Functional replacement of a primary metabolic pathway via multiple independent eukaryote‐to‐eukaryote gene transfers and selective retention
Bibliographic record
Abstract
Although lateral gene transfer (LGT) is now recognized as a major force in the evolution of prokaryotes, the contribution of LGT to the evolution and diversification of eukaryotes is less understood. Notably, transfers of complete pathways are believed to be less likely between eukaryotes, because the successful transfer of a pathway requires the physical clustering of functionally related genes. Here, we report that in one of the closest unicellular relatives of animals, the choanoflagellate, Monosiga, three genes whose products work together in the glutamate synthase cycle are of algal origin. The concerted retention of these three independently acquired genes is best explained as the consequence of a series of adaptive replacement events. More generally, this study argues that (i) eukaryote-to-eukaryote transfers of entire metabolic pathways are possible, (ii) adaptive functional replacements of primary pathways can occur, and (iii) functional replacements involving eukaryotic genes are likely to have also contributed to the evolution of eukaryotes. Lastly, these data underscore the potential contribution of algal genes to the evolution of nonphotosynthetic lineages.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".