Notch1 Phase Separation Coupled Percolation facilitates target gene expression and enhancer looping
Bibliographic record
Abstract
The Notch receptor is a pleiotropic signaling protein that translates intercellular ligand interactions into changes in gene expression via the nuclear localization of the Notch intracellular Domain (NICD). Using a combination of immunohistochemistry, RNA in situ, Optogenetics and super-resolution live imaging of transcription in human cells, we show that the N1ICD can form condensates that positively facilitate Notch target gene expression. We determined that N1ICD undergoes Phase Separation Coupled Percolation (PSCP) into transcriptional condensates, which recruit, enrich, and encapsulate a broad set of core transcriptional proteins. We show that the capacity for condensation is due to the intrinsically disordered transcriptional activation domain of the N1ICD. In addition, the formation of such transcriptional condensates acts to promote Notch-mediated super enhancer-looping and concomitant activation of the MYC protooncogene expression. Overall, we introduce a novel mechanism of Notch1 activity in which discrete changes in nuclear N1ICD abundance are translated into the assembly of transcriptional condensates that facilitate gene expression by enriching essential transcriptional machineries at target genomic loci.
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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 | 0.000 |
| 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".