title: Genetic Diversity and Population Structure in South African, French and Argentinian Angora Goats from Genome-Wide SNP Data.
abstract: The Angora goat populations in Argentina (AR), France (FR) and South Africa (SA) have been kept geographically and genetically distinct. Due to country-specific selection and breeding strategies, there is a need to characterize the populations on a genetic level. In this study we analysed genetic variability of Angora goats from three distinct geographical regions using the standardized 50k Goat SNP Chip. A total of 104 goats (AR: 30; FR: 26; SA: 48) were genotyped. Heterozygosity values as well as inbreeding coefficients across all autosomes per population were calculated. Diversity, as measured by expected heterozygosity (HE) ranged from 0.371 in the SA population to 0.397 in the AR population. The SA goats were the only population with a positive average inbreeding coefficient value of 0.009. After merging the three datasets, standard QC and LD-pruning, 15 105 SNPs remained for further analyses. Principal component and clustering analyses were used to visualize individual relationships within and between populations. All SA Angora goats were separated from the others and formed a well-defined, unique cluster, while outliers were identified in the FR and AR breeds. Apparent admixture between the AR and FR populations was observed, while both these populations showed signs of having some common ancestry with the SA goats. LD averaged over adjacent loci within the three populations per chromosome were calculated. The highest LD values estimated across populations were observed in the shorter intervals across populations. The Ne for the Angora breed was estimated to be 149 animals ten generations ago indicating a declining trend. Results confirmed that geographic isolation and different selection strategies caused genetic distinctiveness between the populations.
authors.affiliation: Department of Animal and Wildlife Sciences, University of Pretoria, Pretoria, South Africa.
authors.forename: Carina
authors.initials: C
authors.lastname: Visser
authors.affiliation: Department of Animal and Wildlife Sciences, University of Pretoria, Pretoria, South Africa.
authors.forename: Simon F
authors.initials: SF
authors.lastname: Lashmar
authors.affiliation: Department of Animal and Wildlife Sciences, University of Pretoria, Pretoria, South Africa.
authors.forename: Este
authors.initials: E
authors.lastname: Van Marle-Köster
authors.affiliation: Instituto de Genética "Ewald Favret", CICVyA-INTA, Hurlingham, Argentina.
authors.forename: Mario A
authors.initials: MA
authors.lastname: Poli
authors.affiliation: INRA, UMR1388 GenPhySe, CS52627, Castanet Tolosan, France.
authors.forename: Daniel
authors.initials: D
authors.lastname: Allain
mesh_terms: D000818:Animals; D001118:Argentina; D033481:Chromosomes, Mammalian / Q000235:genetics; D005602:France; D005819:Genetic Markers; D014644:Genetic Variation; D005828:Genetics, Population; D016678:Genome; D006041:Goats / Q000235:genetics*; D015810:Linkage Disequilibrium / Q000235:genetics; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D011156:Population Density; D025341:Principal Component Analysis; D015203:Reproducibility of Results; D013019:South Africa; D013223:Statistics as Topic
chemical_list: D005819:Genetic Markers