Rapid Dopaminergic Modulation of the Fish Hypothalamic Transcriptome and Proteome
Bibliographic record
Abstract
BACKGROUND: Dopamine (DA) is a major neurotransmitter playing an important role in the regulation of vertebrate reproduction. We developed a novel method for the comparison of transcriptomic and proteomic data obtained from in vivo experiments designed to study the neuroendocrine actions of DA. METHODS AND FINDINGS: Female goldfish were injected (i.p.) with DA agonists (D1-specific; SKF 38393, or D2-specific; LY 171555) and sacrificed after 5 h. Serum LH levels were reduced by 57% and 75% by SKF 38393 and LY 171555, respectively, indicating that the treatments produced physiologically relevant responses in vivo. Bioinformatic strategies and a ray-finned fish database were established for microarray and iTRAQ proteomic analysis of the hypothalamus, revealing a total of 3088 mRNAs and 42 proteins as being differentially regulated by the treatments. Twenty one proteins and mRNAs corresponding to these proteins appeared on both lists. Many of the mRNAs and proteins affected by the treatments were grouped into the Gene Ontology categorizations of protein complex, signal transduction, response to stimulus, and regulation of cellular processes. There was a 57% and 14% directional agreement between the differentially-regulated mRNAs and proteins for SKF 38393 and LY 171555, respectively. CONCLUSIONS: The results demonstrate the applicability of advanced high-throughput genomic and proteomic analyses in an amendable well-studied teleost model species whose genome has yet to be sequenced. We demonstrate that DA rapidly regulates multiple hypothalamic pathways and processes that are also known to be involved in pathologies of the central nervous system.
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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".