Hepatic Transcriptomic Responses to Ethinylestradiol in Embryonic Japanese Quail and Double-Crested Cormorant
Bibliographic record
Abstract
Understanding species differences in sensitivity to toxicants is a critical issue in ecotoxicology. We recently established that double-crested cormorant (DCCO) embryos are more sensitive than Japanese quail (JQ) to the developmental effects of ethinylestradiol (EE2). We explored how this difference in sensitivity between species is reflected at a transcriptomic level. The EE2 was dissolved in dimethyl sulfoxide and injected into the air cell of eggs prior to incubation at nominal concentrations of 0, 3.33, and 33.3 µg/g egg weight. At midincubation (JQ 9 days; DCCO 16 days), livers were collected from five embryos/treatment group for RNA sequencing. Data were processed and analyzed using EcoOmicsAnalyst and ExpressAnalyst. The EE2 exposure dysregulated 238 and 1,987 genes in JQ and DCCO, respectively, with 78 genes in common between the two species. These included classic biomarkers of estrogen exposure such as vitellogenin and apovitellenin. We also report DCCO-specific dysregulation of Phase I/II enzyme-coding genes and species-specific transcriptional ontogeny of vitellogenin-2. Twelve Kyoto Encyclopedia of Genes and Genomes pathways and two EcoToxModules were dysregulated in common in both species including the peroxisome proliferator-activated receptor (PPAR) signaling pathway and fatty acid metabolism. Similar to previously reported differences at the organismal level, DCCO were more responsive to EE2 exposure than JQ at the gene expression level. Our description of differences in transcriptional responses to EE2 in early life stage birds may contribute to a better understanding of the molecular basis for species differences. Environ Toxicol Chem 2024;43:772-783. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.
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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) | 0.001 | 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".