A <i>Drosophila</i> model for Angelman syndrome
Bibliographic record
Abstract
Angelman syndrome is a neurological disorder whose symptoms include severe mental retardation, loss of motor coordination, and sleep disturbances. The disease is caused by a loss of function of UBE3A, which encodes a HECT-domain ubiquitin ligase. Here, we generate a Drosophila model for the disease. The results of several experiments show that the functions of human UBE3A and its fly counterpart, dube3a, are similar. First, expression of Dube3a is enriched in the Drosophila nervous system, including mushroom bodies, the seat of learning and memory. Second, we have generated dube3a null mutants, and they appear normal externally, but display abnormal locomotive behavior and circadian rhythms, and defective long-term memory. Third, flies that overexpress Dube3a in the nervous system also display locomotion defects, dependent on the ubiquitin ligase activity. Finally, missense mutations in UBE3A alleles of Angelman syndrome patients alter amino acid residues conserved in the fly protein, and when introduced into dube3a, behave as loss-of-function mutations. The simplest model for Angelman syndrome is that in the absence of UBE3A, particular substrates fail to be ubiquitinated and proteasomally degraded, accumulate in the brain, and interfere with brain function. We have generated flies useful for genetic screens to identify Dube3a substrates. These flies overexpress Dube3a in the eye or wing and display morphological abnormalities, dependent on the critical catalytic cysteine. We conclude that dube3a mutants are a valid model for Angelman syndrome, with great potential for identifying the elusive UBE3A substrates relevant to the disease.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".