Organellar data sets confirm overall angiosperm relationships if problematic RNA-edit sites are accounted for in mitochondrial genomes
Bibliographic record
Abstract
Premise Plastid-based data sets continue to play a major role in our understanding of early flowering-plant relationships, although organellar genomes of major lineages outside the monocots and eudicots remain under-sampled. A tendency of mitochondrial RNA-edit sites to mislead phylogenetic analysis in mixed transcriptomic/genomic data sets needs attention in angiosperm-wide studies, which only rarely consider mitochondrial genomes. Methods We compared mitochondrial- vs. plastid-based phylogenomic inferences, examined the effect of removing putative RNA-edit sites from mitochondrial data, and performed combined organellar analysis (plastid plus filtered mitochondrial genomes). We expanded taxon sampling for multiple angiosperm lineages for phylogenomic analysis using both organellar genomes, representing several poorly sampled lineages (in particular Degeneriaceae, Trimeniaceae) with smaller (few-gene) data sets. Results Plastid-based inferences recover well-supported relationships that align with and build upon previous studies, and recover well-supported internal relationships for two ANA-grade families (Hydatellaceae, Trimeniaceae) sampled for nearly all species. By contrast, unfiltered mitochondrial inferences of angiosperm phylogeny are generally poorly supported, and recover anomalous relationships compared to plastid-based inferences. However, removing putative mitochondrial RNA-edit sites dramatically reduces inter-organellar conflict and improves overall branch support. Conclusions We accounted for phylogenomic discordance between the two organellar genomes regarding overall angiosperm-wide relationships and filled in taxonomic gaps (poorly sampled lineages). Removing RNA edit sites substantially improves congruence in interorganellar inferences by effectively correcting a systematic bias in mitochondrial data. Uncertain relationships persist among five major mesangiosperm lineages in plastid-based inferences, but a clade comprising Chloranthales, Ceratophyllales and eudicots is well supported by filtered mitochondrial data.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".