Evidence map›Paper›PMID 30449284›Full record

ArticleGenetics, selection, evolution : GSE2018

Genome-wide SNP profiling of worldwide goat populations reveals strong partitioning of diversity and highlights post-domestication migration routes.

Licia Colli, Marco Milanesi, Andrea Talenti, Francesca Bertolini, Minhui Chen, Alessandra Crisà, Kevin Gerard Daly, Marcello Del Corvo, Bernt Guldbrandtsen, Johannes A Lenstra and 15 more

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Article in Genetics, selection, evolution : GSE, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 98 papers.

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98citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

98 citing papers in PubMed.

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  8. Mapping genomic adaptation to environmental heterogeneity in Indian native goat populations through landscape genomics.Mammalian genome : official journal of the International Mammalian Genome Society · 2026
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  10. Review
  11. Signature of Selection Analysis Reveals Candidate Genes Related to Climate Adaptation and Production Traits in Lao Native Goats.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2026
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38 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

25 authors.

Licia ColliDIANA Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti, Università Cattolica del S. Cuore, Piacenza, Italy. licia.colli@unicatt.it.ORCID http://orcid.org/0000-0002-7221-2905
Marco MilanesiDIANA Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti, Università Cattolica del S. Cuore, Piacenza, Italy.ORCID http://orcid.org/0000-0001-6244-7455
Andrea TalentiDipartimento di Medicina Veterinaria, University of Milan, Milan, Italy.
Francesca BertoliniDepartment of Animal Science, Iowa State University, Ames, IA, USA.
Minhui ChenDepartment of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, Århus, Denmark.
Alessandra CrisàConsiglio per la Ricerca in Agricoltura e l'Analisi dell'Economia Agraria (CREA) - Research Centre for Animal Production and Aquaculture, Monterotondo, Rome, Italy.
Kevin Gerard DalyPopulation Genetics Lab, Smurfit Institute of Genetics, Trinity College of Dublin, Dublin, Ireland.
Marcello Del CorvoDIANA Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti, Università Cattolica del S. Cuore, Piacenza, Italy.
Bernt GuldbrandtsenDepartment of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, Århus, Denmark.
Johannes A LenstraFaculty of Veterinary Medicine, Utrecht University, Utrecht, Netherlands.ORCID http://orcid.org/0000-0003-1745-7739
Benjamin D RosenAnimal Genomics and Improvement Laboratory, Agricultural Research Service, United States Department of Agriculture, Beltsville, MD, USA.ORCID http://orcid.org/0000-0001-9395-8346
Elia VajanaDIANA Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti, Università Cattolica del S. Cuore, Piacenza, Italy.
Gennaro CatilloConsiglio per la Ricerca in Agricoltura e l'Analisi dell'Economia Agraria (CREA) - Research Centre for Animal Production and Aquaculture, Monterotondo, Rome, Italy.
Stéphane JoostLaboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Ezequiel Luis NicolazziFondazione Parco Tecnologico Padano, Lodi, Italy.
Estelle RochatLaboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Max F RothschildDepartment of Animal Science, Iowa State University, Ames, IA, USA.
Bertrand ServinGenPhySE, INRA, Université de Toulouse, INPT, ENVT, 31326, Castanet Tolosan, France.
Tad S SonstegardRecombinetics Inc., Saint Paul, MN, USA.
Roberto SteriConsiglio per la Ricerca in Agricoltura e l'Analisi dell'Economia Agraria (CREA) - Research Centre for Animal Production and Aquaculture, Monterotondo, Rome, Italy.
Curtis P Van TassellAnimal Genomics and Improvement Laboratory, Agricultural Research Service, United States Department of Agriculture, Beltsville, MD, USA.ORCID http://orcid.org/0000-0002-8416-2087
Paolo Ajmone-MarsanDIANA Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti, Università Cattolica del S. Cuore, Piacenza, Italy.
Paola CrepaldiDipartimento di Medicina Veterinaria, University of Milan, Milan, Italy.
Alessandra StellaFondazione Parco Tecnologico Padano, Lodi, Italy.
AdaptMap Consortium

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGoat populations that are characterized within the AdaptMap project cover a large part of the worldwide distribution of this species and provide the opportunity to assess their diversity at a global scale. We analysed genome-wide 50 K single nucleotide polymorphism (SNP) data from 144 populations to describe the global patterns of molecular variation, compare them to those observed in other livestock species, and identify the drivers that led to the current distribution of goats.

resultsA high degree of genetic variability exists among the goat populations studied. Our results highlight a strong partitioning of molecular diversity between and within continents. Three major gene pools correspond to goats from Europe, Africa and West Asia. Dissection of sub-structures disclosed regional gene pools, which reflect the main post-domestication migration routes. We also identified several exchanges, mainly in African populations, and which often involve admixed and cosmopolitan breeds. Extensive gene flow has taken place within specific areas (e.g., south Europe, Morocco and Mali-Burkina Faso-Nigeria), whereas elsewhere isolation due to geographical barriers (e.g., seas or mountains) or human management has decreased local gene flows.

conclusionsAfter domestication in the Fertile Crescent in the early Neolithic era (ca. 12,000 YBP), domestic goats that already carried differentiated gene pools spread to Europe, Africa and Asia. The spread of these populations determined the major genomic background of the continental populations, which currently have a more marked subdivision than that observed in other ruminant livestock species. Subsequently, further diversification occurred at the regional level due to geographical and reproductive isolation, which was accompanied by additional migrations and/or importations, the traces of which are still detectable today. The effects of breed formation were clearly detected, particularly in Central and North Europe. Overall, our results highlight a remarkable diversity that occurs at the global scale and is locally partitioned and often affected by introgression from cosmopolitan breeds. These findings support the importance of long-term preservation of goat diversity, and provide a useful framework for investigating adaptive introgression, directing genetic improvement and choosing breeding targets.

Indexed as

Animal MigrationDomesticationGene FlowPolymorphism, Single NucleotideAfricaAnimalsAsiaBreedingEuropeGenetic VariationGenomeGenotypeGoatsPhylogeography

Identifiers

PMID30449284
PMCPMC6240949

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.