Reconstructing the history of a WD40 beta-propeller tandem repeat using a phylogenetically informed algorithm
Bibliographic record
Abstract
Tandem repeat sequences have been found in great numbers in proteins that are conserved in a wide range of living species. In order to reconstruct the evolutionary history of such sequences, it is necessary to develop algorithms and methods that can work with highly divergent motifs. Here we propose a reconstruction algorithm that uses, in parallel, ortholog tandem repeat sequences from n species whose phylogeny is known, allowing it to distinguish mutations that occurred before and after the first speciation. At each step of the reconstruction, both the boundaries and the length of the duplicated segment are recalculated, making the approach suitable for sequences for which the fixed boundary hypothesis may not hold. We use this algorithm to reconstruct a 4-bladed ancestor of the 7-bladed WD40 beta-propeller, using orthologs of the GNB1 human protein in plants, yeasts, nematodes, insects and fishes. The results obtained for the WD40 repeats are very encouraging, as the noise in the duplication reconstruction is significantly reduced.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".