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      A Genome-Wide Association Study Identifies Two Novel Promising Candidate Genes Affecting Escherichia coli F4ab/F4ac Susceptibility in Swine

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          Abstract

          Enterotoxigenic Escherichia coli (ETEC) expressing F4 fimbria is the major pathogenic bacteria causing diarrhoea in neonatal and post-weaning piglets. Previous studies have revealed that the susceptibility to ETEC F4ab/F4ac is an autosomal Mendelian dominant trait and the loci controlling the F4ab/F4ac receptor are located on SSC13q41, between markers SW207 and S0283. To pinpoint these loci and further validate previous findings, we performed a genome-wide association study (GWAS) using a two generation family-based population, consisting of 301 piglets with phenotypes of susceptibility to ETEC F4ab/F4ac by the vitro adhesion test. The DNA of all piglets and their parents was genotyped using the Illumina PorcineSNP60 BeadChip, and 50,972 and 50,483 SNPs were available for F4ab and F4ac susceptibility, respectively, in the association analysis after quality control. In summary, 28 and 18 significant SNPs ( p<0.05) were detected associated with F4ab and F4ac susceptibility respectively at genome-wide significance level. From these significant findings, two novel candidate genes, HEG1 and ITGB5, were firstly identified as the most promising genes underlying F4ab/F4ac susceptibility in swine according to their functions and positions. Our findings herein provide a novel evidence for unravelling genetic mechanism of diarrhoea risk in piglets.

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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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            Genome-Wide Association Study Identifies Loci for Body Composition and Structural Soundness Traits in Pigs

            Background The recent completion of the swine genome sequencing project and development of a high density porcine SNP array has made genome-wide association (GWA) studies feasible in pigs. Methodology/Principal Findings Using Illumina's PorcineSNP60 BeadChip, we performed a pilot GWA study in 820 commercial female pigs phenotyped for backfat, loin muscle area, body conformation in addition to feet and leg (FL) structural soundness traits. A total of 51,385 SNPs were jointly fitted using Bayesian techniques as random effects in a mixture model that assumed a known large proportion (99.5%) of SNPs had zero effect. SNP annotations were implemented through the Sus scrofa Build 9 available from pig Ensembl. We discovered a number of candidate chromosomal regions, and some of them corresponded to QTL regions previously reported. We not only have identified some well-known candidate genes for the traits of interest, such as MC4R (for backfat) and IGF2 (for loin muscle area), but also obtained novel promising genes, including CHCHD3 (for backfat), BMP2 (for loin muscle area, body size and several FL structure traits), and some HOXA family genes (for overall leg action). The candidate regions responsible for body conformation and FL structure soundness did not overlap greatly which implied that these traits were controlled by different genes. Functional clustering analyses classified the genes into categories related to bone and cartilage development, muscle growth and development or the insulin pathway suggesting the traits are regulated by common pathways or gene networks that exert roles at different spatial and temporal stages. Conclusions/Significance This study is one of the earliest GWA reports on important quantitative traits in pigs, and the findings will contribute to the further biological function analysis of the identified candidate genes and potential utilization of them in marker assisted selection.
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              Genome Wide Association Studies for Milk Production Traits in Chinese Holstein Population

              Genome-wide association studies (GWAS) based on high throughput SNP genotyping technologies open a broad avenue for exploring genes associated with milk production traits in dairy cattle. Motivated by pinpointing novel quantitative trait nucleotide (QTN) across Bos Taurus genome, the present study is to perform GWAS to identify genes affecting milk production traits using current state-of-the-art SNP genotyping technology, i.e., the Illumina BovineSNP50 BeadChip. In the analyses, the five most commonly evaluated milk production traits are involved, including milk yield (MY), milk fat yield (FY), milk protein yield (PY), milk fat percentage (FP) and milk protein percentage (PP). Estimated breeding values (EBVs) of 2,093 daughters from 14 paternal half-sib families are considered as phenotypes within the framework of a daughter design. Association tests between each trait and the 54K SNPs are achieved via two different analysis approaches, a paternal transmission disequilibrium test (TDT)-based approach (L1-TDT) and a mixed model based regression analysis (MMRA). In total, 105 SNPs were detected to be significantly associated genome-wise with one or multiple milk production traits. Of the 105 SNPs, 38 were commonly detected by both methods, while four and 63 were solely detected by L1-TDT and MMRA, respectively. The majority (86 out of 105) of the significant SNPs is located within the reported QTL regions and some are within or close to the reported candidate genes. In particular, two SNPs, ARS-BFGL-NGS-4939 and BFGL-NGS-118998, are located close to the DGAT1 gene (160bp apart) and within the GHR gene, respectively. Our findings herein not only provide confirmatory evidences for previously findings, but also explore a suite of novel SNPs associated with milk production traits, and thus form a solid basis for eventually unraveling the causal mutations for milk production traits in dairy cattle.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2012
                23 March 2012
                : 7
                : 3
                : e32127
                Affiliations
                [1 ]Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China
                [2 ]State Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Centre for Disease Control and Prevention, Beijing, China
                American University in Cairo, Egypt
                Author notes

                Conceived and designed the experiments: WXF YL XYN JFL QZ. Performed the experiments: WXF YL XL XYN. Analyzed the data: WXF YL XL XDD JFL. Contributed reagents/materials/analysis tools: WXF YL XDD JFL QZ. Wrote the paper: WXF YL JFL QZ.

                Article
                PONE-D-11-10700
                10.1371/journal.pone.0032127
                3311625
                22457712
                85a263d2-3ff1-466d-bb48-876daed12036
                Fu et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 14 June 2011
                : 24 January 2012
                Page count
                Pages: 8
                Categories
                Research Article
                Agriculture
                Animal Management
                Biology
                Computational Biology
                Genomics
                Genome Analysis Tools
                Genetics
                Heredity
                Genomics
                Genome Analysis Tools
                Model Organisms
                Population Biology
                Mathematics
                Statistics
                Medicine
                Clinical Research Design
                Infectious Diseases
                Bacterial Diseases
                Veterinary Science
                Animal Management
                Veterinary Diseases

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