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Fipa cattle in the southwestern highlands of Tanzania: molecular characterization

Published online by Cambridge University Press:  03 October 2012

P.L. Mwambene ,
A.M. Katule ,
S.W. Chenyambuga ,
Y. Plante  and
P.A.A. Mwakilembe
P.L. Mwambene*
Affiliation:
Livestock Research Centre Uyole, Directorate of Research, Training and Extension, Ministry of Livestock and Fisheries Development, PO Box 6191, Mbeya, Tanzania
A.M. Katule
Affiliation:
Department of Animal Science and Production, Faculty of Agriculture, Sokoine University of Agriculture, PO Box 3004, Morogoro, Tanzania
S.W. Chenyambuga
Affiliation:
Department of Animal Science and Production, Faculty of Agriculture, Sokoine University of Agriculture, PO Box 3004, Morogoro, Tanzania
Y. Plante
Affiliation:
Canadian Animal Genetic Resources Program, Agriculture and Agri-Food Canada, 107 Science Place Saskatoon, Saskatchewan, Canada
P.A.A. Mwakilembe
Affiliation:
Livestock Research Centre Uyole, Directorate of Research, Training and Extension, Ministry of Livestock and Fisheries Development, PO Box 6191, Mbeya, Tanzania
*
Correspondence to: P.L. Mwambene, Livestock Research Centre Uyole, Directorate of Research, Training and Extension, Ministry of Livestock and Fisheries Development, Mbeya, Tanzania. email: piusmwambene@yahoo.co.uk
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Summary

This study aimed at characterising the genetic diversity of two Fipa cattle populations (Sumbawanga and Nkasi) of South-Western Tanzania, and establishing their genetic relationships with the other indigenous cattle strains (Tarime, Iringa red and Ankole) and Friesian cattle found in the area. The genetic diversity was analysed using 30 microsatellite markers. All the markers used were highly polymorphic. The Nkasi Fipa cattle exhibited the highest mean number of alleles (7.31) and mean genetic diversity (0.732) per locus, followed by Sumbawanga Fipa cattle with 7.10 mean number of alleles and 0.725 mean genetic diversity per locus, with the latter population having a very low mean inbreeding coefficient (FIS = 0.027). Three percent of the genetic diversity was due to differences among indigenous strains while the rest was due to differences among individuals within the strains. Small genetic distances (DA) were observed between Sumbawanga Fipa and Nkasi Fipa (0.032), Tarime (0.073), Iringa red (0.076) and Ankole cattle (0.086). As expected, the largest genetic distances were observed between the Friesian and all indigenous strains since this breed has a quite distinct genetic origin. In the assignment test, the proportion of animals from each group correctly assigned to their source population ranged from 55.3 percent (for Nkasi Fipa) to 100 percent (for Friesian). Despite the low genetic differentiation and genetic indistinctiveness of the Sumbawanga Fipa population from the other indigenous strains, its high genetic diversity, very low inbreeding coefficient and a threat emanating from population admixture with other indigenous strains underscore the importance of establishing appropriate conservation and management strategies for it.

Résumé

Cette étude visait à caractériser la diversité génétique de deux populations de bovins Fipa (Sumbawanga et Nkasi) en Tanzanie du Sud-Ouest, et à établir leurs relations génétiques avec les autres souches indigènes de bovins (Tarime, Iringa Red et Ankole) et avec les bovins Friesian présents dans la région. La diversité génétique a été analysée en utilisant 30 marqueurs microsatellites. Tous les marqueurs utilisés étaient hautement polymorphiques. Les bovins Fipa Nkasi présentaient le nombre moyen d'allèles (7,31) et la diversité génétique moyenne (0,732) par locus les plus élevés, suivis par les bovins Fipa Sumbawanga qui possédaient un nombre moyen d'allèles de 7,10, une diversité génétique moyenne par locus de 0,725 et un coefficient de consanguinité très faible (FIS = 0,027). Trois pour cent de la diversité génétique provenait des différences entre les souches indigènes tandis que le reste résultait des différences entre les animaux au sein des souches. Les distances génétiques (DA) étaient faibles entre les bovins Fipa Sumbawanga et Nkasi (0,032), Tarime (0.073), Iringa Red (0,076) et Ankole (0.086). Comme prévu, on a observé les distances génétiques les plus élevées entre toutes les souches indigènes et les bovins Friesian en raison des origines génétiques assez différentes de cette race. Lors du test d'attribution, la proportion d'animaux de chaque groupe qui ont été correctement assignés à leur population d'origine variait entre 55,3 pour cent (pour les Fipa Nkasi) et 100 pour cent (pour les Friesian). Malgré la faible différenciation génétique et le manque de traits génétiques distinctifs de la population de Fipa Sumbawanga par rapport aux autres souches indigènes, sa diversité génétique élevée, son coefficient de consanguinité très faible et la menace provenant du mélange génétique avec les autres souches indigènes mettent en évidence l'importance de planifier des stratégies adéquates pour sa conservation et sa gestion.

