ArticleGenetics, selection, evolution : GSE2026
Impact of genomic selection for disease resistance on the spread of infection in a simulated aquaculture population.
Article in Genetics, selection, evolution : GSE, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundIn aquaculture, selection for disease resistance is typically based on mortality records from challenge tests performed on relatives of selection candidates. However, commercial success depends on limiting disease transmission, particularly the incidence and severity of outbreaks. It remains unclear whether selecting for lower mortality also reduces disease transmission. Both these outcomes are influenced by three underlying epidemiological host traits: susceptibility, infectivity, and infection-induced mortality. This simulation study evaluated the impact of genomic selection against mortality on disease transmission in a salmon population exposed to a pathogen with a fast transmission rate.
methodsMortality was assumed to be recorded on sibs of selection candidate, either as binary dead/alive status or as time to death during cohabitation/bath challenge tests. Phenotypes were simulated using a stochastic compartmental Susceptible-Infected-Removed epidemiological model, with genetic variation for the three underlying traits. Scenarios were explored by varying the genetic correlations between the three underlying traits. Challenge test designs varied in the number of groups, group sizes, and family distribution across groups. For comparison, a reference scenario with direct selection on the underlying traits was included. Genomic selection was applied over 10 discrete generations, and its impact on disease transmission was assessed using the basic reproductive ratio (R
resultsWhen selection was based on dead/alive status, R
conclusionsGenomic selection for disease resistance, when measured as time to death in cohabitation or bath challenge tests conducted until mortality naturally levels off, reduces both mortality and disease spread. Breeding programs may benefit from challenge test designs that enable estimation of genetic parameters for the underlying traits affecting disease transmission and survival.
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