Mapping Quantitative Trait Loci Affecting Variation in <i>Drosophila</i> Triacylglycerol Storage
Bibliographic record
Abstract
OBJECTIVE: Recent genetic studies indicate that Drosophila melanogaster could be a powerful model to identify genes involved in mammalian adipocyte differentiation and fat storage. The objective of our study was to identify quantitative trait loci (QTLs) that contribute to variation in triacylglycerol (TAG) storage in two D. melanogaster laboratory strains. RESEARCH METHODS AND PROCEDURES: We used two genetic mapping procedures to identify loci with main and epistatic effects on TAG storage. First, using 68 recombinant inbred lines derived from the unrelated Oregon R and Russian 2b strains, we mapped the location of QTLs affecting TAG storage using both composite interval mapping and Bayesian epistatic methods. Second, we used the quantitative deficiency mapping procedure to identify candidate genes affecting this trait within one of the QTLs identified on the second chromosome. For both mapping experiments, flies were cultured in standard conditions. TAG content of 4- to 5-day-old flies, adjusted for live body mass and total proteins, was used as the phenotypic measure. RESULTS: Multiple QTLs associated with variation in TAG storage were identified by the genome-wide recombination mapping method, and some of them were sex-specific. The QTLs had main effects, but a male-specific epistatic interaction between two QTLs was also found. Finally, two closely linked QTLs were detected by deficiency mapping at 57E1-57E3 and 57E4-57F1 on chromosome 2, the first of which causes female-specific variation in TAG between the Oregon R and 2b strains. DISCUSSION: Our results suggest that variation in TAG storage in D. melanogaster is controlled by different genetic mechanisms and different sets of QTLs in male and female flies.
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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".