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      A Genome Wide Survey of SNP Variation Reveals the Genetic Structure of Sheep Breeds

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          Abstract

          The genetic structure of sheep reflects their domestication and subsequent formation into discrete breeds. Understanding genetic structure is essential for achieving genetic improvement through genome-wide association studies, genomic selection and the dissection of quantitative traits. After identifying the first genome-wide set of SNP for sheep, we report on levels of genetic variability both within and between a diverse sample of ovine populations. Then, using cluster analysis and the partitioning of genetic variation, we demonstrate sheep are characterised by weak phylogeographic structure, overlapping genetic similarity and generally low differentiation which is consistent with their short evolutionary history. The degree of population substructure was, however, sufficient to cluster individuals based on geographic origin and known breed history. Specifically, African and Asian populations clustered separately from breeds of European origin sampled from Australia, New Zealand, Europe and North America. Furthermore, we demonstrate the presence of stratification within some, but not all, ovine breeds. The results emphasize that careful documentation of genetic structure will be an essential prerequisite when mapping the genetic basis of complex traits. Furthermore, the identification of a subset of SNP able to assign individuals into broad groupings demonstrates even a small panel of markers may be suitable for applications such as traceability.

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          Most cited references 42

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          SNP discovery and allele frequency estimation by deep sequencing of reduced representation libraries.

          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.

            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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              PolyPhred: automating the detection and genotyping of single nucleotide substitutions using fluorescence-based resequencing.

              Fluorescence-based sequencing is playing an increasingly important role in efforts to identify DNA polymorphisms and mutations of biological and medical interest. The application of this technology in generating the reference sequence of simple and complex genomes is also driving the development of new computer programs to automate base calling (Phred), sequence assembly (Phrap) and sequence assembly editing (Consed) in high throughput settings. In this report we describe a new computer program known as PolyPhred that automatically detects the presence of heterozygous single nucleotide substitutions by fluorescencebased sequencing of PCR products. Its operations are integrated with the use of the Phred, Phrap and Consed programs and together these tools generate a high throughput system for detecting DNA polymorphisms and mutations by large scale fluorescence-based resequencing. Analysis of sequences containing known DNA variants demonstrates that the accuracy of PolyPhred with single pass data is >99% when the sequences are generated with fluorescent dye-labeled primers and approximately 90% for those prepared with dye-labeled terminators.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2009
                3 March 2009
                : 4
                : 3
                Affiliations
                [1 ]CSIRO Livestock Industries, St Lucia, Brisbane, Queensland, Australia
                [2 ]United States Department of Agriculture (USDA), Agriculture Research Service (ARS), Meat Animal Research Center, Clay Center, Nebraska, United States of America
                [3 ]Department of Veterinary Science, The University of Melbourne, Melbourne, Parkville, Victoria, Australia
                [4 ]Australian Genome Research Centre, St Lucia, Brisbane, Queensland, Australia
                [5 ]Johns Hopkins University, Institute of Genetic Medicine, Baltimore, Maryland, United States of America
                [6 ]AgResearch, Invermay Agricultural Centre, Mosgiel, New Zealand
                [7 ]ADVS Department, College of Agriculture, Utah State University, Utah, United States of America
                [8 ]School of Meat Science, University of New England, Armidale, New South Wales, Australia
                [9 ]Faculty of Veterinary Science, University of Sydney, Sydney, New South Wales, Australia
                University of Uppsala, Sweden
                Author notes

                Conceived and designed the experiments: JK DT BPD JFM JM HVO FN ISGC. Performed the experiments: AM PW RGI RM ISGC. Analyzed the data: JK DT BPD MH JFM AM PW RGI SM DT JM ISGC. Contributed reagents/materials/analysis tools: JK DT BPD MH RGI JM NC HR ISGC. Wrote the paper: JK DT BPD FN HR ISGC.

                Article
                08-PONE-RA-07434R1
                10.1371/journal.pone.0004668
                2652362
                19270757
                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.
                Page count
                Pages: 13
                Categories
                Research Article
                Genetics and Genomics/Animal Genetics
                Genetics and Genomics/Gene Discovery
                Genetics and Genomics/Genome Projects

                Uncategorized

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