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Assessment of the genetic variability using pedigree analysis of the Sahiwal breed in Kenya

Published online by Cambridge University Press:  03 January 2017

S. Mwangi ,
T.K. Muasya ,
E.D. Ilatsia  and
A.K. Kahi
S. Mwangi
Affiliation:
Animal Breeding and Genomics Group, Department of Animal Sciences, Egerton University, P.O. Box 536, 20115 Egerton, Kenya
T.K. Muasya*
Affiliation:
Animal Breeding and Genomics Group, Department of Animal Sciences, Egerton University, P.O. Box 536, 20115 Egerton, Kenya
E.D. Ilatsia
Affiliation:
Kenya Agricultural and Livestock Research Organisation, Dairy Research Institute P.O. Box 25, 20117 Naivasha, Kenya
A.K. Kahi
Affiliation:
Animal Breeding and Genomics Group, Department of Animal Sciences, Egerton University, P.O. Box 536, 20115 Egerton, Kenya
*
Correspondence to: T.K. Muasya, Animal Breeding and Genomics Group, Department of Animal Sciences, Egerton University, P.O. Box 536, 20115 Egerton, Kenya. email: muasyakt@yahoo.com
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Summary

Pedigree analysis using genealogical information of 18 315 animals born between 1949 and 2008 was done to quantify genetic variability of the Sahiwal population in Kenya. Generation intervals for sire pathways were longer than dam pathways and increased over year periods, from about 4–16 years. The later was due to use of old bulls for breeding in the last 2 year groups and cessation of progeny testing in the year 2000. Average inbreeding level in last year period studied was 1.2 percent. Genetic variability of the population as assessed based on gene origin statistics decreased over the years. The ratio of effective number of founders to founders of 0.06 showed unequal contribution of founders to the reference population. However, since the founding population, ancestors contributed equally as shown by the ratio of fe/fa of 0.94, which could also be due to lack of effective selection in this population. The ratio of fg/fa of 0.63 indicated genetic loss of genetic variability occurred through genetic drift in the Kenyan Sahiwal population. The small number of ancestors (16) that accounted for 50 percent of the total variation in the reference population suggested overuse of a small number of some animals as parents over generations. The smaller ratio of fg/fe compared with fa/fe also confirms loss of genetic variability in the population by genetic drift than bottlenecks. Therefore the breeding strategy for the Sahiwal population in Kenya should incorporate tools that balance rate of genetic gain and the future rate of inbreeding.

Résumé

Une analyse généalogique a été réalisée avec les données de 18 315 animaux nés entre 1949 et 2008 dans le but de quantifier la variabilité génétique de la population Sahiwal au Kenya. Les intervalles générationnels ont été plus longs sur la voie paternelle que sur la voie maternelle et se sont allongés au cours des années, d'environ 4 ans à 16 ans. Ceci a été dû à l'utilisation de vieux mâles pour la reproduction dans les deux dernières périodes d'années et à l'arrêt du contrôle de la descendance en l'an 2000. Le niveau moyen de consanguinité dans la dernière période étudiée a été de 1.2 pour cent. La variabilité génétique de la population, évaluée au moyen de statistiques sur l'origine des gènes, a diminué au fil des années. Le rapport entre le nombre effectif de fondateurs et les fondateurs a été de 0.06, ce qui met en évidence une contribution inégale des fondateurs à la population de référence. Cependant, depuis la population fondatrice, les ancêtres ont contribué équitablement, comme reflété par le rapport fe/fa de 0.94, qui pourrait aussi être dû à un manque de sélection efficace dans cette population. Le rapport fg/fa de 0.63 indique une perte de variabilité génétique causée par dérive génétique dans la population Sahiwal du Kenya. Le faible nombre d'ancêtres (16) expliquant 50 pour cent de la variation totale dans la population de référence suggère l'utilisation excessive en tant que parents d'un petit nombre d'animaux au cours de plusieurs générations. De même, le fait que le rapport fg/fe soit inférieur au rapport fa/fe confirme la perte de variabilité génétique dans la population par dérive génétique plutôt que par goulots d'étranglement génétique. Par conséquent, la stratégie de sélection pour la population Sahiwal au Kenya devrait intégrer des outils permettant d'équilibrer le taux de gain génétique et le taux futur de consanguinité.

