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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
agricultural and biological sciences
The characterization of goat genetic diversity: Towards a genomic approach
Small Ruminant Research, Volume 121, No. 1, Year 2014
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Description
The investigation of genetic diversity at molecular level has been proposed as a valuable complement and sometimes proxy to phenotypic diversity of local breeds and is presently considered as one of the FAO priorities for breed characterization. By recommending a set of selected molecular markers for each of the main livestock species, FAO has promoted the meta-analysis of local datasets, to achieve a global view of molecular genetic diversity. Analysis within the EU Globaldiv project of two large goat microsatellite datasets produced by the Econogene Consortium and the IAEA CRP-Asia Consortium, respectively, has generated a picture of goat diversity across continents. This indicates a gradient of decreasing diversity from the domestication centre towards Europe and Asia, a clear phylogeographic structure at the continental and regional levels, and in Asia a limited genetic differentiation among local breeds. The development of SNP panels that assay thousands of markers and the whole genome sequencing of livestock permit an affordable use of genomic technologies in all livestock species, goats included. Preliminary data from the Italian Goat Consortium indicate that the SNP panel developed for this species is highly informative. The existing panel can be improved by integrating additional SNPs identified from the whole genome sequence alignment of goats adapted to extreme climates. Part of this effort is being achieved by international projects (e.g. EU FP7 NextGen and 3SR projects), but a fair representation of the global diversity in goats requires a large panel of samples (i.e. as in the recently launched 1000 cattle genomes initiative). Genomic technologies offer new strategies to investigate complex traits difficult to measure. For example, the comparison of patterns of diversity among the genomes in selected groups of animals (e.g. adapted to different environments) and the integration of genome-wide diversity with new GIScience-based methods are able to identify molecular markers associated with genomic regions of putative importance in adaptation and thus pave the way for the identification of causative genes. Goat breeds adapted to different production systems in extreme and harsh environments will play an important role in this process. The new sequencing technologies also permit the analysis of the entire mitochondrial genome at maximum resolution. The complete mtDNA sequence is now the common standard format for the investigation of human maternal lineages. A preliminary analysis of the complete goat mtDNA genome supports a single Neolithic origin of domestic goats rather than multiple domestication events in different geographic areas. © 2014 Elsevier B.V.
Authors & Co-Authors
Ajmone-Marsan, Paolo
Italy, Piacenza
Università Cattolica Del Sacro Cuore, Campus Di Piacenza e Cremona
Colli, Licia
Italy, Piacenza
Università Cattolica Del Sacro Cuore, Campus Di Piacenza e Cremona
Han, Jianlin
China, Beijing
Chinese Academy of Agricultural Sciences
Kenya, Nairobi
International Livestock Research Institute Nairobi
Achilli, A.
Italy, Perugia
Università Degli Studi Di Perugia
Lancioni, Hovirag
Italy, Perugia
Università Degli Studi Di Perugia
Joost, Stéphane
Switzerland, Lausanne
École Polytechnique Fédérale de Lausanne
Crepaldi, Paola
Italy, Milan
Università Degli Studi Di Milano
Pilla, Fabio
Italy, Campobasso
Università Degli Studi Del Molise
Stella, Alessandra
Italy, Rome
Consiglio Nazionale Delle Ricerche
Italy, Lodi
Parco Tecnologico Padano
Taberlet, Pierre
France, Grenoble
Laboratoire D’écologie Alpine Leca
Boettcher, Paul J.
Italy, Rome
Food and Agriculture Organization of the United Nations
Negrini, Riccardo
Italy, Piacenza
Università Cattolica Del Sacro Cuore, Campus Di Piacenza e Cremona
Italy, Rome
Associazione Italiana Allevatori
Lenstra, Johannes A.
Netherlands, Utrecht
Universiteit Utrecht
Statistics
Citations: 52
Authors: 13
Affiliations: 13
Identifiers
Doi:
10.1016/j.smallrumres.2014.06.010
ISSN:
09214488
Research Areas
Genetics And Genomics
Maternal And Child Health
Study Approach
Systematic review