TIN2 Binds TRF1 and TRF2 Simultaneously and Stabilizes the TRF2 Complex on Telomeres
Bibliographic record
Abstract
Human telomeres contain two related telomeric DNA-binding proteins, TRF1 and TRF2. The TRF1 complex contains the TRF1 interacting partner, TIN2, as well as PIP1 and POT1 and regulates telomere-length homeostasis. The TRF2 complex is primarily involved in telomere protection and contains the TRF2 interacting partner human (h)Rap1 as well as several factors involved in the DNA damage response. A prior report showed that conditional deletion of murine TRF1 reduced the presence of TRF2 on telomeres. Here we showed that TRF2 is also lost from human telomeres upon TRF1 depletion with small interfering RNA prompting a search for the connection between the TRF1 and TRF2 complexes. Using mass spectrometry and co-immunoprecipitation, we found that TRF1, TIN2, PIP1, and POT1 are associated with the TRF2-hRap1 complex. Gel filtration identified a TRF2 complex containing TIN2 and POT1 but not TRF1 indicating that TRF1 is not required for this interaction. Co-immunoprecipitation, Far-Western assays, and two-hybrid assays showed that TIN2, but not POT1 or PIP1, interacts directly with TRF2. Furthermore, TIN2 was found to bind TRF1 and TRF2 simultaneously, showing that TIN2 can link these telomeric proteins. This connection appeared to stabilize TRF2 on the telomeres as the treatment of cells with TIN2 small interfering RNA resulted in a decreased presence of TRF2 and hRap1 at chromosome ends. The TIN2-mediated cooperative binding of TRF1 and TRF2 to telomeres has important implications for the mechanism of telomere length regulation and protection.
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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) | 0.002 | 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".