Resumen

Se llevó a cabo un análisis genealógico con datos de 18 315 animales nacidos entre 1949 y 2008 con el fin de cuantificar la variabilidad genética de la población Sahiwal en Kenya. Los intervalos generacionales por la vía paterna fueron mayores que por la vía materna y aumentaron con el paso del tiempo, desde aproximadamente 4 a 16 años. Esto último se debió al uso de machos viejos para la cría en las dos últimas franjas de años y al cese del testaje de la progenie en el año 2000. El nivel medio de endogamia en el último periodo de tiempo estudiado fue del 1.2 por ciento. La variabilidad genética de la población, determinada en base a estadísticas del origen de los genes, disminuyó a lo largo de los años. El ratio entre el número efectivo de fundadores y los fundadores fue de 0.06, lo cual muestra una contribución desigual de los fundadores a la población de referencia. Sin embargo, desde la población fundadora, los ancestros contribuyeron equitativamente, tal como refleja el ratio fe/fa de 0.94, que también podría deberse a una falta de selección eficaz en esta población. El ratio fg/fa de 0.63 indicó una pérdida de variabilidad genética ocurrida por deriva genética en la población Sahiwal keniana. El pequeño número de ancestros (16) responsable del 50 por ciento de la variación total en la población de referencia hace pensar en un uso excesivo de un reducido número de animales como progenitores a lo largo de varias generaciones. También el hecho de que el ratio fg/fe sea menor que el ratio fa/fe confirma la pérdida de variabilidad genética en la población por deriva genética más que por cuellos de botella. En consecuencia, la estrategia reproductiva para la población Sahiwal en Kenya debería incorporar herramientas que equilibren la tasa de ganancia genética y la tasa futura de endogamia.

Keywords

effective population sizegenealogygenetic diversityinbreedingoptimum contributiontaille effective de la populationgénéalogiediversité génétiqueconsanguinitécontribution optimaletamaño efectivo de poblacióngenealogíadiversidad genéticaendogamiacontribución óptima
Type
Research Article
Information
Animal Genetic Resources/Resources génétiques animales/Recursos genéticos animales , Volume 59 , December 2016 , pp. 7 - 14
Copyright
Copyright © Food and Agriculture Organization of the United Nations 2016 

