Faculty Opinions recommendation of Genetic basis and evolution of rapid cycling in railway populations of tetraploid Arabidopsis arenosa.
Bibliographic record
Abstract
Spatially structured plant populations with diverse adaptations provide powerful models to investigate evolution. Human-generated ruderal habitats are abundant and low-competition, but are challenging for plants not adapted to them. Ruderal habitats also sometimes form networked corridors (e.g. roadsides and railways) that allow rapid long-distance spread of successfully adapted variants. Here we use transcriptomic and genomic analyses, coupled with genetic mapping and transgenic follow-up, to understand the evolution of rapid cycling during adaptation to railway sites in autotetraploid Arabidopsis arenosa. We focus mostly on a hybrid population that is likely a secondary colonist of a railway site. These mountain railway plants are phenotypically similar to their cosmopolitan cousins. We thus hypothesized that colonization primarily involved the flow of adaptive alleles from the cosmopolitan railway variant. But our data shows that it is not that simple: while there is evidence of selection having acted on introgressed alleles, selection also acted on rare standing variation, and new mutations may also contribute. Among the genes we show have allelic divergence with functional relevance to flowering time are known regulators of flowering, including FLC and CONSTANS. Prior implications of these genes in weediness and rapid cycling supports the idea that these are "evolutionary hotspots" for these traits. We also find that one of two alleles of CONSTANS under selection in the secondary colonist was selected from rare standing variation in mountain populations, while the other was introgressed from the cosmopolitan railway populations. The latter allele likely arose in diploid populations over 700km away, highlighting how ruderal populations could act as allele conduits and thus influence local adaptation. PMID: 29975688 Funding information This work was supported by: Biotechnology and Biological Sciences Research Council, United Kingdom Grant ID: BB/P013511/1 Biotechnology and Biological Sciences Research Council, United Kingdom Grant ID: BBS/E/J/000PR9788 Biotechnology and Biological Sciences Research Council, United Kingdom Grant ID: BBS/E/J/000PR9773
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".