Genetic Structure of Nine Horse Populations

BURÓCZIOVÁ, M., ŘÍHA, J., ŽIDEK, R., TRANDŽÍK, J., JAKABOVÁ, D.: Genetic structure of nine horse populations. Acta univ. agric. et silvic. Mendel. Brun., 2008, LVI, No. 2, pp. 57–60 In the present study was estimate the genetic diversity and relationships among nine horses breeds in Czech and Slovak Republic. In conclusion, the main objective of study was to show the level of genetic distance among the horse breeds with diff erent history of breeding of each country. Furthermore, it should be clarifi ed whether these populations and subpopulations are distinct enough from each other to justify defi ning separate breeds. This research concerns the variability of microsatellite markers in genotypes of horse. We compared the genetic diversity and distance among nine horse breeds Czech and Slovak Warmblood both of Czech origin, Slovak Warmblood of Slovak origin, Hucul, Hafl ing, Furioso, Noriker, Silesian Noriker and Bohemian-Moravian Belgian Horse. In total, 932 animals were genotyped for 17 microsatellites markers (AHT4, AHT5, ASB2, HMS3, HMS6, HMS7, HTG4, HTG10, VHL20, HTG6, HMS2, HTG7, ASB17, ASB23, CA425, HMS1, LEX3) recommended by the International Society of Animal Genetics. In the diff erent population size, the allele frequencies, observed and expected heterozygosity, test for deviations from Hardy-Weinberg equilibrium and Polymorphism information content have been calculated for each breed. We analyzed genetic distance and diversity among them on the base of the dataset of highly polymorphic set of microsatellites representing all autozomes using set of PowerMarker v3.25 analysis tools and Structure 2.2. programme for results comparison. microsatellite, horse breeds, genetic diversity Introduct on genetic characterization is important to guard breed integrity and conserve breed identity. Furthermore, it is a prerequisite for managing genetic resources (Bjørnstad & Røed, 2002). Molecular techniques have been widely used to analyse phylogenetic relationships among various animal groups and diff erent breeds. Microsatellite loci comprise an attractive potential resource to determine population histories and evolutionary processes, as these loci permit simple and accurate typing in combination with high levels of polymorphism and widespread distribution in the genome. The usefulness of microsatellite markers has been documented in many previous equine population genetic studies (e.g. Cañon et al. 2000; Bjørnstad & Røed, 2001; Cunningham et al. 2001). The present study is focused on using microsatellite markers to characterise genetic structure of horse populations in Czech Republic and Slovak Republic. MATERIAL AND METHODS Hair, blood and sperm samples were collected from 932 unrelated individuals of Czech Warmblood, Slovak Warmblood, Slovak Warmblood origin from Slovakia, Hucul, Hafl ing, Furioso, Noriker, Silesian Noriker and Bohemian-Moravian Belgian Horse. Genomic DNA was isolated using the JETQUICK Tissue DNA Spin Kit and JETQUICK Blood & Cell Culture DNA Spin Kit (Genomed GmbH, Germany), by following the Protocol Handbook. Determination of microsatellites was performed using the PCR reaction with 17-plex horse genotyping kit designed by Applied Biosystems StockMarks® (Applied Biosystems, Foster City, CA, USA). The genotyping of microsatellite markers was performed on ABI PRISM 310 Genetic Analyzer (Applied Biosystems, Foster City, CA, USA) by fl uorescent fragment analysis and detected by so ware GeneScan® 3.7 NT. 58 M. Burócziová, J. Říha, R. Židek, J. Trandžík, D. Jakabová Alleles were asigned by GENOTYPER. Alleles were assingned to alphabetical symbols (B, C, F, G, H, I, J, K, L, M, N, O, P, Q, R, S). Genetic variability of each horse breeds was calculated as number of alleles (NA) per microsatellite, observed heterozygosity (Ho), expected heterozygosity (HE), Polymorphism information content (PIC) under Hardy-Weinberg equilibrium (Table I). PowerMarker v 3.25. was used for noted analysis. Nei’s standard distance was measured for graphs construction using PhyloDraw V0.82 programme and Structure 2.2 programme for fi gure construction using clusterisation and classifi cation methods. The breeds were divided into two subgroups warmbloods (Czech Warmblood, Slovak Warmblood, Slovak Warmblood origin from Slovakia, Hucul, Furioso) and coldbloods (Noriker, Silesian Noriker Bohemian-Moravian Belgian horse, Hafl ing). RESULTS The total number of alleles was 168 across the 17 microsatellites. The number of alleles per locus ranged from 6 (HMS6) to 15 (ASB17). In the data set of all individuals, the average number of alleles was 7.150. The average observed heterozygosity of warmblood horses ranged from 0.716 (Czech Warmblood) to 0.947 (Furioso), in the coldblood populations varied from 0.711 (Bohemian-Moravian Belgian Horse) to 0.781 (Table I). Gene diversity (He) varied in warmblood horses from 0.748 (Hucul) to 0.777 (Slovak Warmblood origin from Slovakia) and coldblood breeds from 0.686 (Hafl ing) to 0.722 (Noriker). The Polymorphism information content PIC ranged from 0.641 (Hafl ing) to 0.743 (Slovak Warmblood origin from Slovakia). I: Average number of alleles per locus, Heterozygosity Ho – observed. He – expected heterozygosity, Average polymorphism information content PIC Breed Number of Animals in Breed Average no. of alleles per locus Ho He PIC Czech Warmblood (CW) 234 8.294 0.716 0.759 0.724 Slovak Warmblood (SW) 234 7.882 0.730 0.750 0.710 Slovak Warmblood origin from Slovakia (SWSR) 96 8.058 0.921 0.777 0.743 Hucul (HUC) 124 8.235 0.757 0.748 0.716 Furioso (FUR) 37 6.059 0.947 0.755 0.721 Hafl ing (HFLG) 105 6.647 0.781 0.686 0.641 Noriker (NOR) 44 6.706 0.741 0.722 0.682 Silesian Noriker (SLN) 22 5.823 0.744 0.707 0.664 Bohemian-Moravian Belgian Horse (BMBH) 35 6.647 0.711 0.716 0.681 1: The diversity and population structure of nine horse breeds using Structure 2.2. programme. Each individual is represented by one thin vertical line and each breed is characterized by one colour. Genetic structure of nine horse populations 59 SW CW NOR BMBH SLN HFLG HUC FUR SWSR 2: The UPGMA dendograms was construced from Nei’s standard genetic distance (1972), summarizing genetic distance among 932 horses based on 17 microsatellites. 3: The neighbour-joining trees was construced from Nei’s standard genetic distance (1972) mine horse populations.