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References

Ballou, J.D. & Lacy, R.C. 1995. Identifying genetically important individuals for management of genetic variation in pedigreed populations. In Ballou, J.D., Gilpin, M. & Foose, T.J., eds. Population management for survival and recovery: analytical methods and strategies in small population management, pp. 76–111. New York, Columbia University Press.Google Scholar
Battagin, M., Penasa, M., Pretto, D. & Cassandro, M. 2010. Pedigree analysis of Burlina cattle population. Acta Agraria Kaposváriensis, 14(2): 161–165.Google Scholar
Boichard, D., Maignel, L. & Verrier, E. 1997. The value of using probabilities of gene origin to measure genetic variability in a population. Genet. Sel. Evol., 29: 5–23.CrossRefGoogle Scholar
Bouquet, A., Venot, E., Laloë, D., Forabosco, F., Fogh, A., Pabiou, T., Moore, K., Eriksson, J.A., Renand, G. & Phocas, F. 2011. Genetic structure of the European Charolais and Limousin cattle metapopulations using pedigree analyses. J. Anim. Sci., 89: 1719–1730.CrossRefGoogle ScholarPubMed
Bozzi, R., Franci, O., Forabosco, F., Pugliese, C., Crovetti, A. & Filippini, F. 2006. Genetic variability in three Italian beef cattle breeds derived from pedigree information. Ital. J. Anim. Sci., 5: 129–137.CrossRefGoogle Scholar
Carneiro, P.L.S., Malhado, C.H.M., Euclides, R.F., Torres, R.A., Lopes, P.S., Carneiro, A.P.S. & Cunha, E.E. 2006. Oscilação genética em populações submetidas a métodos de seleção tradicionais e associados a marcadores moleculares. Revista Brasileira de Zootecnia, 35: 84–91.CrossRefGoogle Scholar
Cortés, O., Sevane, N., Baro, J.A. & Cañón, J. 2014. Pedigree analysis of a highly fragmented population, the Lidia cattle breed. Livest. Sci., 167: 1–8.CrossRefGoogle Scholar
Daetwyler, H.D., Villanueva, B., Bijma, P. & Woolliams, J.A. 2007. Inbreeding in genome-wide selection. J. Anim. Breeding Genet., 124: 369–376.CrossRefGoogle ScholarPubMed
Danchin-Burge, C., Leroy, G., Brochard, M., Moureaux, S. & Terrier, E. 2012. Evolution of the genetic variability of eight French dairy cattle breeds assessed by pedigree analysis. J. Anim. Breeding Genet., 129: 206–217.CrossRefGoogle ScholarPubMed
Falconer, D.S. & Mackay, T.F.C. 1996. Introduction to quantitative genetics. London, UK, Longman.Google Scholar
FAO. 1998. Secondary guidelines for development of national farm animal genetic resources management plans: management of small populations at risk. Rome, Italy, FAO (available at http://www.fao.org/docrep).Google Scholar
Faria, F.J.C., Vercesi Filho, A.E., Madalena, F.E. & Josahkian, L.A. 2002 Pedigree analysis. In Proceedings of the Seventh World Congress on Genetics Applied to Livestock Production, 19–23 August 2002, Montpellier, France, pp. 26–29Google Scholar
Faria, F.J.C., Madalena, F.E. & Josahkian, L.A. 2009. Pedigree analysis in the Brazilian Zebu breeds. J. Anim. Breeding Genet., 126(2): 148–153.CrossRefGoogle ScholarPubMed
Fernandez, J., Meuwissen, T.H.E., Toro, M.A. & Maki-Tanila, A. 2011. Management of genetic diversity in small farm animal populations. Animal, 5: 1684–1698.CrossRefGoogle ScholarPubMed
Filho, J.C.R., Lopes, P.S., Verneque, R.S., Torres, R.A., Teodoro, R.L. & Carneiro, P.L.S. 2010. Population structure of Brazilian Gyr dairy cattle. Revista Brasileira de Zootecnia, 39(12): 2640–2645 (available at http://www.scielo.br/pdf/rbz/v39n12/a12v39n12.pdf).CrossRefGoogle Scholar
Franklin, I.R. & Frankham, R. 1998. How large must populations be to retain evolutionary potential? Anim. Conserv., 1: 69–70 (available at http://www.ph.eau.ee/~lki/kalakasv/consgen/Franklin_1998.pdf).CrossRefGoogle Scholar
Goyache, F., Gutiérrez, J.P., Fernandez, I., Gomez, E., Alvarez, I., D?az, J. & Royo, L.J. 2003. Using pedigree information to monitor genetic variability of endangered populations: the Xalda sheep breed of Asturias as an example. J. Anim. Breeding Genet., 120: 95–105.CrossRefGoogle Scholar
Gutiérrez, J.P. & Goyache, F. 2005. A note on ENDOG: a computer program for analysing pedigree information. J. Anim. Breeding Genet., 122: 172–176.CrossRefGoogle ScholarPubMed
Gutiérrez, J.P., Altarriba, J., Diaz, C., Quintanilla, R., Cânon, J. & Piedrafita, J. 2003. Pedigree analysis of eight Spanish beef cattle breeds. Genet. Sel. Evol., 35: 43–63.CrossRefGoogle ScholarPubMed
Gutierrez, J.P., Cervantes, I. & Goyache, F. 2009. Improving the estimation of realized effective population sizes in farm animals. J. Anim. Breeding Genet., 126: 327–332.CrossRefGoogle ScholarPubMed
Hammami, H., Croquet, C., Stoll, J., Rekik, B. & Gengler, N. 2007. Genetic diversity and joint pedigree analysis of two importing Holstein populations. J. Dairy Sci., 90: 3530–3541.CrossRefGoogle ScholarPubMed
Hill, W.G. 2000. Maintenance of quantitative genetic variation in animal breeding programmes. Livest. Prod. Sci., 63: 99–109.CrossRefGoogle Scholar
Ilatsia, E.D., Muasya, T.K., Muhuyi, W.B. & Kahi, A.K. 2007. Genetic and phenotypic parameters and annual trends for milk production and fertility traits of the Sahiwal cattle in semi arid Kenya. Trop. Anim. Health Prod., 39: 37–48.CrossRefGoogle ScholarPubMed
