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      Comparison of host genetic factors influencing pig response to infection with two North American isolates of porcine reproductive and respiratory syndrome virus

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          Abstract

          Background

          Porcine reproductive and respiratory syndrome (PRRS) is one of the most important swine diseases in the world and genetic selection of pigs for increased resistance to PRRS is an attractive method to improve the health status of the swine herd. This study compared phenotypic and genetic responses to infection with one of two genetically distinct type 2 PRRS virus (PRRSV) isolates: NVSL-97-7895 (NVSL) and KS-2006-72109 (KS06), and evaluated whether the single nucleotide polymorphism (SNP) WUR10000125 (WUR) on chromosome 4 that was associated with viral load and weight gain under infection with NVSL also has an effect on response to infection across North American PRRSV isolates. Wood’s lactation curve was fitted to repeated viremia measurements to derive five curve characteristics that were evaluated.

          Results

          Infection with NVSL was characterized by reaching a 14 ± 2 % higher peak viremia (PV) 2.5 ± 0.6 days earlier (time to peak; TP) than KS06, followed by 36 ± 1 % faster virus clearance, which occurred 3.9 ± 0.7 days sooner. Weight gain from 0 to 42 days post-infection (WG) tended to be higher under infection with KS06 than NVSL (3.7 ± 1.5 kg). Estimates of heritability were moderate for both PRRSV isolates for viral load from 0 to 21 days post-infection (VL) (NVSL: 0.31 ± 0.06; KS06: 0.51 ± 0.09) and WG (NVSL: 0.33 ± 0.06; KS06: 0.31 ± 0.09). Strong negative genetic correlations were observed between VL and WG for both NVSL (−0.74 ± 0.10) and KS06 (−0.52 ± 0.17) infected pigs. Pigs with genotype AB at the WUR SNP had a more desirable phenotype than AA pigs for all traits under infection with NVSL, but only for VL and PV with KS06; effects on other traits were smaller and not significantly different from zero (P > 0.05). Genetic correlations of host response between isolates were strong for VL, WG and PV. Accounting for WUR genotype had little impact on these correlations, suggesting that response to PRRSV infection has a substantial polygenic component that is common between these two isolates.

          Conclusions

          These results suggest that the KS06 PRRSV isolate is less virulent than NVSL but that genetic selection for increased resistance to either of these genetically distinct isolates is expected to increase resistance to the other isolate.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12711-016-0222-0) contains supplementary material, which is available to authorized users.

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          Most cited references49

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          Statistical confidence for likelihood-based paternity inference in natural populations.

          Paternity inference using highly polymorphic codominant markers is becoming common in the study of natural populations. However, multiple males are often found to be genetically compatible with each offspring tested, even when the probability of excluding an unrelated male is high. While various methods exist for evaluating the likelihood of paternity of each nonexcluded male, interpreting these likelihoods has hitherto been difficult, and no method takes account of the incomplete sampling and error-prone genetic data typical of large-scale studies of natural systems. We derive likelihood ratios for paternity inference with codominant markers taking account of typing error, and define a statistic delta for resolving paternity. Using allele frequencies from the study population in question, a simulation program generates criteria for delta that permit assignment of paternity to the most likely male with a known level of statistical confidence. The simulation takes account of the number of candidate males, the proportion of males that are sampled and gaps and errors in genetic data. We explore the potentially confounding effect of relatives and show that the method is robust to their presence under commonly encountered conditions. The method is demonstrated using genetic data from the intensively studied red deer (Cervus elaphus) population on the island of Rum, Scotland. The Windows-based computer program, CERVUS, described in this study is available from the authors. CERVUS can be used to calculate allele frequencies, run simulations and perform parentage analysis using data from all types of codominant markers.
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            Design of a High Density SNP Genotyping Assay in the Pig Using SNPs Identified and Characterized by Next Generation Sequencing Technology

