Biochemical characterization of Yin Yang 1 – RNA complexes
Bibliographic record
Abstract
YY1 (Yin Yang 1) is present in the Xenopus oocyte cytoplasm as a constituent of messenger ribonucleoprotein complexes (mRNPs). Association of YY1 with mRNPs requires direct RNA-binding activity. Previously, we have shown YY1 has a high affinity for U-rich RNA; however, potential interactions with plausible in vivo targets have not been investigated. Here we report a biochemical characterization of the YY1-RNA interaction including an investigation of the stability, potential 5'-methylguanosine affinity, and specificity for target RNAs. The formation of YY1-RNA complexes in vitro was highly resistant to thermal, ionic, and detergent disruption. The endogenous oocyte YY1-mRNA interactions were also found to be highly stable. Specific YY1-RNA interactions were observed with selected mRNA and 5S RNA probes. The affinity of YY1 for these substrates was within an order of magnitude of that for its cognate DNA element. Experiments aimed at determining the potential role of the 7-methylguanosine cap on RNA-binding reveal no significant difference in the affinity of YY1 for capped or uncapped mRNA. Taken together, the results show that the YY1-RNA interaction is highly stable, and that YY1 possesses the ability to interact with structurally divergent RNA substrates. These data are the first to specifically document the interaction between YY1 and potential in vivo targets.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".