Ilatsia, E.D., Roessler, R., Kahi, A.K., Piepho, H.P. & Zarate, A.V. 2011. Evaluation of basic and alternative breeding programs for Sahiwal cattle genetic resources in Kenya. Anim. Prod. Sci., 51: 682–694.CrossRefGoogle Scholar
Kahi, A.K., Nitter, G. & Gall, C.F. 2004. Developing breeding schemes for pasture based dairy production systems in Kenya. II. Evaluation of alternative objectives and schemes using a two-tier open nucleus and the young bull system. Livest. Prod. Sci., 88: 179–192.CrossRefGoogle Scholar
Kamiti, D.N. 2014. Evaluation of genetic diversity of Sahiwal cattle in Kenya . Egerton University, Genetics. Vol. 109, pp. 364–373. (M.Sc. Thesis).Google Scholar
Lacy, R.C. 1989. Analysis of founder representation in pedigrees: founder equivalents and founder genome equivalents. Zoo Biol., 8: 111–123.CrossRefGoogle Scholar
Lacy, R.C. 1995. Clarification of genetic terms and their use in the management of captive populations. Zoo Biol., 14: 565–578.CrossRefGoogle Scholar
Maignel, L., Boichard, D. & Verrier, E. 1996. Genetic variability of French dairy breeds estimated from pedigree information. InterBull Bulletin, 14: 49–54.Google Scholar
Malhado, C.H.M., Malhado, A.C.M., Carneiro, P.L.S., Ramos, A.A., Ambrosini, D.P. & Pala, A. (2012). Population structure and genetic variability in the Murrah dairy breed of water buffalo in Brazil accessed via pedigree analysis. Trop. Anim. Health Prod., 44: 1891–1897 (available at http://doi.org/10.1007/s11250-012-0153-x).CrossRefGoogle ScholarPubMed
McParland, S., Kearney, J.F., Rath, M. & Berry, D.P. 2007. Inbreeding trends and pedigree analysis of Irish dairy and beef cattle populations. J. Anim. Sci., 85: 322–331.CrossRefGoogle Scholar
Melka, M.G., Stachowicz, K., Miglior, F. & Schenkel, F.S. 2013. Analyses of genetic diversity in five Canadian dairy breeds using pedigree data. J. Anim. Breeding Genet., 130: 476–486.CrossRefGoogle ScholarPubMed
Meuwissen, T.H.E. & Sonesson, A.K. 1998. Maximizing the response of selection with a predefined rate of inbreeding: overlapping generations. J. Anim. Sci., 76(10): 2575–2583.CrossRefGoogle ScholarPubMed
Meuwissen, T.H.E. & Woolliams, J. 1994. Effective sizes of livestock populations to prevent a decline in fitness. Theoret. Appl. Genet., 89: 1019–1026.CrossRefGoogle ScholarPubMed
Meyn, K. & Wilkins, J.V. 1974. Breeding for milk in Kenya with particular reference to the Sahiwal stud. World Anim. Rev., 11: 24–30.Google Scholar
Muasya, T.K., Kariuki, J.N. & Muia, J.M.K. 2011. Population structure of the Sahiwal breed in Kenya. Livest. Res. Rural Dev., 23, Article #186 (available at http://www.lrrd.org/lrrd23/9/muas23186.htm).Google Scholar
Muasya, T.K., Peters, K.J. & Kahi, A.K. 2013. Breeding structure and genetic variability of the Holstein-Friesian dairy cattle population in Kenya. Anim. Genet. Resour., 52: 127–137.CrossRefGoogle Scholar
Muhuyi, W.B., Lokwaleput, I. & Sinkeet, S.N. 1999. Conservation and utilization of the Sahiwal cattle in Kenya. FAO Anim. Genet. Res. Inf., 26: 35–44.CrossRefGoogle Scholar
Nomura, T., Honda, T. & Mukai, F. 2001. Inbreeding and effective population size of Japanese Black cattle. J. Anim. Sci., 79: 366–370.CrossRefGoogle ScholarPubMed
Razook, A.G., Figueiredo, L.A., Bonilha Neto, L.M., Trovo, J.B.F., Packer, I.U., Pacola, L.J. & Cândido, J.G. 1993. Intensidades de seleção e repostas diretas e correlacionadas em 10 anos de progênies de bovinos das raças Nelore e Guzerá selecionadas para peso pós desmame. B. Indústr. Anim., 50: 147–163.Google Scholar
Schierenbeck, S., Reinhardt, F., Reentes, R., Simianer, H. & König, S. 2011. Identification of informative co-operator herds for progeny testing based on yield deviations. J. Dairy Sci., 94: 2071–2082.CrossRefGoogle Scholar
Sölkner, J., Filipcic, L. & Hampshire, N. 1998. Genetic variability of populations and similarity of subpopulations in Austrian cattle breeds determined by analysis of pedigrees. Anim. Sci., 67: 249–256.CrossRefGoogle Scholar
Sorensen, A.C., Sorensen, M.K. & Berg, P. 2005. Inbreeding in Danish dairy cattle breeds. J. Dairy Sci., 88: 1865–1872.CrossRefGoogle ScholarPubMed
Verneque, R.S., Reis Filho, J.C., Martinez, M.L., Lopes, P.S., Teodoro, R.L., Torres, R.A., Machado, M.A. & Peixoto, M.G.C.D. 2006. Population genetic structure of Brasilian Gir Dairy cattle. In Proceedings of the Eighth World Congress on Genetics Applied to Livestock Production, 13–18 August 2006, Belo Horizonte, Brazil, 01-91.Google Scholar
Vozzi, P.A., Marcondes, C.R., Magnabosco, C.U., Bezerra, L.A.F. & Lôbo, R.B. 2006. Structure and genetic variability in Nellore (Bos indicus) cattle by pedigree analysis. Genet. Mol. Biol., 29: 482–485.CrossRefGoogle Scholar
Weigel, K.A. & Lin, S.W. 2002. Controlling inbreeding by constraining the average relationship between parents of young bulls entering AI progeny test programs. J. Anim. Sci., 85: 2376–2383.Google ScholarPubMed