Resumen

Este estudio tuvo como objetivo caracterizar la diversidad genética de dos poblaciones bovinas de la raza Fipa (Sumbawanga y Nkasi) de la región suroccidental de Tanzania, y establecer sus relaciones genéticas con otras razas bovinas que se encuentran en la zona, tanto autóctonas (Tarime, roja Iringa y Ankole) como la Frisona. La diversidad genética se analizó utilizando 30 marcadores microsatélites. Todos los marcadores utilizados fueron altamente polimórficos. La población Nkasi Fipa presentó el mayor número medio de alelos (7,31) y la mayor diversidad genética media (0.732) por locus, seguida por la población Sumbawanga Fipa con un número medio de alelos de 7,10 y una diversidad genética media por locus de 0.725, mostrando esta última población un coeficiente promedio de consanguinidad muy bajo (FIS = 0,027). El 3% de la diversidad genética se debió a las diferencias entre razas autóctonas, mientras que el resto se debió a las diferencias entre individuos de la misma raza. Se observaron distancias genéticas (DA) pequeñas entre Sumbawanga Fipa y Nkasi Fipa (0.032), Tarime (0.073), roja Iringa (0.076) y Ankole (0,086). Como era de esperar, las mayores distancias genéticas se observaron entre la Frisona y todas las razas indígenas, ya que esta raza tiene un origen genético muy diferente. En la prueba de asignación, la proporción de animales de cada grupo asignado correctamente a su población de origen osciló entre 55,3 percent (para Nkasi Fipa) y el 100 percent (para la Frisona). A pesar de la baja diferenciación genética y de la indiferenciación genética de la población Sumbawanga Fipa respecto a las otras razas autóctonas, su alta diversidad genética, su muy bajo coeficiente de consanguinidad y la amenaza que representa el cruzamiento con otras razas indígenas resaltan la importancia de establecer estrategias adecuadas de conservación y de manejo de esta población.

Keywords

conservationgenetic diversityFipa populationindigenous strainsmicrosatellitesconservationdiversité génétiquepopulation de bovins Fipasouches indigènesmicrosatellitesconservacióndiversidad genéticapoblación Fiparazas indígenasmicrosatélites
Type
Research Article
Information
Animal Genetic Resources/Resources génétiques animales/Recursos genéticos animales , Volume 51 , December 2012 , pp. 31 - 43
Copyright
Copyright © Food and Agriculture Organization of the United Nations 2012

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References

Ciampolini, R., Cetica, V., Ciani, E., Mozzanti, E., Fosella, X., Marroni, F., Biagetti, M., Sebastiani, C., Papa, P., Filippini, G., Cianci, D. & Presciuttini, S. 2006. Statistical analysis of individual assignment tests among four cattle breeds using fifteen STR loci. J. Anim. Sci., 84: 11–19.Google Scholar
Dalvit, C., De Marchi, M., Dal Zotto, R., Zanetti, E., Meuwissen, T. & Cassandro, M. 2008. Genetic characterization of the Burlina cattle breed using microsatellites markers. J. Anim. Breed. Genet., 125: 137–144.Google Scholar
Falconer, D.S. & Mackay, T.F.C. 1996. Introduction to quantitative genetics, p. 463. 4th edn. Essex, UK: Longman Group.Google Scholar
Falush, D., Stephens, M. & Pritchard, J.K. 2003. Inference of population structure: extensions to linked loci and correlated allele frequencies. Genetics, 164: 1567–1587.Google Scholar
FAO. 2004. Secondary Guidelines for Development of National Farm Animal Genetic Resources Management Plans. Measurement of Domestic Animal Diversity (MoDAD): Recommended Microsatellite Markers. (available at http://dad.fao.org/cgi-bin/getblob.cgi?sid=-1,50006220).Google Scholar
FAO. 2007. The State of the World's Animal Genetic Resources for Food and Agriculture, edited by Barbara Rischkowsky & Dafydd Pilling. Rome. (available at http://www.fao.org/docrep/010/a1250e/a1250e00.htm).Google Scholar
FASS. 2010. Guide for the Care and Use of Agricultural Animals in Research and Teaching, 3rd edn, p. 177. 2441 Village Green Place Champaign, IL 61822, Federation of Animal Science Societies (FASS). (available at http://www.fass.org).Google Scholar
Guo, S.W. & Thompson, E.A. 1992. Performing the exact test of Hardy-Weinberg proportion for multiple alleles. Biometrics, 48: 361–372.Google Scholar
Ibeagha-Awemu, E.M., Jann, O.C., Weimann, C. & Erhardt, G. 2004. Genetic diversity, introgression and relationships among West/Central African cattle breeds. Genet. Sel. Evol., 36: 673–690.Google Scholar
Jordana, J., Alexandrino, P., Beja-Pereira, A., Bessa, I., Canon, J., Carretero, Y., Dunner, S., Laloe, D., Moazami-Goudarzi, K., Sanchez, A. & Ferrand, N. 2003. Genetic structure of eighteen local south European beef cattle breeds by comparative F-statistics analysis. J. Anim. Breed. Genet., 120: 73–87.Google Scholar
Kalinowski, S.T., Taper, M.L. & Marshall, T.C. 2007. Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment. Mol. Ecol., 16: 1099–1006.Google Scholar
Kugonza, D.R., Nabasirye, M., Mpairwe, D., Hanotte, O. & Okeyo, A.M. 2011. Productivity and morphology of Ankole cattle in three livestock production systems in Uganda. Anim. Genet. Resour. Inform., 48: 13–22 (available at http://www.fao.org/docrep/014/i2200t/i2200t.pdf).Google Scholar
Köhler-Rollefson, I. 2005. Indigenous Breeds, Local Communities. Documenting Animal Breeds and Breeding from a Community Perspective. Sadri, Rajasthan, India. ISBN No. 81-901624-1-1.Google Scholar
Laval, G., Iannuccelli, N., Legault, C., Milan, D., Groenen, M.A.M., Giuffra, E., Anderson, L., Nissen, P.H., Jorgensen, C.B., Beeckmann, H., Foulley, J.L., Chevalet, C. & Ollivier, L. 2000. Genetic diversity of eleven European pig breeds. Genet. Sel. Evol., 32: 187–203.Google Scholar
Machado, A.M., Antonio, A., Schuster, I., Martinez, M.L. & Campos, A.L. 2003. Genetic diversity of four cattle breeds using microsatellite markers. R. Bras. Zootec., 32: 93–98.Google Scholar
MacHugh, D.E., Shriver, M.D., Loftus, R.T., Cunningham, P. & Bradley, D.G. 1997. Microsatellite DNA variation and the evolution, domestication and phylogeography of Taurine and Zebu cattle (Bos taurus and Bos indicus). Genetics, 146: 1071–1086.Google Scholar
Moioli, B., Napolitano, F. & Catillo, G. 2004. Genetic diversity between Piedmontese, Maremmana, and Podolica cattle breeds. J. Hered., 95: 250–256.Google Scholar
Mukesh, M., Sodhi, M., Bhatia, S. & Mishra, B.P. 2004. Genetic diversity of Indian native cattle breeds as analyzed with 20 microsatellite loci. J. Anim. Breed. Genet., 121: 416–424.Google Scholar
Mwacharo, J.M., Okeyo, A.M., Kamande, G.K. & Rege, J.E.O. 2006. The small East African shorthorn zebu cows in Kenya. Linear body measurements. Trop. Anim. Health Prod., 38: 65–74.Google Scholar
Mwambene, P.L., Katule, A.M., Chenyambuga, S.W. & Mwakilembe, P.A.A. 2012. Fipa cattle in the southwestern highlands of Tanzania: socio-economic roles, traditional management practices and production constraints. Anim. Genet. Resour. doi:10.1017/S2078633612000112. (accepted).Google Scholar
Nei, M., Tajima, F. & Tateno, Y. 1983. Accuracy of estimated phylogenetic trees from molecular data II. Gene frequency data. J. Mol. Evol., 19: 153–170.Google Scholar
Notter, D.R. 1999. The importance of genetic diversity in livestock populations of the future. J. Anim. Sci., 80: 1776–1785.Google Scholar
Okomo, M. 1997. Characterization of the genetic diversity of East African cattle using microsatellite DNA markers. University of Nairobi, Nairobi, Kenya. 189 pp. (MSc thesis).Google Scholar
Okomo, M.A., Rege, J.E.O., Teale, A. & Hanotte, O. 1998. Genetic characterisation of indigenous East African cattle breeds using microsatellite DNA markers. In Proceedings of the 6th World Congress on Genetics Applied to Livestock Production, pp. 243–246, 11–16 January, 1998 Armidale, New Zealand. Vol. 27.Google Scholar
Okomo-Adhiambo, M. 2002. Characterization of genetic diversity in indigenous cattle of East Africa: use of micro satellite DNA techniques, pp. 10. Nairobi, Kenya, International Livestock Research Institute (ILRI).Google Scholar
Peakall, R. & Smouse, P.E. 2006. GENALEX 6.41: Genetic analysis in excel. Population genetic software for teaching and research. Mol. Ecol. Notes, 6: 288–295.Google Scholar
Petit, R.J., El Mousadik, A. & Pons, O. 1998. Identifying populations for conservation on the basis of genetic markers. Conserv. Biol., 12: 844–855.Google Scholar
Pritchard, J.K., Stephens, M. & Donnelly, P. 2000. Inference of population structure using multilocus genotype data. Genetics, 155: 945–959.Google Scholar
Raymond, M. & Rousset, F. 1995. An exact test for population differentiation. Evolution, 49: 1280–1283.Google Scholar
Rege, J.E.O. 1992. African animal genetic resources: their characterization, utilization and conservation. Rege, J.E.O., & Lipner, M.E. eds. Proceedings of the Research plan workshop held at ILCA, p. 164Addis Ababa, Ethiopia, 19–21 February 1992. ILCA (International Livestock Centre for Africa), Addis Ababa, Ethiopia.Google Scholar
Rege, J.E.O. & Tawah, C.L. 1999. The state of African cattle genetic resources II. Geographical distribution, characteristics and uses of present-day breeds and strains. Anim. Genet. Resour. Info., 26: 1–25. (available at ftp://ftp.fao.org/docrep/fao/012/x3565t/x3565t00.pdf).Google Scholar
Rehman, M.S. & Khan, M.S. 2009. Genetic diversity of Hariana and Hissar cattle from Pakistan using microsatellite analysis. Paskistan Vet. J., 29(2): 67–71.Google Scholar
Rendo, F., Iriondo, M., Jugo, B.M., Aguirre, A., Mazon, L.I., Vicario, A., Gomez, M. & Estonba, A. 2004. Analysis of the genetic structure of endangered bovine breeds from the Western Pyrenees using DNA microsatellite markers. Biochem. Genet., 42: 99–108.Google Scholar
Rousset, F. 2007. Genepop’007: a complete re-implementation of the GENEPOP software for Windows and Linux. Mol. Ecol., 8: 103–106.Google Scholar
Saitou, N. & Nei, M. 1987. The neighbour-joining method: a new method for reconstructing phylogenetic trees. Mol. Biol. Evol., 4: 406–425.Google Scholar
Sambrook, J., Fritsch, E.F. & Maniatis, T. 1989. Molecular Cloning – A Laboratory Manual. 2nd Edn., Cold Spring Harbor Laboratory Press, New York, USA.Google Scholar
Takezaki, N. & Nei, M. 1996. Genetic distances and reconstruction of phylogenetic trees from microsatellite DNA. Genetics, 144: 389–399.Google Scholar
Talle, S.B. 2004. Use of Molecular Genetic Technologies to Characterise the Genetic Variation in Norwegian and Icelandic Cattle. A PhD thesis submitted to the Department of Animal and Aquacultural Sciences, Agricultural University of Norway. 151 pp.Google Scholar
Tamura, K., Peterson, D., Peterson, N., Stecher, G., Nei, M. & Kumar, S. 2011. MEGA5: Molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance and maximum parsimony methods. Mol. Biol. Evol., 28: 2731–2739.Google Scholar
The United Republic of Tanzania (URT). 2006. National Livestock Policy, Ministry of Livestock and Fisheries Development, 60 p.Google Scholar
Toro, M. & Maki-Tanila, A. 2007. Genomics reveals domestication history and facilitates breed development. In Oldenbroek, K. ed. Utilization and conservation of farm animal genetic resources, pp. 75–102. Wageningen, The Netherlands, Wageningen Academic Publishers.Google Scholar
URT. 2006. The United Republic of Tanzania. National Livestock Policy, Ministry of Livestock and Fisheries Development, Dar es Salaam. 99pp (available at http://www.mifugo.go.tz).Google Scholar
Weir, B.S. & Cockerham, C.C. 1984. Estimating F-statistics with special regard to system of mating. Evolution, 38: 1358–1370.Google Scholar