Genetic diversity and population structure among indigenous and imported goat breeds in Kenya

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Ruth W Waineina
Kiplangat Ngeno
Tobias O. Okeno
Evans D. Ilatsia


Population structure and relationship information among goats is critical for genetic improvement, utilization, and conservation. This study explored population structure and level of introgression among four goat breeds in Kenya: the indigenous Galla (n = 12) and three imported breeds, the Alpine (n = 29), Toggenburg (n = 31), and Saanen (n = 24). Genetic diversity was analyzed using four indices (polymorphic SNPs, mean allele frequency, observed and expected heterozygosity and inbreeding coefficient) within each breed. Population structure assessed using model-based clustering (ADMIXTURE) revealed four breeds according to their geographic regions in Kenya. Kenyan Alpine goats were the most admixed breed with about 10 % of its genome derived from Galla, 10 % and 6 % from Saanen and Toggenburg respectively. The association of Galla with other breeds was anticipated since the Galla breed was used as the founder population for crossbreeding with Saanen, Alpine and Toggenburg breeds. The relationship information evaluated by computing Reynolds genetic distance revealed five distinctive clusters: Alpine, Galla, Saanen, Toggenburg and some mixture of Alpine and Toggenburg. Saanen and Galla breeds seem to be the most genetically distinct among the sampled populations. The genetic variation among the goat populations observed will provide a good opportunity for sustainable utilization, conservation, and future genetic resource improvement programmes in goat breeds in Kenya.



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How to Cite
Waineina, R. W., Ngeno , K. ., Okeno, T. O. . and Ilatsia, E. D. (2021) “Genetic diversity and population structure among indigenous and imported goat breeds in Kenya”, Genetic Resources, 2(3), pp. 25–35. doi: 10.46265/genresj.EQFQ1540.
Original Articles

Ahuya, C. O. et al. (2009). “Performance of Toggenburg dairy goats in smallholder production systems of the eastern highlands of Kenya”. Small Ruminant Research 83(1-3), pp. 7–13. DOI:

Ajmone-Marsan, P. et al. (2014). “The characterization of goat genetic diversity: Towards a genomic approach”. Small Ruminant Research 121(1), pp. 58–72. DOI:

Alexander, D. H., J. Novembre, and K. Lange (2009). “Fast model-based estimation of ancestry in unrelated individuals”. Genome Research 19(9), pp. 1655–1664. DOI:

Andersson, Leif and Michel Georges (2004). “Domestic-animal genomics: deciphering the genetics of complex traits”. Nature Reviews Genetics 5(3), pp. 202–212. DOI:

Andolfatto, P (2001). “Adaptive hitchhiking effects on genome variability”. Current Opinion in Genetics & Development 11(6), pp. 635–641. DOI:

Anmarkrud, Jarl A et al. (2008). “Microsatellite evolution: Mutations, sequence variation, and homoplasy in the hypervariable avian microsatellite locus HrU10”. BMC Evolutionary Biology 8(1), pp. 138–138. DOI:

Aziz, M A (2010). “Present status of the world goat populations and their productivity”. Lohmann Information 45(2), pp. 42–52. URL:

Bett, R C (2009). Design and evaluation of breeding strategies for low input dairy goat production systems in Kenya.

Bett, R C et al. (2007). “Genetic improvement of the Kenya Dual Purpose Goat: Influence of economic values and prospects for a practical breeding programme”. Tropical Science 47(3), pp. 105–119. DOI:

Bett, R. C. et al. (2011). “Definition of breeding objectives and optimum crossbreeding levels for goats in the smallholder production systems”. Small Ruminant Research 96(1), pp. 16–24. DOI:

Brito, Luiz F. et al. (2017). “Genetic diversity and signatures of selection in various goat breeds revealed by genome-wide SNP markers”. BMC Genomics 18(1), pp. 229–229. DOI:

Chenyambuga, S. W. et al. (2004). “Genetic Characterization of Indigenous Goats of Sub-saharan Africa Using Microsatellite DNA Markers”. Asian-Australasian Journal of Animal Sciences 17(4), pp. 445–452. DOI:

Deshingkar, P et al. (2008). Livestock and poverty reduction in India: findings from the ODI Livelihood Options Project. Nairobi, Kenya. URL:

Eding, J. H. and G. Laval (1999). “Measuring genetic uniqueness in livestock”. In: Genebanks and the conservation of farm animal genetic resources. Ed. by J. K. Oldenbroek. Lelystad, the Netherlands: DLO-Institute for Animal Science and Health (ID-DLO), Instituut voor Veehouderij en Diergezondheid, Research Branch Zeist, pp. 33–58.

FAO (2011). Molecular genetic characterization of animal genetic resources. Vol. 9. FAO Animal Production and Health Guidelines. Rome. URL:

FAO (2012). Phenotypic characterization of animal genetic resources. Vol. 11. FAO Animal Production and Health Guidelines. Rome. URL:

Garnier-Géré, P and L Chikhi (2013). “Population Subdivision, Hardy–Weinberg Equilibrium and the Wahlund Effect.” In: eLS. Ed. by Ltd John Wiley & Sons. DOI:

Gizaw, S. et al. (2011). “Characterization and conservation of indigenous sheep genetic resources: A practical framework for developing countries”. In: ILRI Research Report. Vol. 27. Nairobi, Kenya: ILRI. URL:

Groeneveld, L. F. et al. (2010). “Genetic diversity in farm animals - a review”. Animal Genetics 41, pp. 6–31. DOI:

Herrero, M. et al. (2013). “The roles of livestock in developing countries”. Animal 7, pp. 3–18. DOI:

Hoshino, A A et al. (2012). “Microsatellites as tools for genetic diversity analysis”. In: Genetic Diversity in Microorganisms. Ed. by Mahmut Caliskan.

Jarne, Philippe and Pierre J.L. Lagoda (1996). “Microsatellites, from molecules to populations and back”. Trends in Ecology & Evolution 11(10), pp. 424–429. DOI:

Kohn, Michael H. et al. (2006). “Genomics and conservation genetics”. Trends in Ecology & Evolution 21(11), pp. 629–637. DOI:

Kosgey, I. S. and A. M. Okeyo (2007). “Genetic improvement of small ruminants in low-input, smallholder production systems: Technical and infrastructural issues”. Small Ruminant Research 70(1), pp. 76–88. DOI:

Krause, A K (2006). Breeding programmes for small ruminants in the tropics with special reference to the crossbreeding programme of the Dairy Goat Association of Kenya (DGAK). (PhD Thesis) Humboldt University, Berlin, Germany.

Laval, Guillaume, Magali SanCristobal, and Claude Chevalet (2002). “Measuring genetic distances between breeds: use of some distances in various short term evolution models”. Genetics Selection Evolution 34(4), pp. 1–27. DOI:

Letunic, Ivica and Peer Bork (2019). “Interactive Tree Of Life (iTOL) v4: recent updates and new developments”. Nucleic Acids Research 47(W1), W256–W259. DOI:

Mbuku, S. M. et al. (2015). “Optimum crossbreeding systems for goats in low-input livestock production system in Kenya”. Small Ruminant Research 123(1), pp. 55–61. DOI:

Mburu, Monica et al. (2014). “Factors Affecting Kenya Alpine Dairy Goat Milk Production in Nyeri Region”. Journal of Food Research 3(6), pp. 160–160. DOI:

McVean, Gil (2009). “A Genealogical Interpretation of Principal Components Analysis”. PLoS Genetics 5(10), e1000686–e1000686. DOI:

Nicoloso, L et al. (2015). “Genetic diversity of Italian goat breeds assessed with a medium-density SNP chip”. Genetics Selection Evolution 47(1). DOI:

O Ahuya, C, A M Okeyo, and F M Murithi (2006). “Productivity of cross-bred goats under smallholder production systems in the Eastern highlands of Kenya”. In: Small stock in development: Proceedings of a workshop on enhancing the contribution of small livestock to the livelihoods of resource-poor communities. URL:

Ogola, T. D. O., W. K. Nguyo, and I. S. Kosgey (2010). “Economic contribution and viability of dairy goats: implications for a breeding programme”. Tropical Animal Health and Production 42(5), pp. 875–885. DOI:

Ojango, J. M. K. et al. (2016). “System characteristics and management practices for small ruminant production in “Climate Smart Villages” of Kenya”. Animal Genetic Resources/Ressources génétiques animales/Recursos genéticos animales 58, pp. 101–110. DOI:

Onzima, R. B. et al. (2018). “Genome-wide population structure and admixture analysis reveals weak differentiation among Ugandan goat breeds”. Animal Genetics 49(1), pp. 59–70. DOI:

Palian, B and G Racokzi (1976). Sheep and goat development project, Kenya. Breeding and research - Technical report 3. Rome, Italy.

Peacock, C (2005). “Goats: Unlocking their potential for Africa’s farmers”. In: Proceedings of the Seventh Conference of Ministers Responsible for Animal Resources.

Peacock, C (2007). The goats model. A proven approach to reducing poverty among smallholder farmers in Africa by developing profitable goat enterprises and sustainable support services. URL:

Peacock, C. et al. (2011). “Practical crossbreeding for improved livelihoods in developing countries: The FARM Africa goat project”. Livestock Science 136(1), pp. 38–44. DOI:

Purcell, Shaun et al. (2007). “PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses”. The American Journal of Human Genetics 81(3), pp. 559–575. DOI:

Qanbari, Saber and Henner Simianer (2014). “Mapping signatures of positive selection in the genome of livestock”. Livestock Science 166, pp. 133–143. DOI:

Rege, J and A Okeyo (2011). “Improving our knowledge of tropical indigenous animal genetic resources”. In: Animal Genetics Training Resource Version 3 Training Module 2. Nairobi, Kenya; Uppsala, Sweden: ILRI. URL:

Scarpa, Riccardo et al. (2003). “Valuing indigenous cattle breeds in Kenya: an empirical comparison of stated and revealed preference value estimates”. Ecological Economics 45(3), pp. 409–426. DOI:

Shivairo, R S et al. (2013). “Production Challenges and Socio-Economic Impact of Dairy Goat Farming amongst Smallholder Farmers in Kenya”. Food Science and Quality Management 17, pp. 54–61.

Tosser-Klopp, Gwenola et al. (2014). “Design and Characterization of a 52K SNP Chip for Goats”. PLoS ONE 9(1), e86227–e86227. DOI:

Vignal, Alain et al. (2002). “A review on SNP and other types of molecular markers and their use in animal genetics”. Genetics Selection Evolution 34(3), pp. 275–305. DOI:

Visser, Carina et al. (2016). “Genetic Diversity and Population Structure in South African, French and Argentinian Angora Goats from Genome-Wide SNP Data”. PLOS ONE 11(5), e0154353–e0154353. DOI:

W Waineina, R et al. (2019). “Performance of Dairy Goat Breeds in different Production Systems in Kenya”. In: Proceedings of the Tanzania Society of Animal Production (TSAP), 42nd Scientific Conference, pp. 23–25.

Zheng, X. et al. (2012). “A high-performance computing toolset for relatedness and principal component analysis of SNP data”. Bioinformatics 28(24), pp. 3326–3328. DOI: