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      A genome-wide association study of fetal response to type 2 porcine reproductive and respiratory syndrome virus challenge

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          Abstract

          Control of porcine reproductive and respiratory syndrome (PRRS) is economically important for the swine industry worldwide. As current PRRS vaccines do not completely protect against heterologous challenge, alternative means of control, including enhanced genetic resilience, are needed. For reproductive PRRS, the genetic basis of fetal response to PRRS virus (PRRSV) infection is poorly understood. Genome-wide association studies (GWAS) were done here using data from 928 fetuses from pregnant gilts experimentally challenged with type 2 PRRSV. Fetuses were assessed for viral load in thymus (VLT), viral load in endometrium (VLE), fetal death (FD) and fetal viability (FV), and genotyped at a medium density. Collectively, 21 candidate genomic regions were found associated with these traits, seven of which overlap with previously reported QTLs for pig health and reproduction. A comparison with ongoing and related transcriptomic analyses of fetal response to PRRSV infection found differentially expressed genes within 18 candidate regions. Some of these genes have immune system functions, and have been reported to contribute to host response to PRRSV infection. The results provide new evidence about the genetic basis of fetal response to PRRSV challenge, and may ultimately lead to alternative control strategies to reduce the impact of reproductive PRRS.

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          Most cited references58

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          JNK signaling in apoptosis.

          Jun N-terminal kinases or JNKs play a critical role in death receptor-initiated extrinsic as well as mitochondrial intrinsic apoptotic pathways. JNKs activate apoptotic signaling by the upregulation of pro-apoptotic genes through the transactivation of specific transcription factors or by directly modulating the activities of mitochondrial pro- and antiapoptotic proteins through distinct phosphorylation events. This review analyses our present understanding of the role of JNK in apoptotic signaling and the various mechanisms by which JNK promotes apoptosis.
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            Assessment of the economic impact of porcine reproductive and respiratory syndrome on swine production in the United States.

            To estimate the annual cost of infections attributable to porcine reproductive and respiratory syndrome (PRRS) virus to US swine producers. Economic analysis. Data on the health and productivity of PRRS-affected and PRRS-unaffected breeding herds and growing-pig populations were collected from a convenience sample of swine farms in the midwestern United States. Health and productivity variables of PRRS-affected and PRRS-unaffected swine farms were analyzed to estimate the impact of PRRS on specific farms. National estimates of PRRS incidence were then used to determine the annual economic impact of PRRS on US swine producers. PRRS affected breeding herds and growing-pig populations as measured by a decrease in reproductive health, an increase in deaths, and reductions in the rate and efficiency of growth. Total annual economic impact of these effects on US swine producers was estimated at dollar 66.75 million in breeding herds and dollar 493.57 million in growing-pig populations. PRRS imposes a substantial financial burden on US swine producers and causes approximately dollar 560.32 million in losses each year. By comparison, prior to eradication, annual losses attributable to classical swine fever (hog cholera) and pseudorabies were estimated at dollar 364.09 million and dollar 36.27 million, respectively (adjusted on the basis of year 2004 dollars). Current PRRS control strategies are not predictably successful; thus, PRRS-associated losses will continue into the future. Research to improve our understanding of ecologic and epidemiologic characteristics of the PRRS virus and technologic advances (vaccines and diagnostic tests) to prevent clinical effects are warranted.
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              Genome-wide association analysis by lasso penalized logistic regression.

              In ordinary regression, imposition of a lasso penalty makes continuous model selection straightforward. Lasso penalized regression is particularly advantageous when the number of predictors far exceeds the number of observations. The present article evaluates the performance of lasso penalized logistic regression in case-control disease gene mapping with a large number of SNPs (single nucleotide polymorphisms) predictors. The strength of the lasso penalty can be tuned to select a predetermined number of the most relevant SNPs and other predictors. For a given value of the tuning constant, the penalized likelihood is quickly maximized by cyclic coordinate ascent. Once the most potent marginal predictors are identified, their two-way and higher order interactions can also be examined by lasso penalized logistic regression. This strategy is tested on both simulated and real data. Our findings on coeliac disease replicate the previous SNP results and shed light on possible interactions among the SNPs. The software discussed is available in Mendel 9.0 at the UCLA Human Genetics web site. Supplementary data are available at Bioinformatics online.
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                05 February 2016
                2016
                : 6
                : 20305
                Affiliations
                [1 ]Department of Agricultural, Food, and Nutritional Science, University of Alberta , Edmonton, AB T6G 2P5, Canada
                [2 ]University Clinic for Swine, Department for Farm Animals and Veterinary Public Health, University of Veterinary Medicine Vienna , Vienna 1210, Austria
                [3 ]Department of Large Animal Clinical Sciences, Western College of Veterinary Medicine, University of Saskatchewan , Saskatoon, SK S7N 5B4, Canada
                Author notes
                Article
                srep20305
                10.1038/srep20305
                4742883
                26846722
                180ba091-54ff-4c3e-b097-a6a8d4eaf05e
                Copyright © 2016, Macmillan Publishers Limited

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 02 September 2015
                : 30 December 2015
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