Signatures of selection and environmental adaptation across the goat genome post-domestication

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Dokumenter

DOI

  • Francesca Bertolini, National Institute of Aquatic Resources, Technical University of Denmark (DTU), 2800, Lyngby, Denmark. fbert@iastate.edu.
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  • Bertrand Servin, GenPhySE, INRA, INPT, ENVT, Université de Toulouse, 31326, Castanet-Tolosan, France. andres.legarra@inra.fr.
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  • Andrea Talenti, Dipartimento di Medicina Veterinaria, Università degli Studi di Milano, 20133, Milan, Italy.
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  • Estelle Rochat, Laboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015, Lausanne, Switzerland.
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  • Eui Soo Kim, Recombinetics Inc, St Paul, 55104, MN, USA.
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  • Claire Oget, GenPhySE, INRA, INPT, ENVT, Université de Toulouse, 31326, Castanet-Tolosan, France. andres.legarra@inra.fr.
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  • Isabelle Palhière, GenPhySE, INRA, INPT, ENVT, Université de Toulouse, 31326, Castanet-Tolosan, France. andres.legarra@inra.fr.
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  • Alessandra Crisà, Consiglio per la ricerca in agricoltura e l'analisi dell'economia agraria (CREA) - Research Centre for Animal Production and Acquaculture, 00015, Monterotondo, Roma, Italy.
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  • Gennaro Catillo, Consiglio per la ricerca in agricoltura e l'analisi dell'economia agraria (CREA) - Research Centre for Animal Production and Acquaculture, 00015, Monterotondo, Roma, Italy.
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  • Roberto Steri, Consiglio per la ricerca in agricoltura e l'analisi dell'economia agraria (CREA) - Research Centre for Animal Production and Acquaculture, 00015, Monterotondo, Roma, Italy.
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  • Marcel Amills, Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Campus Universitat Autonoma de Barcelona, Bellaterra, 08193, Barcelona, Spain.
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  • Licia Colli, BioDNA Centro di Ricerca sulla Biodiversità e sul DNA Antico, Università Cattolica del S. Cuore, 29100, Piacenza, Italy.
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  • Gabriele Marras, Fondazione Parco Tecnologico Padano (PTP), 26900, Lodi, Italy.
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  • Marco Milanesi, School of Veterinary Medicine, Department of Support, Production and Animal Health, São Paulo State University (UNESP), Araçatuba, Brazil.
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  • Ezequiel Nicolazzi, Fondazione Parco Tecnologico Padano (PTP), 26900, Lodi, Italy.
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  • Benjamin D Rosen, Animal Genomics and Improvement Laboratory, ARS USDA, Beltsville, MD, 20705, USA.
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  • Curtis P Van Tassell, Animal Genomics and Improvement Laboratory, ARS USDA, Beltsville, MD, 20705, USA.
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  • Bernt Guldbrandtsen
  • Tad S Sonstegard, Recombinetics Inc, St Paul, 55104, MN, USA.
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  • Gwenola Tosser-Klopp, GenPhySE, INRA, INPT, ENVT, Université de Toulouse, 31326, Castanet-Tolosan, France. andres.legarra@inra.fr.
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  • Alessandra Stella, BioDNA Centro di Ricerca sulla Biodiversità e sul DNA Antico, Università Cattolica del S. Cuore, 29100, Piacenza, Italy.
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  • Max F Rothschild, Department of Animal Science, Iowa State University, Ames, IA, 50011, USA.
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  • Stéphane Joost, Laboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015, Lausanne, Switzerland.
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  • Paola Crepaldi, Dipartimento di Medicina Veterinaria, Università degli Studi di Milano, 20133, Milan, Italy.
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  • The ADAPTMAP consortium (Vivi Hunnicke Nielsen; member)

BACKGROUND: Since goat was domesticated 10,000 years ago, many factors have contributed to the differentiation of goat breeds and these are classified mainly into two types: (i) adaptation to different breeding systems and/or purposes and (ii) adaptation to different environments. As a result, approximately 600 goat breeds have developed worldwide; they differ considerably from one another in terms of phenotypic characteristics and are adapted to a wide range of climatic conditions. In this work, we analyzed the AdaptMap goat dataset, which is composed of data from more than 3000 animals collected worldwide and genotyped with the CaprineSNP50 BeadChip. These animals were partitioned into groups based on geographical area, production uses, available records on solid coat color and environmental variables including the sampling geographical coordinates, to investigate the role of natural and/or artificial selection in shaping the genome of goat breeds.

RESULTS: Several signatures of selection on different chromosomal regions were detected across the different breeds, sub-geographical clusters, phenotypic and climatic groups. These regions contain genes that are involved in important biological processes, such as milk-, meat- or fiber-related production, coat color, glucose pathway, oxidative stress response, size, and circadian clock differences. Our results confirm previous findings in other species on adaptation to extreme environments and human purposes and provide new genes that could explain some of the differences between goat breeds according to their geographical distribution and adaptation to different environments.

CONCLUSIONS: These analyses of signatures of selection provide a comprehensive first picture of the global domestication process and adaptation of goat breeds and highlight possible genes that may have contributed to the differentiation of this species worldwide.

OriginalsprogEngelsk
TidsskriftGenetics Selection Evolution
Vol/bind50
Sider (fra-til)57
ISSN0999-193X
DOI
StatusUdgivet - 19 nov. 2018

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