Dissecting Molecular Evolution in the Highly Diverse Plant Clade Caryophyllales Using Transcriptome Sequencing
Bibliographic record
Abstract
Many phylogenomic studies based on transcriptomes have been limited to "single-copy" genes due to methodological challenges in homology and orthology inferences. Only a relatively small number of studies have explored analyses beyond reconstructing species relationships. We sampled 69 transcriptomes in the hyperdiverse plant clade Caryophyllales and 27 outgroups from annotated genomes across eudicots. Using a combined similarity- and phylogenetic tree-based approach, we recovered 10,960 homolog groups, where each was represented by at least eight ingroup taxa. By decomposing these homolog trees, and taking gene duplications into account, we obtained 17,273 ortholog groups, where each was represented by at least ten ingroup taxa. We reconstructed the species phylogeny using a 1,122-gene data set with a gene occupancy of 92.1%. From the homolog trees, we found that both synonymous and nonsynonymous substitution rates in herbaceous lineages are up to three times as fast as in their woody relatives. This is the first time such a pattern has been shown across thousands of nuclear genes with dense taxon sampling. We also pinpointed regions of the Caryophyllales tree that were characterized by relatively high frequencies of gene duplication, including three previously unrecognized whole-genome duplications. By further combining information from homolog tree topology and synonymous distance between paralog pairs, phylogenetic locations for 13 putative genome duplication events were identified. Genes that experienced the greatest gene family expansion were concentrated among those involved in signal transduction and oxidoreduction, including a cytochrome P450 gene that encodes a key enzyme in the betalain synthesis pathway. Our approach demonstrates a new approach for functional phylogenomic analysis in nonmodel species that is based on homolog groups in addition to inferred ortholog groups.
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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 | 0.001 | 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 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".