Editing the Melanocortin-4 Receptor Gene in Channel Catfish Using the CRISPR-Cas9 System
Bibliographic record
Abstract
The melanocortin-4 receptor (MC4R) plays a critical role in homeostasis and the regulation of body weight. Polymorphisms in the mc4r gene have been discovered and linked to growth, carcass composition, and meat quality traits. Therefore, we used the CRISPR-Cas9 system to target the mc4r gene in the most important freshwater aquaculture species in the USA, channel catfish, Ictalurus punctatus. Guide RNAs were designed to direct the Cas9 to the coding sequence of the channel catfish mc4r gene. gRNA(s)-Cas9 mixtures were delivered into one-cell embryos using electroporation and microinjection. For each treatment, the nature and rate of mutations were analyzed. Hatching and survival rates were calculated. The overall mutation rates were 30.6% and 66.7–90.6% for electroporation and microinjection, respectively. Mutated fish generated via electroporation or microinjection exhibited 38% and 20% improvement in body weight, respectively, when compared with the full-sib control. The mean feed conversion ratio of the mutants was 1.18 compared with 1.57 in the control fish. The improved growth and feed conversion indicate that the generation of mc4r-edited fish could economically benefit aquaculture production.
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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 | 0.001 |
| Research integrity | 0.001 | 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".