Molecular Evolution across the Asteraceae: Micro- and Macroevolutionary Processes
Bibliographic record
Abstract
The Asteraceae (Compositae) is a large family of over 20,000 wild, weedy, and domesticated species that comprise approximately 10% of all angiosperms, including annual and perennial herbs, shrubs and trees, and species on every continent except Antarctica. As a result, the Asteraceae provide a unique opportunity to understand the evolutionary genomics of lineage radiation and diversification at numerous phylogenetic scales. Using publicly available expressed sequence tags from 22 species representing four of the major Asteraceae lineages, we assessed neutral and nonneutral evolutionary processes across this diverse plant family. We used bioinformatic tools to identify candidate genes under selection in each species. Evolution at silent and coding sites were assessed for different Gene Ontology functional categories to compare rates of evolution over both short and long evolutionary timescales. Our results indicate that patterns of molecular change across the family are surprisingly consistent on a macroevolutionary timescale and much more so more than would be predicted from the analysis of one (or many) examples of microevolution. These analyses also point to particular classes of genes that may be crucial in shaping the radiation of this diverse plant family. Similar analyses of nuclear and chloroplast genes in six other plant families confirm that many of these patterns are common features of the plant kingdom.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".