A Broadscale Phylogenetic Analysis of Group II Intron RNAs and Intron-Encoded Reverse Transcriptases
Bibliographic record
Abstract
Group II introns are self-splicing RNAs that are frequently assumed to be the ancestors of spliceosomal introns. They are widely distributed in bacteria and are also found in organelles of plants, fungi, and protists. In this study, we present a broadscale phylogenetic analysis of group II introns using sequence data from both the conserved RNA structure and the intron-encoded reverse transcriptase (RT). Two similar phylogenies are estimated for the RT open reading frame (ORF), based on either amino acid or nucleotide sequence, whereas one phylogeny is produced for the RNA. In making these estimates, we confronted nearly all the classic challenges to phylogenetic inference, including positional saturation, base composition heterogeneity, short internodes with low support, and sensitivity to taxon sampling. Although the major lineages are well-defined, robust resolution of topology is not possible between these lineages. The approximately unbiased (AU) and Shimodaira-Hasegawa topology tests indicated that the RT ORF and RNA ribozyme data sets are in significant conflict under a variety of models, revealing the possibility of imperfect coevolution between group II introns and their intron-encoded ORFs. The high level of sequence divergence, large timescale, and limited number of alignable characters in our study are representative of many RTs and group I introns, and our results suggest that phylogenetic analyses of any of these sequences could suffer from the same sources of error and instability identified in this study.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".