Enhanced Loss of Retinoic Acid Network Genes in Xenopus laevis Achieves a Tighter Signal Regulation
Bibliographic record
Abstract
Retinoic acid (RA) is a major regulatory signal during embryogenesis produced from vitamin A (retinol) by an extensive, autoregulating metabolic and signaling network to prevent fluctuations that result in developmental malformations. Xenopus laevis is an allotetraploid hybrid frog species whose genome includes L (long) and S (short) chromosomes from the originating species. Evolutionarily, the X. laevis subgenomes have been losing either L or S homoeologs in about 43% of genes to generate singletons. In the RA network, out of the 47 genes, about 47% have lost one of the homoeologs, like the genome average. Interestingly, RA metabolism genes from storage (retinyl esters) to retinaldehyde production exhibit enhanced gene loss with 75% singletons out of 28 genes. The effect of this gene loss on RA signaling autoregulation was studied. Employing transient RA manipulations, homoeolog gene pairs were identified in which one homoeolog exhibits enhanced responses or looser regulation than the other, while in other pairs both homoeologs exhibit similar RA responses. CRISPR/Cas9 targeting of individual homoeologs to reduce their activity supports the hypothesis where the RA metabolic network gene loss results in tighter network regulation and more efficient RA robustness responses to overcome complex regulation conditions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".