The role of structural pleiotropy and regulatory evolution in the retention of heteromers of paralogs
Bibliographic record
Abstract
Abstract Many paralogs derive from the duplication of genes encoding homomeric proteins. Such duplication events lead to the formation of homomers and heteromers, thus creating new structures from a single event. We exhaustively characterize this phenomenon using the budding yeast protein-protein interaction network. We observe that paralogs that heteromerize are very frequent and less functionally diverged than those that lost this property, raising the possibility that heteromerization prevents functional divergence. Using in silico evolution, we show that for homomers and heteromers that share binding interfaces, mutations on one complex have pleiotropic effects on the other complex, resulting in highly correlated responses to selection. As a result, heteromerization could be preserved indirectly due to selection for the maintenance of homomers. By integrating data on gene expression and protein localization, we find that regulatory evolution could play a role in overcoming these structural pleiotropic effects and in allowing paralog functional divergence.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".