using in vivo DNA footprinting to identify sites of DNA-protein interaction and altered chromatin configuration. We identified sites of modified chromatin that mark the parental alleles in NDN-expressing cells, and in cells in which NDN is not expressed. Our results suggest that long-lasting allele-specific marks and more labile tissue-specific marks layer epigenetic information that can be discriminated using DNA footprinting methodologies. Sites of modified chromatin mark the parental alleles in NDN-expressing cells, and in cells in which NDN is not expressed. Our results suggest that a layering of epigenetic information controls allele- and tissue-specific gene expression of this imprinted gene.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".