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Short communication
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Characterization of 27 breed-specific single nucleotide polymorphisms (SNPs) and their
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polymorphisms within- and across-breed in goat
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I. Cappuccio1, L. Pariset1, P. Ajmone-Marsan2, S. Dunner3, O. Cortes3,G. Erhardt4, C. Peter4,
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S. Joost5, I. Nijman6, J.A. Lenstra6, G. Luikart7, G. Obexer-Ruff, A. Valentini1 and Econogene
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Consortium9
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Dipartimento di Produzioni Animali, Università della Tuscia, Viterbo, Italy
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Istituto di Zootecnica, Università Cattolica del Sacro Cuore, Piacenza, Italy
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Departimento de Producción Animal, Universidad Complutense, Madrid, Spain
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Department of Animal Breeding and Genetics, Justus-Liebig-Universität, Giessen, Germany
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Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
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Laboratoire de Biologie des Populations d'Altitude, Université Joseph Fourier, Grenoble, France
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Institute of Genetics, Veterinary Faculty, University of Berne, Switzerland
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http://lasig.epfl.ch/projets/econogene
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Correspondence: L. Pariset, tel. +39 761 357447, fax +39 761 357434, e-mail: pariset@unitus.it
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Author to whom reprint requests should be addressed: corresponding author
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Summary
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Single nucleotide polymorphisms (SNPs) are useful markers in biodiversity studies and in
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commercial tasks like traceability and paternity testing. Within the Econogene project, we
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characterized in goat 27 single nucleotide polymorphisms (SNPs) identified using a targeted-gene
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approach. Inter-breed polymorphisms were identified in a panel of 16 unrelated individuals
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belonging to 8 different goat breeds selected throughout Europe. Genotypes of goat from the 8
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breeds were determined for all the SNPs characterized and basic statistics were calculated for each
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SNP. The SNPs described will be a useful complement to available genome markers. To date, there
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are not SNPs available for goat in NCBI dbSNP database and only 26 are reported in literature.
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Keywords
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Goat, single nucleotide polymorphisms, gene diversity.
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An ideal genetic marker for population and evolutionary studies should be abundant and distributed
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widely across the genome and the data must be comparable across laboratories using different
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genotype scoring methods or technologies (Sunnucks 2000), characteristics proper to single
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nucleotide polymorphisms (SNPs). SNPs are frequent in most genomes (Brouillette et al. 2000;
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Sachidanandam et al. 2001; Shubitowski et al. 2001), are suitable in ecological and conservation
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studies (Morin et al., 2004; Seddon et al., 2005; Vignal et al. 2002; Brumfield et al. 2003) and are
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valuable for estimating parameters such as population history and inference of relationships
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(Kuhner et al., 2000; Glaubitz et al., 2003). Despite some obvious advantages of SNPs and their
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increasing use in human and model organism studies, they have not been employed frequently in
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studies of non-model organisms, primarily due to difficulties in finding SNPs in species where little
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DNA sequence data (Aitken et al 2004). Regardless of the difficulties in SNPs identification, the
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use of those markers could lead to a rapid, large scale and cost effective genotyping (Schlotterer,
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2004; Syvanen, 2001; Vitalis, 2001; Vignal, 2002).
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Within the Econogene project, a concerted list of genes involved in key metabolic pathways and
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candidate to have high adaptive value and to be under strong natural or artificial selection has been
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selected for SNP discovery by across-breed DNA comparison in goat. SNPs were characterized on
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unrelated individuals belonging to 8 goat breeds selected throughout Europe and representing the
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most of the variation across a wide geographic area: German Alpine (Germany), Corsican (France),
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Verata (Spain), Greek goat (Greece), Grigia Molisana (Italy), Baladie (Egypt), Polish fawn
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improved goat (Polony), Brava (Portougal). The 27 SNPs identified were analysed in about 30
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individuals of each of the same 8 breeds, sampling no more than 3 individuals per farm. DNA was
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isolated after collection of whole blood using standard techniques.
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SNPs have been discovered both in exon and intron sequences using PCR-RFLP, SSCP, DHPLC or
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direct sequencing. Primers were designed using goat sequences, where available, or the consensus
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of genomic sequences of the closest species present in Genebank, and used both for PCR
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amplification and sequencing of the corresponding genomic fragment. Sequences were BLASTed to
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check for homology greater than 90%. Of the 27 identified SNPs, 18 were transitions, 8 were
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transversions and 1 was a deletion. Table 1 shows loci in which SNPs were identified,
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characterization details and, for each locus and over all populations, the frequencies of the rare
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allele, the number of samples analysed, the gene diversity (He) and the Ho (Weir, 1996), the PIC
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(Botstein et al., 1980) and the F statistics (Weir & Cockerham, 1984). In table 2 the Fis and the
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frequencies of the rare alleles for each locus and each breed are reported (Weir & Hill, 2002).
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All the statistical analyses were calculated using the program Powermarker (Liu & Muse, 2001).
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Of the 27 identified SNPs, 26 show a frequency overall breeds of the rare allele higher then 5% and
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are suitable for population genetic analysis.
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Acknowledgements:
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This work has been partially supported by the EU Econogene contract QLK5-CT-2001-02461. The
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content of the publication does not represent necessarily the views of the Commission or its
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services.
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