Scaling the Drosophila Wing: TOR-Dependent Target Gene Access by the Hippo Pathway Transducer Yorkie
Bibliographic record
Abstract
Organ growth is controlled by patterning signals that operate locally (e.g., Wingless/Ints [Wnts], Bone Morphogenetic Proteins [BMPs], and Hedgehogs [Hhs]) and scaled by nutrient-dependent signals that act systemically (e.g., Insulin-like peptides [ILPs] transduced by the Target of Rapamycin [TOR] pathway). How cells integrate these distinct inputs to generate organs of the appropriate size and shape is largely unknown. The transcriptional coactivator Yorkie (Yki, a YES-Associated Protein, or YAP) acts downstream of patterning morphogens and other tissue-intrinsic signals to promote organ growth. Yki activity is regulated primarily by the Warts/Hippo (Wts/Hpo) tumour suppressor pathway, which impedes nuclear access of Yki by a cytoplasmic tethering mechanism. Here, we show that the TOR pathway regulates Yki by a separate and novel mechanism in the Drosophila wing. Instead of controlling Yki nuclear access, TOR signaling governs Yki action after it reaches the nucleus by allowing it to gain access to its target genes. When TOR activity is inhibited, Yki accumulates in the nucleus but is sequestered from its normal growth-promoting target genes--a phenomenon we term "nuclear seclusion." Hence, we posit that in addition to its well-known role in stimulating cellular metabolism in response to nutrients, TOR also promotes wing growth by liberating Yki from nuclear seclusion, a parallel pathway that we propose contributes to the scaling of wing size with nutrient availability.
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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) | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".