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      Genomics and disease resistance studies in livestock.

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          Abstract

          This paper considers the application of genetic and genomic techniques to disease resistance, the interpretation of data arising from such studies and the utilisation of the research outcomes to breed animals for enhanced resistance. Resistance and tolerance are defined and contrasted, factors affecting the analysis and interpretation of field data presented, and appropriate experimental designs discussed. These general principles are then applied to two detailed case studies, infectious pancreatic necrosis in Atlantic salmon and bovine tuberculosis in dairy cattle, and the lessons learnt are considered in detail. It is concluded that the rate limiting step in disease genetic studies will generally be provision of adequate phenotypic data, and its interpretation, rather than the genomic resources. Lastly, the importance of cross-disciplinary dialogue between the animal health and animal genetics communities is stressed.

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          Most cited references36

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          Accuracy of Predicting the Genetic Risk of Disease Using a Genome-Wide Approach

          Background The prediction of the genetic disease risk of an individual is a powerful public health tool. While predicting risk has been successful in diseases which follow simple Mendelian inheritance, it has proven challenging in complex diseases for which a large number of loci contribute to the genetic variance. The large numbers of single nucleotide polymorphisms now available provide new opportunities for predicting genetic risk of complex diseases with high accuracy. Methodology/Principal Findings We have derived simple deterministic formulae to predict the accuracy of predicted genetic risk from population or case control studies using a genome-wide approach and assuming a dichotomous disease phenotype with an underlying continuous liability. We show that the prediction equations are special cases of the more general problem of predicting the accuracy of estimates of genetic values of a continuous phenotype. Our predictive equations are responsive to all parameters that affect accuracy and they are independent of allele frequency and effect distributions. Deterministic prediction errors when tested by simulation were generally small. The common link among the expressions for accuracy is that they are best summarized as the product of the ratio of number of phenotypic records per number of risk loci and the observed heritability. Conclusions/Significance This study advances the understanding of the relative power of case control and population studies of disease. The predictions represent an upper bound of accuracy which may be achievable with improved effect estimation methods. The formulae derived will help researchers determine an appropriate sample size to attain a certain accuracy when predicting genetic risk.
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            Major quantitative trait loci affect resistance to infectious pancreatic necrosis in Atlantic salmon (Salmo salar).

            Infectious pancreatic necrosis (IPN) is a viral disease currently presenting a major problem in the production of Atlantic salmon (Salmon salar). IPN can cause significant mortality to salmon fry within freshwater hatcheries and to smolts following transfer to seawater, although challenged populations show clear genetic variation in resistance. To determine whether this genetic variation includes loci of major effect, a genomewide quantitative trait loci (QTL) scan was performed within 10 full-sib families that had received a natural seawater IPN challenge. To utilize the large difference between Atlantic salmon male and female recombination rates, a two-stage mapping strategy was employed. Initially, a sire-based QTL analysis was used to detect linkage groups with significant effects on IPN resistance, using two to three microsatellite markers per linkage group. A dam-based analysis with additional markers was then used to confirm and position any detected QTL. Two genomewide significant QTL and one suggestive QTL were detected in the genome scan. The most significant QTL was mapped to linkage group 21 and was significant at the genomewide level in both the sire and the dam-based analyses. The identified QTL can be applied in marker-assisted selection programs to improve the resistance of salmon to IPN and reduce disease-related mortality.
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              The impacts of livestock diseases and their control on growth and development processes that are pro-poor.

              Poverty is now at the heart of development discourse; we discuss how it is measured and understood. We next consider the negative and positive impacts of livestock on pro-poor development. Taking a value-chain approach that includes keepers, users and eaters of livestock, we identify diseases that are road blocks on the 'three livestock pathways out of poverty'. We discuss livestock impacts on poverty reduction and review attempts to prioritize the livestock diseases relevant to the poor. We make suggestions for metrics that better measure disease impact and show the benefits of more rigorous evaluation before reviewing recent attempts to measure the importance of disease to the poor. High impact of a disease does not guarantee high benefits from its control; other factors must be taken into consideration, including technical feasibility and political desirability. We conclude by considering how we might better understand and exploit the roles of livestock and improved animal health by posing three speculative questions on the impact of livestock diseases and their control on global poverty: how can understanding livestock and poverty links help disease control?; if global poverty reduction was the aim of livestock disease control, how would it differ from the current model?; and how much of the impact of livestock disease on poverty is due to disease control policy rather than disease itself?
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                Author and article information

                Journal
                Livest Sci
                Livestock science
                Elsevier BV
                1871-1413
                1871-1413
                Aug 2014
                : 166
                Affiliations
                [1 ] The Roslin Institute & Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian EH25 9RG, UK.
                Article
                S1871-1413(14)00235-2
                10.1016/j.livsci.2014.04.034
                4547482
                26339300
                f6871823-bc86-4ac1-9284-487a9e95d2a0
                History

                Bovine tuberculosis,Epidemiology,Genetics,Infection,Infectious pancreatic necrosis,Tolerance

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