            Background The dissection of complex traits of economic importance to the pig industry requires the availability of a significant number of genetic markers, such as single nucleotide polymorphisms (SNPs). This study was conducted to discover several hundreds of thousands of porcine SNPs using next generation sequencing technologies and use these SNPs, as well as others from different public sources, to design a high-density SNP genotyping assay. Methodology/Principal Findings A total of 19 reduced representation libraries derived from four swine breeds (Duroc, Landrace, Large White, Pietrain) and a Wild Boar population and three restriction enzymes (AluI, HaeIII and MspI) were sequenced using Illumina's Genome Analyzer (GA). The SNP discovery effort resulted in the de novo identification of over 372K SNPs. More than 549K SNPs were used to design the Illumina Porcine 60K+SNP iSelect Beadchip, now commercially available as the PorcineSNP60. A total of 64,232 SNPs were included on the Beadchip. Results from genotyping the 158 individuals used for sequencing showed a high overall SNP call rate (97.5%). Of the 62,621 loci that could be reliably scored, 58,994 were polymorphic yielding a SNP conversion success rate of 94%. The average minor allele frequency (MAF) for all scorable SNPs was 0.274. Conclusions/Significance Overall, the results of this study indicate the utility of using next generation sequencing technologies to identify large numbers of reliable SNPs. In addition, the validation of the PorcineSNP60 Beadchip demonstrated that the assay is an excellent tool that will likely be used in a variety of future studies in pigs.
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              GBP5 promotes NLRP3 inflammasome assembly and immunity in mammals.

              Inflammasomes are sensory complexes that alert the immune system to the presence of infection or tissue damage. These complexes assemble NLR (nucleotide binding and oligomerization, leucine-rich repeat) or ALR (absent in melanoma 2-like receptor) proteins to activate caspase-1 cleavage and interleukin (IL)-1β/IL-18 secretion. Here, we identified a non-NLR/ALR human protein that stimulates inflammasome assembly: guanylate binding protein 5 (GBP5). GBP5 promoted selective NLRP3 inflammasome responses to pathogenic bacteria and soluble but not crystalline inflammasome priming agents. Generation of Gbp5(-/-) mice revealed pronounced caspase-1 and IL-1β/IL-18 cleavage defects in vitro and impaired host defense and Nlrp3-dependent inflammatory responses in vivo. Thus, GBP5 serves as a unique rheostat for NLRP3 inflammasome activation and extends our understanding of the inflammasome complex beyond its core machinery.
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                Author and article information

                Contributors
                ahess@iastate.edu
                Zeenath.Islam@roslin.ed.ac.uk
                mhayr@iastate.edu
                browland@vet.k-state.edu
                Joan.Lunney@ars.usda.gov
                andrea.wilson@roslin.ed.ac.uk
                plastow@ualberta.ca
                jdekkers@iastate.edu
                Journal
                Genet Sel Evol
                Genet. Sel. Evol
                Genetics, Selection, Evolution : GSE
                BioMed Central (London )
                0999-193X
                1297-9686
                20 June 2016
                20 June 2016
                2016
                : 48
                : 43
                Affiliations
                [ ]Department of Animal Science, Iowa State University, Ames, IA USA
                [ ]The Roslin Institute and R(D)SVS, University of Edinburgh, Edinburgh, Midlothian UK
                [ ]College of Veterinary Medicine, Kansas State University, Manhattan, KS USA
                [ ]USDA, ARS, BARC, Beltsville, MD USA
                [ ]University of Alberta, Edmonton, AB Canada
                Article
                222
                10.1186/s12711-016-0222-0
                4915112
                27324857
                5802cd69-5114-46a4-9932-d3d2a2007b5c
                © The Author(s) 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 12 January 2016
                : 8 June 2016
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100008762, Genome Canada;
                Award ID: Application of Genomics to Improve Swine Health and Welfare
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100005825, National Institute of Food and Agriculture;
                Award ID: 2013-68004-20362
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100008370, National Pork Board;
                Award ID: 12-061 and14-223
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2016

                Genetics
                Genetics

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