Epigenetics and island‐mainland divergence in an insectivorous small mammal
Bibliographic record
Abstract
Geographically isolated populations, specifically island-mainland counterparts, tend to exhibit phenotypic variation in many species. The so-called island syndrome occurs when different environmental pressures lead to insular divergence from mainland populations. This phenomenon can be seen in an island population of Nova Scotia masked shrews (Sorex cinereus), which have developed a specialized feeding habit and digestive enzyme compared to their mainland counterparts. Epigenetic modifications, such as DNA methylation (DNAm), can impact phenotypes by altering gene expression without changing the DNA sequence. Here, we used a de novo masked shrew genome assembly and a mammalian methylation array profiling 37 thousand conserved CpGs to investigate morphological and DNA methylation patterns between island and mainland populations. Island shrews were morphologically and epigenetically different than their mainland counterparts, exhibiting a smaller body size. A gene ontology enrichment analyses of differentially methylated CpGs implicated developmental and digestive system related pathways. Based on our shrew epigenetic clock, island shrews might also be aging faster than their mainland counterparts. This study provides novel insight on phenotypic and epigenetic divergence in island-mainland mammal populations and suggests an underlying role of methylation in island-mainland divergence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.001 | 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".