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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

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          Abstract

          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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          Development and Characterization of a High Density SNP Genotyping Assay for Cattle

          Lakshmi Matukumalli, Cynthia Lawley, Robert Schnabel … (2009)
          The success of genome-wide association (GWA) studies for the detection of sequence variation affecting complex traits in human has spurred interest in the use of large-scale high-density single nucleotide polymorphism (SNP) genotyping for the identification of quantitative trait loci (QTL) and for marker-assisted selection in model and agricultural species. A cost-effective and efficient approach for the development of a custom genotyping assay interrogating 54,001 SNP loci to support GWA applications in cattle is described. A novel algorithm for achieving a compressed inter-marker interval distribution proved remarkably successful, with median interval of 37 kb and maximum predicted gap of <350 kb. The assay was tested on a panel of 576 animals from 21 cattle breeds and six outgroup species and revealed that from 39,765 to 46,492 SNP are polymorphic within individual breeds (average minor allele frequency (MAF) ranging from 0.24 to 0.27). The assay also identified 79 putative copy number variants in cattle. Utility for GWA was demonstrated by localizing known variation for coat color and the presence/absence of horns to their correct genomic locations. The combination of SNP selection and the novel spacing algorithm allows an efficient approach for the development of high-density genotyping platforms in species having full or even moderate quality draft sequence. Aspects of the approach can be exploited in species which lack an available genome sequence. The BovineSNP50 assay described here is commercially available from Illumina and provides a robust platform for mapping disease genes and QTL in cattle.
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            SNP discovery and allele frequency estimation by deep sequencing of reduced representation libraries.

            Curtis Van Tassell, Timothy P. L. Smith, Lakshmi Matukumalli … (2008)
            High-density single-nucleotide polymorphism (SNP) arrays have revolutionized the ability of genome-wide association studies to detect genomic regions harboring sequence variants that affect complex traits. Extensive numbers of validated SNPs with known allele frequencies are essential to construct genotyping assays with broad utility. We describe an economical, efficient, single-step method for SNP discovery, validation and characterization that uses deep sequencing of reduced representation libraries (RRLs) from specified target populations. Using nearly 50 million sequences generated on an Illumina Genome Analyzer from DNA of 66 cattle representing three populations, we identified 62,042 putative SNPs and predicted their allele frequencies. Genotype data for these 66 individuals validated 92% of 23,357 selected genome-wide SNPs, with a genotypic and sequence allele frequency correlation of r = 0.67. This approach for simultaneous de novo discovery of high-quality SNPs and population characterization of allele frequencies may be applied to any species with at least a partially sequenced genome.
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              Efficient mapping of mendelian traits in dogs through genome-wide association.

              Elinor K Karlsson, Izabella Baranowska, Claire Wade … (2007)
              With several hundred genetic diseases and an advantageous genome structure, dogs are ideal for mapping genes that cause disease. Here we report the development of a genotyping array with approximately 27,000 SNPs and show that genome-wide association mapping of mendelian traits in dog breeds can be achieved with only approximately 20 dogs. Specifically, we map two traits with mendelian inheritance: the major white spotting (S) locus and the hair ridge in Rhodesian ridgebacks. For both traits, we map the loci to discrete regions of <1 Mb. Fine-mapping of the S locus in two breeds refines the localization to a region of approximately 100 kb contained within the pigmentation-related gene MITF. Complete sequencing of the white and solid haplotypes identifies candidate regulatory mutations in the melanocyte-specific promoter of MITF. Our results show that genome-wide association mapping within dog breeds, followed by fine-mapping across multiple breeds, will be highly efficient and generally applicable to trait mapping, providing insights into canine and human health.
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                Author and article information

                Contributors
                : Role: Editor
                Journal
                Journal ID (nlm-ta): PLoS One
                Journal ID (publisher-id): plos
                Journal ID (pmc): plosone
                Title: PLoS ONE
                Publisher: Public Library of Science (San Francisco, USA )
                ISSN (Electronic): 1932-6203
                Publication date Collection: 2009
                Publication date (Electronic): 5 August 2009
                Volume: 4
                Issue: 8
                Electronic Location Identifier: e6524
                Affiliations
                [1 ]Wageningen University, Animal Breeding and Genomics Centre, Wageningen, The Netherlands
                [2 ]Department of Pathology, University of Cambridge, Cambridge, United Kingdom
                [3 ]Division of Genetics and Genomics, The Roslin Institute and the Royal (Dick) School of Veterinary Studies, University of Edinburgh, Roslin Midlothian, United Kingdom
                [4 ]Institute for Genomic Biology, University of Illinois, Urbana, Illinois, United States of America
                [5 ]Aarhus University, Faculty of Agricultural Sciences, Tjele, Denmark
                [6 ]The Wellcome Trust Sanger Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom
                [7 ]INRA, Laboratoire de Génétique Cellulaire, Castanet Tolosan, France
                [8 ]Illumina, Inc., San Diego, California, United States of America
                [9 ]Department of Animal Science and Center for Integrated Animal Genomics, Iowa State University, Ames, Iowa, United States of America
                [10 ]USDA, ARS, US Meat Animal Research Center, Clay Center, Nebraska, United States of America
                [11 ]Division of Animal Sciences, University of Missouri-Columbia, Columbia, Missouri, United States of America
                [12 ]Bovine Functional Genomics Laboratory, U.S. Department of Agriculture (USDA), Agricultural Research Service (ARS), Beltsville, Maryland, United States of America
                Temasek Life Sciences Laboratory, Singapore
                Author notes

                Conceived and designed the experiments: RC AA JB MR CVT JT LBS MG. Performed the experiments: AMR RC JH MG. Analyzed the data: AMR AJA MH HK AL HJM CVT MG. Contributed reagents/materials/analysis tools: AMR RC NA AJA CB CC RC PD JH ZLH DM DN GR MR TS RDS CVT RW LBS MG. Wrote the paper: AMR MG.

                Article
                Publisher ID: 09-PONE-RA-10188
                DOI: 10.1371/journal.pone.0006524
                PMC ID: 2716536
                PubMed ID: 19654876
                SO-VID: cd2b929c-5787-4fe1-bfbb-e5cdd8be8274
                Copyright © This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.
                History
                Date received : 6 May 2009
                Date accepted : 21 June 2009
                Page count
                Pages: 13
                Categories
                Subject: Research Article
                Subject: Genetics and Genomics/Animal Genetics
                Subject: Genetics and Genomics/Genomics
                Subject: Genetics and Genomics/Population Genetics

                ScienceOpen disciplines: Uncategorized
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                ScienceOpen disciplines: Uncategorized

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