Different mating contexts lead to extensive rewiring of female brain coexpression networks in the guppy
Bibliographic record
Abstract
Understanding the basis of behavior requires dissecting the complex waves of gene expression that underlie how the brain processes stimuli and produces an appropriate response. In order to determine the dynamic nature of the neurogenomic network underlying mate choice, we use transcriptome sequencing to capture the female neurogenomic response in two brain regions involved in sensory processing and decision-making under different mating and social contexts. We use differential coexpression (DC) analysis to evaluate how gene networks in the brain are rewired when a female evaluates attractive and nonattractive males, greatly extending current single-gene approaches to assess changes in the broader gene regulatory network. We find the brain experiences a remarkable amount of network rewiring in the different mating and social contexts we tested. Further analysis indicates the network differences across contexts are associated with behaviorally relevant functions and pathways, particularly learning, memory and other cognitive functions. Finally, we identify the loci that display social context-dependent connections, revealing the basis of how relevant neurological and metabolic pathways are differentially recruited in distinct social contexts. More broadly, our findings contribute to our understanding of the genetics of mating and social behavior by identifying gene drivers behind behavioral neural processes, illustrating the utility of DC analysis in neurosciences and behavior.
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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 | 0.000 | 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) | 0.000 | 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 teacher head, 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".