Comparative genomics in the Asteraceae reveals little evidence for parallel evolutionary change in invasive taxa
Bibliographic record
Abstract
Asteraceae, the largest family of flowering plants, has given rise to many notorious invasive species. Using publicly available transcriptome assemblies from 35 Asteraceae, including six major invasive species, we examined evidence for micro- and macro-evolutionary genomic changes associated with invasion. To detect episodes of positive selection repeated across multiple introductions, we conducted comparisons between native and introduced genotypes from six focal species and identified genes with elevated rates of amino acid change (dN/dS). We then looked for evidence of positive selection at a broader phylogenetic scale across all taxa. As invasive species may experience founder events during colonization and spread, we also looked for evidence of increased genetic load in introduced genotypes. We rarely found evidence for parallel changes in orthologous genes in the intraspecific comparisons, but in some cases we identified changes in members of the same gene family. Using among-species comparisons, we detected positive selection in 0.003-0.69% and 2.4-7.8% of the genes using site and stochastic branch-site models, respectively. These genes had diverse putative functions, including defence response, stress response and herbicide resistance, although there was no clear pattern in the GO terms. There was no indication that introduced genotypes have a higher proportion of deleterious alleles than native genotypes in the six focal species, suggesting multiple introductions and admixture mitigated the impact of drift. Our findings provide little evidence for common genomic responses in invasive taxa of the Asteraceae and hence suggest that multiple evolutionary pathways may lead to adaptation during introduction and spread in these species.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".