Genomic analyses of phenotypic differences between native and invasive populations of diffuse knapweed (Centaurea diffusa)
Bibliographic record
Abstract
AbstractInvasive species represent excellent opportunities to study the evolutionary potential of traits important to success in novel environments. Although some ecologically-important traits have been identified in invasive species, little is typically known about the genetic mechanisms that underlie invasion success in non-model species. Here, we use a genome-wide association (GWAS) approach to identify the genetic basis of trait variation in the non-model, invasive, diffuse knapweed (Centaurea diffusa Lam. [Asteraceae]). To assist with this analysis, we have assembled the first draft genome reference and fully annotated plastome assembly for this species, and the one of the first from this large, weedy, genus, which is of major ecological and economic importance. We collected phenotype data from 372 individuals from four native and four invasive populations of C. diffusa grown in a common environment. Using these individuals, we produced reduced-representation genotype-by-sequencing (GBS) libraries and identified 7058 SNPs. We identify two SNPs associated with leaf width in these populations, a trait which significantly varies between native and invasive populations. In this rosette forming species, increased leaf width is a major component of increased biomass, a common trait in invasive plants correlated with increased fitness. Finally, we use annotations from Arabidopsis thaliana to identify 98 candidate genes that are near the associated SNPs and highlight several good candidates for leaf width variation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 teacher head, 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".