Mutation and evolutionary analyses identify <i>NR2E1‐</i>candidate‐regulatory mutations in humans with severe cortical malformations
Bibliographic record
Abstract
Nuclear receptor 2E1 (NR2E1) is expressed in human fetal and adult brains; however, its role in human brain-behavior development is unknown. Previously, we have corrected the cortical hypoplasia and behavioral abnormalities in Nr2e1(-/-) mice using a genomic clone spanning human NR2E1, which bolsters the hypothesis that NR2E1 may similarly play a role in human cortical and behavioral development. To test the hypothesis that humans with abnormal brain-behavior development may have null or hypomorphic NR2E1 mutations, we undertook the first candidate mutation screen of NR2E1 by sequencing its entire coding region, untranslated, splice site, proximal promoter and evolutionarily conserved non-coding regions in 56 unrelated patients with cortical disorders, namely microcephaly. We then genotyped the candidate mutations in 325 unrelated control subjects and 15 relatives. We did not detect any coding region changes in NR2E1; however, we identified seven novel candidate regulatory mutations that were absent from control subjects. We used in silico tools to predict the effects of these candidate mutations on neural transcription factor binding sites (TFBS). Four candidate mutations were predicted to alter TFBS. To facilitate the present and future studies of NR2E1, we also elucidated its molecular evolution, genetic diversity, haplotype structure and linkage disequilibrium by sequencing an additional 94 unaffected humans representing Africa, the Americas, Asia, Europe, the Middle East and Oceania, as well as great apes and monkeys. We detected strong purifying selection, low genetic diversity, 21 novel polymorphisms and five common haplotypes at NR2E1. We conclude that protein-coding changes in NR2E1 do not contribute to cortical and behavioral abnormalities in the patients examined here, but that regulatory mutations may play a role.
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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".