Genetic variability analysis of 26 sheep breeds in the Czech Republic.
Abstract
In this study, the intra- and inter-population level of genetic diversity of 26 transboundary and local sheep breeds reared in the Czech Republic was analysed. A total of 14,999 animals genotyped for 11 microsatellite markers were included to describe the gene pool of the breeds. The level of genetic diversity was derived from the proportion of heterozygous animals among and within breeds. The average polymorphic information content (0.745) and Shannon’s index (1.361) showed a high genetic variability of the applied set of genetic markers. The average observed heterozygosity (0.683 ± 0.009), as well as FIS index (-0.025 ± 0.004), pointed to a sufficient proportion of heterozygotes concerning the loss of genetic diversity. The deficit of heterozygotes was most evident in Cameroon sheep (FIS = 0.036). The Nei's genetic distances and Wright's FST indexes showed that the analysed breeds are genetically differentiated to separate clusters with Cameroon sheep as the most genetically distant breed. Individual variation accounted for 83.2 % of total diversity conserved across breeds, whereas 16.8 % of genetic similarity resulted from the inter-population reduction in heterozygosity.
Keywords: microsatellite analysis, genetic diversity, sheep, transboundary and local breed
References
Bravo, S. et al. (2019). Genetic diversity and phylogenetic relationship among araucana creole sheep and Spanish sheep breeds. Small Ruminant Research, 172, 23–30. https://doi.org/10.1016/j.smallrumres.2019.01.007
Chessa, B. et al. (2009). Revealing the history of sheep domestication using retrovirus integrations. Science, 324(5926), 532–536. https://doi.org/10.1126/science.1170587
Faigl, V. et al. (2012). Artificial insemination of small ruminants - A review. Acta Veterinaria Hungarica, 60(1), 115–129. https://doi.org/10.1556/AVet.2012.010
FAO. (2007). The State of the World’s Animal Genetic Resources for Food and Agriculture. Edited by D. P. Barbara Rischkowsky. Rome, Italy.
FAO. (2020). Domestic Animal Diversity Information System. Retrieved from http://www.fao.org/dad-is/transboundary-breed/en/
Gaouar, S. B. S., Kdidi, S. and Ouragh, L. (2016). Estimating population structure and genetic diversity of five Moroccan sheep breeds by microsatellite markers. Small Ruminant Research, 144, 23–27. https://doi.org/10.1016/j.smallrumres.2016.07.021
Hennink, S. and Zeven, A. C. (1990). The interpretation of Nei and Shannon-Weaver within population variation indices. Euphytica, 51(3), 235–240. https://doi.org/10.1007/BF00039724
Hoda, A. and Bytyqi, H. (2017). Genetic diversity of sheep breeds from Albania and Kosova by microsatellite markers and mtDNA. Albanian Journal of Agricultural Science, 13-17.
Jawasreh, K. et al. (2018). Genetic diversity and population structure of local and exotic sheep breeds in Jordan using microsatellites markers. Veterinary World, 11(6), 778–781. https://doi.org/10.14202/vetworld.2018.778-781
Jyotsana, B. et al. (2010). Genetic features of Patanwadi, Marwari and Dumba ssheep breeds (India) inferred bymicrosatellite markers. Small Ruminant Research, 93(1), 57–60. https://doi.org/10.1016/j.smallrumres.2010.03.008
Kalinowski, S. T., Taper, M. L. and Marshall, T. C. (2007). Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment. Molecular Ecology, 16(5), 1099–1106. https://doi.org/10.1111/j.1365-294x.2007.03089.x
Loukovitis, D. et al. (2016). Genetic diversity of Greek sheep breeds and transhumant populations utilizing microsatellite markers. Small Ruminant Research, 136, 238–242. https://doi.org/10.1016/j.smallrumres.2016.02.008
Mahmoud, A. H. et al. (2020). Genetic variability of sheep populations of Saudi Arabia using microsatellite markers. Indian Journal of Animal Research, 54(4), 409-412. http://dx.doi.org/10.18805/ijar.B-775
Moravčíková, N. et al. (2016). Genetic diversity of Old Kladruber and Nonius horse populations through microsatellite variation analysis. Acta Agriculturae Slovenica, Supplement 5, 45–49.
