Variant functional assessment in <i>Drosophila</i> by overexpression: what can we learn?
Bibliographic record
Abstract
The last decade has been highlighted by the increased use of next-generation DNA sequencing technology to identify novel human disease genes. A critical downstream part of this process is assigning function to a candidate gene variant. Functional studies in Drosophila melanogaster, the common fruit fly, have made a prominent contribution in annotating variant impact in an in vivo system. The use of patient-derived knock-in flies or rescue-based, “humanization”, approaches are novel and valuable strategies in variant testing but have been recently widely reviewed. An often-overlooked strategy for determining variant impact has been GAL4/upstream activation sequence-mediated tissue-defined overexpression in Drosophila. This mini-review will summarize the recent contribution of ectopic overexpression of human reference and variant cDNA in Drosophila to assess variant function, interpret the consequence of the variant, and in some cases infer biological mechanisms.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".