Direct phylogenetic evidence for lateral transfer of elongation factor-like gene
Bibliographic record
Abstract
Genes encoding elongation factor-like (EFL) proteins, which show high similarity to elongation factor-1alpha (EF-1alpha), have been found in phylogenetically distantly related eukaryotes. The sporadic distribution of "EFL-containing" lineages within "EF-1alpha-containing" lineages indirectly, but strongly, suggests lateral gene transfer as the principal driving force in EFL evolution. However, one of the most critical aspects in the above hypothesis, the donor lineages in any putative cases of lateral EFL gene transfer, remained unclear. In this study, we provide direct evidence for lateral transfer of an EFL gene through the analyses of 10 diatom EFL genes. All diatom EFL homologues tightly clustered in phylogenetic analyses, suggesting acquisition of the exogenous EFL gene early in diatom evolution. Our survey additionally identified Thalassiosira pseudonana as a eukaryote bearing EF-1alpha and EFL genes and secondary EFL gene loss in Phaeodactylum tricornutum, the complete genome of which encodes only the EF-1alpha gene. Most importantly, the EFL phylogeny recovered a robust grouping of homologues from diatoms, the cercozoan Bigelowiella natans, and the foraminifer Planoglabratella opecularis, with the diatoms nested within the Bigelowiella plus Planoglabratella (Rhizaria) grouping. The particular relationships recovered are further consistent with two characteristic sequence motifs. The best explanation of our data analyses is an EFL gene transfer from a foraminifer to a diatom, the first case in which the donor-recipient relationship was clarified. Finally, based on a reverse transcriptase quantitative PCR assay and the genome information of Thalassiosira and Phaeodactylum, we propose the loss of elongation factor function in Thalassiosira EF-1alpha.
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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 | 0.001 | 0.001 |
| 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".