Inference of population of origin of individual animals from different Small East African goat populations using microsatellite markers
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Chenyambuga, S.W., Kifaro, G.C., Gwakisa, P.S., Hanotte, O. and Rege, J.E.O. 2006. Inference of population of origin of individual animals from different Small East African goat populations using microsatellite markers. In: Rege, J.E.O.; Nyamu, A.M.; Sendalo, D. (eds.). 2006. The role of biotechnology in animal agriculture to address poverty in Africa: Opportunities and challenges. Proceedings of the 4th All Africa Conference on Animal Agriculture and the 31st annual meeting of Tanzania Society for Animal Production, Arusha, Tanzania, 20-24 September 2005. Dar es Salaam, Tanzania: TSAP and Nairobi, Kenya: ILRI.
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A study was conducted to determine the population membership of individual goats from seven Small East African goat strains using microsatellite genotype information. The populations were Maasai, Ugogo, Sukuma, Ujiji, Coastal, Mbeya and Newala goats. The number of individuals per population ranged from 40 to 50 and for each individual, 19 microsatellite loci were analysed. Three approaches were used to determine the affiliation of individuals to their source populations: an allele sharing distance matrix which was used to construct a phylogenetic tree of individual animals based on inter-individual genetic distances, individual assignment tests using a Bayesian statistical approach and maximum likelihood approach. The phylogenetic tree with individual animals as the taxonomic units showed that only individuals from Coastal (83%) and Newala (94%) goats were assigned to their own population cluster. Individuals from Maasai, Ujiji, Ugogo, Sukuma, and Mbeya populations did not show population-specific clusters. For the Bayesian method, the proportion of individuals assigned into their correct population of origin ranged from 85.5% (for Sukuma and Ugogo) to 100% (for Newala and Mbeya). For the maximum likelihood method, the proportion of individuals correctly assigned to their source populations ranged from 64.6% (Ugogo goats) to 100% (Newala goats). The breed assignment test based on the Bayesian method was found to be more efficient in allocating individuals to their source populations, followed by the maximum likelihood method.