Naqvi, A. N. et al. (2017). Assessment of genetic diversity and structure of major sheep breeds from Pakistan. Small Ruminant Research, 148, 72–79. https://doi.org/10.1016/j.smallrumres.2016.12.032
Nei, M. (1978). Estimation of average heterozygosity and genetic distance from a small number of individuals. Genetics, 89(3), 583-590.
Neubauer, V. et al. (2015). Genetic diversity and population structure of Zackel sheep and other Hungarian sheep breeds. Archives Animal Breeding, 58(2), 343–50. https://doi.org/10.5194/aab-58-343-2015
Niu, L. L. et al. (2012). Genetic variability and individual assignment of Chinese indigenous sheep populations (Ovis aries) using microsatellites. Animal Genetics, 43(1), 108–111. https://doi.org/10.1111/j.1365-2052.2011.02212.x
Ocampo, R. J. et al. (2017). Genetic characterization of Colombian indigenous ssheep. Revista Colombiana de Ciencias Pecuarias, 30(2), 116–25. http://dx.doi.org/10.17533/udea.rccp.v30n2a03
Othman, O. E. M. et al. (2016). Sheep diversity of five Egyptian breeds: Genetic proximity revealed between desert breeds: Local sheep breeds diversity in Egypt. Small Ruminant Research, 144, 346–352. https://doi.org/10.1016/j.smallrumres.2016.10.020
Peakall, R. and Smouse, P. E. (2012). GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research-an update. Bioinformatics, 28(19), 2537–2539. https://dx.doi.org/10.1093/bioinformatics/bts460
Peakall, R. and Smouse, P. E. (2006). Genalex 6: genetic analysis in Excel. Population genetic software for teaching and research. Molecular Ecology Notes, 6(1), 288–295. https://doi.org/10.1111/j.1471-8286.2005.01155.x
Peter, C. et al. (2007). Genetic diversity and subdivision of 57 European and Middle-Eastern ssheep breeds. Animal Genetics, 38(1), 37–44. https://doi.org/10.1111/j.1365-2052.2007.01561.x
Pichler, R. et al. (2017). Short tandem repeat (STR) based genetic diversity and relationship of domestic sheep breeds with primitive wild Punjab Urial sheep (Ovis vignei punjabiensis). Small Ruminant Research, 148, 11–21. https://doi.org/10.1016/j.smallrumres.2016.12.024
Qwabe, S. O., van Marle-Köster, E. and Visser, C. (2013). Genetic diversity and population structure of the endangered Namaqua Afrikaner ssheep. Tropical Animal Health and Production, 45(2), 511–516. https://doi.org/10.1007/s11250-012-0250-x
Raoul, J. and Elsen, J.-M. (2020). Effect of the rate of artificial insemination and paternity knowledge on the genetic gain for French meat sheep breeding programs. Livestock Science, 232, 103932. https://doi.org/10.1016/j.livsci.2020.103932
Raymond, M. and Rousset, F. (1995). GENEPOP (Version 1.2): Population genetics software for exact tests and ecumenicism. Journal of Heredity, 86(3), 248–249. https://doi.org/10.1093/oxfordjournals.jhered.a111573
Rousset, F. (2008). Genepop’007: a complete re-implementation of the GENEPOP software for Windows and Linux. Molecular Ecology Resources, 8(1), 103–106. https://doi.org/10.1111/j.1471-8286.2007.01931.x
Taberlet, P. et al. (2008). Are cattle, sheep, and goats endangered species? Molecular Ecology, 17(1), 275–284. https://doi.org/10.1111/j.1365-294x.2007.03475.
Tolone, M. et al. (2012). Genetic diversity and population structure of Sicilian sheep breeds using microsatellite markers. Small Ruminant Research, 102(1), 18-25. https://doi.org/10.1016/j.smallrumres.2011.09.010
Vahidi, S. M. F. et al. (2016). Multilocus genotypic data reveal high genetic diversity and low population genetic structure of Iranian indigenous sheep. Animal Genetics, 47(4), 463–470. https://doi.org/10.1111/age.12429
Weir, B. S. and Cockerham, C. C. (1984). Estimating F-statistics for the analysis of population structure. Evolution, 38(6), 1358–1370. https://doi.org/10.2307/2408641
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