The genomic basis of the plant island syndrome in Darwin’s giant daisies
Bibliographic record
Abstract
Abstract Oceanic archipelagos comprise multiple disparate environments over small geographic areas and are isolated from other biotas. These conditions have led to some of the most spectacular adaptive radiations, which have been key to our understanding of evolution, and offer a unique chance to characterise the genomic basis underlying rapid and pronounced phenotypic changes. Repeated patterns of evolutionary change in plants on oceanic archipelagos, i.e. the plant island syndrome, include changes in leaf morphology, acquisition of perennial life-style, and change of ploidy. Here, we describe the genome of the critically endangered and Galápagos endemic Scalesia atractyloides Arnot., obtaining a chromosome-resolved 3.2-Gbp assembly with 43,093 candidate gene models. Using a combination of fossil transposable elements, k -mer spectra analyses and orthologue assignment, we identify the two ancestral subgenomes and date their divergence and the polyploidization event, concluding that the ancestor of all Scalesia species on the Galápagos was an allotetraploid. There are a comparable number of genes and transposable elements across the two subgenomes, and while their synteny has been mostly conserved, we find multiple inversions that may have facilitated adaptation. We identify clear signatures of selection across genes associated with vascular development, life-growth, adaptation to salinity and changes in flowering time, thus finding compelling evidence for a genomic basis of island syndrome in Darwin’s giant daisy radiation. This work advances understanding of factors influencing subgenome divergence in polyploid genomes, and characterizes the quick and pronounced genomic changes in a specular and diverse radiation of an iconic island plant radiation.
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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 | 0.000 | 0.000 |
| 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".