Genome-wide screen for modifiers of Parkinson's disease genes in Drosophila
Bibliographic record
Abstract
BACKGROUND: Mutations in parkin and PTEN-induced kinase 1 (Pink1) lead to autosomal recessive forms of Parkinson's disease (PD). parkin and Pink1 encode a ubiquitin-protein ligase and a mitochondrially localized serine/threonine kinase, respectively. Recent studies have implicated Parkin and Pink1 in a common and evolutionarily conserved pathway for protecting mitochondrial integrity. RESULTS: To systematically identify novel components of the PD pathways, we generated a genetic background that allowed us to perform a genome-wide F1 screen for modifiers of Drosophila parkin (park) and Pink1 mutant phenotype. From screening ~80% of the fly genome, we identified a number of cytological regions that interact with park and/or Pink1. Among them, four cytological regions were selected for identifying corresponding PD-interacting genes. By analyzing smaller deficiency chromosomes, available transgenic RNAi lines, and P-element insertions, we identified five PD-interacting genes. Among them, opa1 and drp1 have been previously implicated in the PD pathways, whereas debra (dbr), Pi3K21B and β4GalNAcTA are novel PD-interacting genes. CONCLUSIONS: We took an unbiased genetic approach to systematically isolate modifiers of PD genes in Drosophila. Further study of novel PD-interacting genes will shed new light on the function of PD genes and help in the development of new therapeutic strategies for treating Parkinson's 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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".