ArticleGenetics, selection, evolution : GSE2017
A model to estimate effects of SNPs on host susceptibility and infectivity for an endemic infectious disease.
Article in Genetics, selection, evolution : GSE, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- SIRE 2.0: a novel method for estimating polygenic host effects underlying infectious disease transmission, and analytical expressions for prediction accuracies.Genetics, selection, evolution : GSE · 2025Article
- Optimal experimental designs for estimating genetic and non-genetic effects underlying infectious disease transmission.Genetics, selection, evolution : GSE · 2022Article
- Review: Livestock disease resilience: from individual to herd level.Animal : an international journal of animal bioscience · 2021Review
- Why genetic selection to reduce the prevalence of infectious diseases is way more promising than currently believed.Genetics · 2021Article
- Estimating individuals' genetic and non-genetic effects underlying infectious disease transmission from temporal epidemic data.PLoS computational biology · 2020Article
- The economic value of RGenetics, selection, evolution : GSE · 2020Article
- Prospects for the Analysis and Reduction of Damaging Behaviour in Group-Housed Livestock, With Application to Pig Breeding.Frontiers in genetics · 2020Review
- Genetic parameters and genomic breeding values for digital dermatitis in Holstein Friesian dairy cattle: host susceptibility, infectivity and the basic reproduction ratio.Genetics, selection, evolution : GSE · 2019Article
- Enhancing genetic disease control by selecting for lower host infectivity and susceptibility.Heredity · 2019Article
- Derivation of the economic value of RGenetics, selection, evolution : GSE · 2018Article
- Can We Breed Cattle for Lower Bovine TB Infectivity?Frontiers in veterinary science · 2018Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundInfectious diseases in farm animals affect animal health, decrease animal welfare and can affect human health. Selection and breeding of host individuals with desirable traits regarding infectious diseases can help to fight disease transmission, which is affected by two types of (genetic) traits: host susceptibility and host infectivity. Quantitative genetic studies on infectious diseases generally connect an individual's disease status to its own genotype, and therefore capture genetic effects on susceptibility only. However, they usually ignore variation in exposure to infectious herd mates, which may limit the accuracy of estimates of genetic effects on susceptibility. Moreover, genetic effects on infectivity will exist as well. Thus, to design optimal breeding strategies, it is essential that genetic effects on infectivity are quantified. Given the potential importance of genetic effects on infectivity, we set out to develop a model to estimate the effect of single nucleotide polymorphisms (SNPs) on both host susceptibility and host infectivity. To evaluate the quality of the resulting SNP effect estimates, we simulated an endemic disease in 10 groups of 100 individuals, and recorded time-series data on individual disease status. We quantified bias and precision of the estimates for different sizes of SNP effects, and identified the optimum recording interval when the number of records is limited.
resultsWe present a generalized linear mixed model to estimate the effect of SNPs on both host susceptibility and host infectivity. SNP effects were on average slightly underestimated, i.e. estimates were conservative. Estimates were less precise for infectivity than for susceptibility. Given our sample size, the power to estimate SNP effects for susceptibility was 100% for differences between genotypes of a factor 1.56 or more, and was higher than 60% for infectivity for differences between genotypes of a factor 4 or more. When disease status was recorded 11 times on each animal, the optimal recording interval was 25 to 50% of the average infectious period.
conclusionsOur model was able to estimate genetic effects on susceptibility and infectivity. In future genome-wide association studies, it may serve as a starting point to identify genes that affect disease transmission and disease prevalence.
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