Monoallelic Chromatin Conformation Flanking Long-Range Silenced Domains in Cancer-Derived and Normal Cells
Bibliographic record
Abstract
Epigenetic inactivation of chromatin plays an important role in determining cell phenotype in both normal and cancer cells, but our knowledge is still incomplete with respect to any potential monoallelic nature of the phenomenon. We have genotyped DNA isolated from chromatin of two colorectal cancer-derived lines and a culture of normal human intestinal epithelial cells (HIEC), which was immunoprecipitated with antibodies to acetylated vs. methylated histone H3K9, and presented the data as B allele frequency differences over multiple single-nucleotide polymorphism (SNP) moving window averages. [B allele is an arbitrary term defined as one of the two alleles at any given SNP, named A and B]. Three different validation tests confirmed that peaks exhibiting differences represented monoallelic domains. These complementary tests confirmed the following: 1) genes in the regions of high B allele frequency difference were expressed monoallelically; 2) in normal cells all five imprinting control regions which carried heterozygous SNPs were characterized by B allele difference peaks; and 3) the haplotypes in the B allele difference peaks were faithfully maintained in the chromatin immunoprecipitated with the respective antibodies. In both samples most of the monoallelic domains were found at the boundaries between regions of open and closed chromatin. With respect to the cancer line, this supports the established concept of conformation spreading, but the results from the normal cells were unexpected. Since these cells were polyclonal, the monoallelic structures were probably not determined by random choice as occurs in X-inactivation, so we propose that epigenetic inactivation in some domains may be heritable and polymorphic in normal human cells.
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".