Comparative analyses of the Smith−Magenis syndrome protein RAI1 in mice and common marmoset monkeys
Bibliographic record
Abstract
Retinoic acid-induced 1 (RAI1) encodes a transcriptional regulator critical for brain development and function. RAI1 haploinsufficiency in humans causes a syndromic autism spectrum disorder known as Smith-Magenis syndrome (SMS). The neuroanatomical distribution of RAI1 has not been quantitatively analyzed during the development of the prefrontal cortex, a brain region critical for cognitive function and social behaviors and commonly implicated in autism spectrum disorders, including SMS. Here, we performed comparative analyses to uncover the evolutionarily convergent and divergent expression profiles of RAI1 in major cell types during prefrontal cortex maturation in common marmoset monkeys (Callithrix jacchus) and mice (Mus musculus). We found that while RAI1 in both species is enriched in neurons, the percentage of excitatory neurons that express RAI1 is higher in newborn mice than in newborn marmosets. By contrast, RAI1 shows similar neural distribution in adult marmosets and adult mice. In marmosets, RAI1 is expressed in several primate-specific cell types, including intralaminar astrocytes and MEIS2-expressing prefrontal GABAergic neurons. At the molecular level, we discovered that RAI1 forms a protein complex with transcription factor 20 (TCF20), PHD finger protein 14 (PHF14), and high mobility group 20A (HMG20A) in the marmoset brain. In vitro assays in human cells revealed that TCF20 regulates RAI1 protein abundance. This work demonstrates that RAI1 expression and protein interactions are largely conserved but with some unique expression in primate-specific cells. The results also suggest that altered RAI1 abundance could contribute to disease features in disorders caused by TCF20 dosage imbalance.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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".