Widespread Alu repeat-driven expansion of consensus DR2 retinoic acid response elements during primate evolution
Bibliographic record
Abstract
BACKGROUND: Nuclear receptors are hormone-regulated transcription factors whose signaling controls numerous aspects of development and physiology. Many receptors recognize DNA hormone response elements formed by direct repeats of RGKTCA motifs separated by 1 to 5 bp (DR1-DR5). Although many known such response elements are conserved in the mouse and human genomes, it is unclear to which extent transcriptional regulation by nuclear receptors has evolved specifically in primates. RESULTS: We have mapped the positions of all consensus DR-type hormone response elements in the human genome, and found that DR2 motifs, recognized by retinoic acid receptors (RARs), are heavily overrepresented (108,582 elements). 90% of these are present in Alu repeats, which also contain lesser numbers of other consensus DRs, including 50% of consensus DR4 motifs. Few DR2s are in potentially mobile AluY elements and the vast majority are also present in chimp and macaque. 95.5% of Alu-DR2s are distributed throughout subclasses of AluS repeats, and arose largely through deamination of a methylated CpG dinucleotide in a non-consensus motif present in AluS sequences. We find that Alu-DR2 motifs are located adjacent to numerous known retinoic acid target genes, and show by chromatin immunoprecipitation assays in squamous carcinoma cells that several of these elements recruit RARs in vivo. These findings are supported by ChIP-on-chip data from retinoic acid-treated HL60 cells revealing RAR binding to several Alu-DR2 motifs. CONCLUSION: These data provide strong support for the notion that Alu-mediated expansion of DR elements contributed to the evolution of gene regulation by RARs and other nuclear receptors in primates and humans.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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 | 0.001 |
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".