The loose evolutionary relationships between transcription factors and other gene products across prokaryotes
Bibliographic record
Abstract
BACKGROUND: Tests for the evolutionary conservation of associations between genes coding for transcription factors (TFs) and other genes have been limited to a few model organisms due to the lack of experimental information of functional associations in other organisms. We aimed at surmounting this limitation by using the most co-occurring gene pairs as proxies for the most conserved functional interactions available for each gene in a genome. We then used genes predicted to code for TFs to compare their most conserved interactions against the most conserved interactions for the rest of the genes within each prokaryotic genome available. RESULTS: We plotted profiles of phylogenetic profiles, p-cubic, to compare the maximally scoring interactions of TFs against those of other genes. In most prokaryotes, genes coding for TFs showed lower co-occurrences when compared to other genes. We also show that genes coding for TFs tend to have lower Codon Adaptation Indexes compared to other genes. CONCLUSIONS: The co-occurrence tests suggest that transcriptional regulation evolves quickly in most, if not all, prokaryotes. The Codon Adaptation Index analyses suggest quick gene exchange and rewiring of transcriptional regulation across prokaryotes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 teacher head, 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".