Behavioral transcriptomic effects of triploidy and probiotic therapy (<i>Bifidobacterium</i>, <i>Lactobacillus</i>, and <i>Lactococcus</i> mixture) on juvenile Chinook salmon (<i>Oncorhynchus tshawytscha</i>)
Bibliographic record
Abstract
Aquaculturists use polyploid fish to maximize production albeit with some unintended consequences including compromised behaviors and physiological function. Given benefits of probiotic therapies (e.g., improved immune response, growth, and metabolism), we explored probiotic supplementation (mixture of Bifidobacterium, Lactobacillus, and Lactococcus), to overcome drawbacks. We first examined fish gut bacterial community composition using 16S metabarcoding (via principal coordinate analyses and PERMANOVA) and determined probiotics significantly impacted gut bacteria composition (p = 0.001). Secondly, we examined how a genomic disruptor (triploidy) and diet supplements (probiotics) impact gene transcription and behavioral profiles of hatchery-reared Chinook salmon (Oncorhynchus tshawytscha). Juveniles from four treatment groups (diploid-regular feed, diploid-probiotic feed, triploid-regular feed, and triploid-probiotic feed; n = 360) underwent behavioral assays to test activity, exploration, neophobia, predator evasion, aggression/sociality, behavioral sensitivity, and flexibility. In these fish, transcriptional profiles for genes associated with neural functions (neurogenesis/synaptic plasticity) and biomarkers for stress response and development (growth/appetite) were (i) examined across treatments and (ii) used to describe behavioral phenotypes via principal component analyses and general linear mixed models. Triploids exhibited a more active behavioral profile (p = 0.002), and those on a regular diet had greater Neuropeptide Y transcription (p = 0.02). A growth gene (early growth response protein 1, p = 0.02) and long-term neural development genes (neurogenic differentiation factor, p = 0.003 and synaptysomal-associated protein 25-a, p = 0.005) impacted activity and reactionary profiles, respectively. Overall, our probiotic treatment did not compensate for triploidy. Our research highlights novel applications of behavioral transcriptomics for identifying candidate genes and dynamic, mechanistic associations with complex behavioral repertoires.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".