Impact of genomic selection for disease resistance on the spread of infection in a simulated aquaculture population
Silvia García-Ballesteros, Jesús Fernández, Andrea B Doeschl-Wilson, Beatriz Villanueva · 2026
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Description
Four authors use computer simulation to ask whether breeding fish for disease survival also slows the spread of infection. In aquaculture, selection usually relies on mortality records from challenge tests on relatives of the breeding candidates. Yet farms care about outbreaks, not only deaths. Survival also rests on three hidden traits: how easily a fish catches the disease, how strongly it passes it on, and how likely infection is to kill it. The team modeled a salmon population facing a fast-spreading pathogen.
They applied genomic selection over ten generations and tracked the basic reproductive ratio, which measures spread. Selecting on simple dead-or-alive records gave mixed results that hinged on how the hidden traits correlate. Selecting on time to death lowered spread in every scenario, often below the level where outbreaks sustain themselves.
Catalog record
| CREATOR | Silvia García-Ballesteros, Jesús Fernández, Andrea B Doeschl-Wilson, Beatriz Villanueva |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 74 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |