The rate and potential relevance of new mutations in a colonizing plant lineage
Bibliographic record
Abstract
By following the evolution of populations that are initially genetically homogeneous, much can be learned about core biological principles. For example, it allows for detailed studies of the rate of emergence of de novo mutations and their change in frequency due to drift and selection. Unfortunately, in multicellular organisms with generation times of months or years, it is difficult to set up and carry out such experiments over many generations. An alternative is provided by "natural evolution experiments" that started from colonizations or invasions of new habitats by selfing lineages. With limited or missing gene flow from other lineages, new mutations and their effects can be easily detected. North America has been colonized in historic times by the plant Arabidopsis thaliana, and although multiple intercrossing lineages are found today, many of the individuals belong to a single lineage, HPG1. To determine in this lineage the rate of substitutions-the subset of mutations that survived natural selection and drift-, we have sequenced genomes from plants collected between 1863 and 2006. We identified 73 modern and 27 herbarium specimens that belonged to HPG1. Using the estimated substitution rate, we infer that the last common HPG1 ancestor lived in the early 17th century, when it was most likely introduced by chance from Europe. Mutations in coding regions are depleted in frequency compared to those in other portions of the genome, consistent with purifying selection. Nevertheless, a handful of mutations is found at high frequency in present-day populations. We link these to detectable phenotypic variance in traits of known ecological importance, life history and growth, which could reflect their adaptive value. Our work showcases how, by applying genomics methods to a combination of modern and historic samples from colonizing lineages, we can directly study new mutations and their potential evolutionary relevance.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".