Maternal stress has divergent effects on gene expression patterns in the brains of male and female threespine stickleback
Bibliographic record
Abstract
Maternal stress can have long-term effects on neurodevelopment that can influence offspring performance and population evolutionary trajectories. To examine the mechanistic basis for these neurodevelopmental effects of maternal stress, we used RNA-seq to assess differential gene expression across the brain transcriptome of adult male and female threespine stickleback (Gasterosteus aculeatus) from stressed and unstressed mothers. We identified sexually divergent effects of maternal stress on the brain transcriptome. In males, genes that were upregulated by maternal stress were enriched for processes involved in synaptic function and organization and steroid hormone-mediated signalling pathways, whereas in females genes that were upregulated by maternal stress were enriched for processes involved in protein translation and metabolic functions. The expression of several genes involved in the hypothalamic-pituitary-interrenal response to stress and epigenetic processes such as the regulation of DNA methylation patterns and miRNAs increased in males and not in females. These data suggest that maternal stress has markedly different effects on cellular pathways in the brains of male and female offspring of mothers that are exposed to stress, which could have important implications when assessing the long-term ecological and evolutionary impacts of stress across generations.
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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".