(Epi)genomic adaptation driven by fine geographical scale environmental heterogeneity after recent biological invasions
Bibliographic record
Abstract
Elucidating processes and mechanisms involved in rapid local adaptation to varied environments is a poorly understood but crucial component in management of invasive species. Recent studies have proposed that genetic and epigenetic variation could both contribute to ecological adaptation, yet it remains unclear on the interplay between these two components underpinning rapid adaptation in wild animal populations. To assess their respective contributions to local adaptation, we explored epigenomic and genomic responses to environmental heterogeneity in eight recently colonized ascidian (Ciona intestinalis) populations at a relatively fine geographical scale. Based on MethylRADseq data, we detected strong patterns of local environment-driven DNA methylation divergence among populations, significant epigenetic isolation by environment (IBE), and a large number of local environment-associated epigenetic loci. Meanwhile, multiple genetic analyses based on single nucleotide polymorphisms (SNPs) showed genomic footprints of divergent selection. In addition, for five genetically similar populations, we detected significant methylation divergence and local environment-driven methylation patterns, indicating the strong effects of local environments on epigenetic variation. From a functional perspective, a majority of functional genes, Gene Ontology (GO) terms, and biological pathways were largely specific to one of these two types of variation, suggesting partial independence between epigenetic and genetic adaptation. The methylation quantitative trait loci (mQTL) analysis showed that the genetic variation explained only 18.67% of methylation variation, further confirming the autonomous relationship between these two types of variation. Altogether, we highlight the complementary interplay of genetic and epigenetic variation involved in local adaptation, which may jointly promote populations' rapid adaptive capacity and successful invasions in different environments. The findings here provide valuable insights into interactions between invaders and local environments to allow invasive species to rapidly spread, thus contributing to better prediction of invasion success and development of management strategies.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.097 | 0.001 |
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; both teacher heads agree on what is shown here.
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".