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

Francesca Bertolini; Bertrand Servin; Andrea Talenti; Estelle Rochat; Eui Soo Kim; Claire Oget; Isabelle Palhière; Alessandra Crisà; Gennaro Catillo; Roberto Steri; Marcel Amills; Licia Colli; Gabriele Marras; Marco Milanesi; Ezequiel Nicolazzi; Benjamin D. Rosen; Curtis P. Van Tassell; Bernt Guldbrandtsen; Tad S. Sonstegard; Gwenola Tosser-Klopp; Alessandra Stella; Max F. Rothschild; Stéphane Joost; Paola Crepaldi

doi:10.1186/s12711-018-0421-y

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

Authors

Bertolini, Francesca^{1, 2}
Servin, Bertrand³
Talenti, Andrea⁴
Rochat, Estelle⁵
Kim, Eui Soo⁶
Oget, Claire³
Palhière, Isabelle³
Crisà, Alessandra⁷
Catillo, Gennaro⁷
Steri, Roberto⁷
Amills, Marcel⁸
Colli, Licia^{9, 10}
Marras, Gabriele¹¹
Milanesi, Marco^{9, 12}
Nicolazzi, Ezequiel¹¹
Rosen, Benjamin D.¹³
Van Tassell, Curtis P.¹³
Guldbrandtsen, Bernt¹⁴
Sonstegard, Tad S.⁶
Tosser-Klopp, Gwenola³
Stella, Alessandra¹⁰
Rothschild, Max F.¹
Joost, Stéphane⁵
Crepaldi, Paola⁴

And 4 more

¹ Iowa State University, Department of Animal Science, Ames, IA, 50011, USA , Ames (United States)
² Technical University of Denmark (DTU), National Institute of Aquatic Resources, Lyngby, 2800, Denmark , Lyngby (Denmark)
³ GenPhySE, INRA, Université de Toulouse, INPT, ENVT, Castanet Tolosan, 31326, France , Castanet Tolosan (France)
⁴ Università degli Studi di Milano, Dipartimento di Medicina Veterinaria, Milan, 20133, Italy , Milan (Italy)
⁵ Ecole Polytechnique Fédérale de Lausanne (EPFL), Laboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), Lausanne, 1015, Switzerland , Lausanne (Switzerland)
⁶ Recombinetics Inc, St Paul, MN, 55104, USA , St Paul (United States)
⁷ Consiglio per la ricerca in agricoltura e l’analisi dell’economia agraria (CREA) - Research Centre for Animal Production and Acquaculture, Monterotondo, Roma, 00015, Italy , Monterotondo, Roma (Italy)
⁸ Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Campus Universitat Autonoma de Barcelona, Bellaterra, Barcelona, 08193, Spain , Barcelona (Spain)
⁹ Università Cattolica del S. Cuore, DIANA Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti, Piacenza, 29100, Italy , Piacenza (Italy)
¹⁰ Università Cattolica del S. Cuore, BioDNA Centro di Ricerca sulla Biodiversità e sul DNA Antico, Piacenza, 29100, Italy , Piacenza (Italy)
¹¹ Fondazione Parco Tecnologico Padano (PTP), Lodi, 26900, Italy , Lodi (Italy)
¹² São Paulo State University (UNESP), Department of Support, Production and Animal Health, School of Veterinary Medicine, Araçatuba, Brazil , Araçatuba (Brazil)
¹³ ARS USDA, Animal Genomics and Improvement Laboratory, Beltsville, MD, 20705, USA , Beltsville (United States)
¹⁴ Aarhus University, Center for Quantitative Genetics and Genomics, Tjele, 8830, Denmark , Tjele (Denmark)

Type

Published Article

Journal

Genetics Selection Evolution

Publisher

Springer (Biomed Central Ltd.)

Publication Date

Nov 19, 2018

Volume

Issue

Identifiers

DOI: 10.1186/s12711-018-0421-y

Source

Springer Nature

License

Green

Abstract

BackgroundSince 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.ResultsSeveral 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.ConclusionsThese 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.

Abstract