Epigenetic responses to oil exposure in wild Arctic seabird populations
Bibliographic record
Abstract
Anthropogenic pollution has been shown to have detrimental effects on organismal physiology, behavior, and fitness, but the underlying genomic mechanisms mediating these effects are not well understood.Epigenetic regulation, such as DNA methylation, has been proposed as a potential mechanism mediating these effects but currently there are few studies in natural populations.Here, I examined the methylation patterns of liver tissues from black guillemot (Cepphus grylle) in regions in the Canadian Arctic with different histories of exposure to polycyclic aromatic compounds (PACs).When compared to a reference site, I observed that all three sites with PACs exposure share a core set of differentially methylated regions (DMRs), implying that there are some consistent methylation responses to these compounds.However, the two sites with shortterm exposure to anthropogenic sources of PACs shared more DMRs than they did with the site experiencing chronic exposure to natural PACs.Furthermore, I found that when compared to a reference site with very low PACs exposure, populations that have been exposed to anthropogenic PACs are characterized by having DMRs with significantly greater ratios of hypermethylated to hypomethylated versus the population experiencing chronic exposure to natural PACs.Taken together, these results imply that the specific composition and exposure length of PACs might influence the direction of the epigenetic response.This study provides novel insights into the epigenetic mechanisms underlying biological responses to anthropogenic oil pollution.The identified DMRs serve as a genomic resource for further research investigating the functional role of DNA methylation in response to anthropogenic oil pollution.I am extremely grateful to my supervisor, Dr. Rowan Barrett, for giving me the invaluable opportunity to pursue graduate studies.Throughout the process, I have appreciated the level of autonomy he provided me in working on my thesis, as well as his insightful guidance whenever I needed it.Thank you also to Dr. Jennifer Provencher and Dr. Kyle Elliott for serving as members of my supervisory committee, providing me valuable advice and feedback through their expertise
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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 | 0.000 | 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) | 0.002 | 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".