Аграрный вестник Урала № 07 (186) 2019Биология и биотехнологии
The study of the population structure and genetic diversity of hungarian mangalica breed of pigs based on microsatellites analysis
Predominant use in the present pig breeding the breeds of European and North American origin characterized by high levels of productivity, has led to the displacement of local breeds. The study of the allele pool of pigs of the Hungarian Mangalica breed, which was on the verge of extinction, but restored by the joint efforts of various specialists up to 7,000 individuals, it is of interest in the aspect in the genetic diversity conservation of endangered and small-numbered breeds. The aim of this work was to conduct microsatellite analysis to determine the population genetic parameters of the Hungarian Mangalica breed of pigs and assessing the degree of its differentiation with respect to groups of Large White, Landrace and Duroc breeds. Analysis of using the pairwise genetic distance matrix for the FST index showed a significant differentiation of Mangalica from Large White and Duroc breeds, and at the same time, some genetic similarity with Landrace one. Thus, it has been shown that pigs of the Mangalica breed are characterized by relatively high levels of allelic and genetic diversity, and the data obtained can be used to study the parameters of the genetic diversity of small pig breeds.
breeds of pig, Mangalica, genetic diversity, microsatellites
1. Mikhailova O. A. The history of breeding and the problem of conservation of rare and endangered species of pigs // Pig breeding. 2016. No. 1. Pp. 8–11.
2. Hungarian Mangalica: pros and cons of the breed [Electronic resource]. URL: https://vusadebke.com/fermerstvo/ghivotnovodstvo/svinyi/vengerskaya-mangalica.html (access date: 26.06.2019).
3. Georgescu S. E., Manea M. A., Dudu A., Costache M. Phylogenetic relationships of the mangalica swine breed inferred from mitochondrial DNA variation / // International Journal of Molecular Sciences. 2012. No. 13 (7). Pp. 8467–8481.
4. Flores L. [et al.] Genetic analysis of Mexican hairless pig populations // Journal of Animal Science. 2001. V. 79. Pp. 3021–3026.
5. Mahmoudi B. [et al.] Breed characteristics in Iranian native goat populations // Journal of Cell and Animal Biology. 2011. No. 5 (7). Pp. 129–134.
6. Mekuriaw G. [et al.] Review on current knowledge of genetic diversity of domestic goats (Capra hircus) identified by microsatellite loci: how those efforts are strong to support the breeding programs? // Journal of Life Science and Biomedicine. 2016. No. 6 (2). Pp. 22–32.
7. Zinovieva N. A. [et al.] Assessment of the contribution of different populations to the genetic diversity of pigs of the root of a large white breed // Agricultural biology. 2012. No. 6. Pp. 35–42.
8. Lugovoy S. I. Characterization of the gene pool of local breeds of pigs in Ukraine for the loci of the microsatellite DNA // Bulletin of the Novosibirsk State Agrarian University. 2013. No. 2 (27). Pp. 67–72.
9. Kharzinova V. R. [et al.] Local breed of pig: comparative analysis of allele-based analysis of microsatellites // Pig breeding. 2017. No. 1. Pp. 5–7.
10. Kharzinova V. R. [et al.] Population-genetic characteristic of pigs of breeds Large White, Landrace and Duroc using microsatellites // Husbandry. 2018. No. 4. Pp. 2–7.
11. Peakall R., Smouse P. E. GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research — an update // Bioinformatics. 2012. No. 28. Pp. 2537–2539.
12. Keenan K., McGinnity P., Cross T. F., Crozier W. W., Prodöhl P. A. diveRsity: An R package for the estimation and exploration of population genetics parameters and their associated errors // Methods in Ecology and Evolution. 2013. No. 4. Pp. 782–788.
13. Jombart T. Adegenet: a R package for the multivariate analysis of genetic markers // Bioinformatics. 2008. No. 24. Pp. 1403–1405.
14. Wickham H. ggplot2: Elegant graphics for data analysis. – New York : Springer-Verlag, 2009. – 216 p.
15. Jost L. GST and its relatives do not measure differentiation // Molecular Ecology. 2008. No. 17. Pp. 4015–4026.
16. Huson D. H., Bryant D. Application of phylogenetic networks in evolutionary studies // Molecular Biology and
Evolution. 2006. No. 23. Pp. 254–267.
17. R Core Team. R: a language and environment for statistical computing. R Foundation for statistical computing. – Vienna, 2012. – 2630 p.
Download article as PDF: