YAP, TAZ, and Yorkie: a conserved family of signal-responsive transcriptional coregulators in animal development and human diseaseThis paper is one of a selection of papers published in this Special Issue, entitled CSBMCB’s 51st Annual Meeting – Epigenetics and Chromatin Dynamics, and has undergone the Journal’s usual peer review process.
Bibliographic record
Abstract
How extracellular cues are transduced to the nucleus is a fundamental issue in biology. The paralogous WW-domain proteins YAP (Yes-associated protein) and TAZ (transcriptional coactivator with PDZ-binding motif; also known as WWTR1, for WW-domain containing transcription regulator 1) constitute a pair of transducers linking cytoplasmic signaling events to transcriptional regulation in the nucleus. A cascade composed of mammalian Ste20-like (MST) and large tumor suppressor (LATS) kinases directs multisite phosphorylation, promotes 14-3-3 binding, and hinders nuclear import of YAP and TAZ, thereby inhibiting their transcriptional coactivator and growth-promoting activities. A similar cascade regulates the trafficking and function of Yorkie, the fly orthologue of YAP. Mammalian YAP and TAZ are expressed in various tissues and serve as coregulators for transcriptional enhancer factors (TEFs; also referred to as TEADs, for TEA-domain proteins), runt-domain transcription factors (Runxs), peroxisome proliferator-activated receptor gamma (PPARgamma), T-box transcription factor 5 (Tbx5), and several others. YAP and TAZ play distinct roles during mouse development. Both, and their upstream regulators, are intimately linked to tumorigenesis and other pathogenic processes. Here, we review studies on this family of signal-responsive transcriptional coregulators and emphasize how relative sequence conservation predicates their function and regulation, to provide a conceptual framework for organizing available information and seeking new knowledge about these signal transducers.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".