We propose the first comprehensive in-depth study monitoring horses in the Czech Republic. We scanned 9,289 animals from 44 populations for 17 equine STRs. Other equids analysed involved Equus przewalskii and Equus asinus. The total of 228 different alleles were detected, with the mean number of 13.4 per locus. The highest allelic richness (AR) was found in the Welsh Part Bred (6.01), followed by the Camargue (5.93) and Czech Sport Pony (5.91), whereas the Friesian exhibited the lowest AR (3.06). Interpopulation differences explained approximately nine per cent of the total genetic diversity. Reynold's genetic distance ranged from 0.003 between the Czech Warmblood and the Slovak Warmblood to 0.404 between the Friesian and donkeys. Close genetic proximity between the Silesian Noriker and Noriker was revealed. The Moravian Warmblood was better differentiated and more distant from the Czech Warmblood than the Kinsky Horse and retained the original genes of the old Austro-Hungarian tribes. A high gene flow level and a lack of genetic structure were found in the seven studied populations. Despite the historical bottlenecks and previous inbreeding, the Czech-Moravian Belgian Horse, Hucul, Old Kladruber Horse and Silesian Noriker did not suffer a serious loss of genetic diversity due to genetic drift/low effective population size. A NeighborNet dendrogram revealed breeds not classified in their groups according to the nomenclature (the Friesian, Hafling and Merens).

Based on a data set comprising 2879 animals and 17 nuclear microsatellite DNA markers, we propose the most comprehensive in-depth study mapping the genetic structure and specifying the assignment success rates in horse breeds at the Czech population scale. The STRUCTURE program was used to perform systematic Bayesian clustering via the Markov chain Monte Carlo estimation, enabling us to explain the population stratification and to identify genetic structure patterns within breeds worldwide. In total, 182 different alleles were found over all the populations and markers, with the mean number of 10.7 alleles per locus. The expected heterozygosity ranged from 0.459 (Friesian) to 0.775 (Welsh Part Bred), and the average level reached 0.721. The average observed heterozygosity corresponded to 0.709, with the highest value detected in the Czech Sport Pony (0.775). The largest number of private alleles was found in Equus przewalskii. The population inbreeding coefficient F_IS ranged from –0.08 in the Merens to 0.14 in the Belgian Warmblood. The total within-population inbreeding coefficient was estimated to be moderate. As expected, very large genetic differentiation and small gene flow were established between the Friesian and Equus przewalskii (F_ST= 0.37, Nm = 0.43). Zero F_ST values indicated no differences between the Czech Warmblood–Slovak Warmblood and the Czech Warmblood–Bavarian Warmblood. A high level of breeding and connectivity was revealed between the Slovak Warmblood–Bavarian Warmblood, Dutch Warmblood–Oldenburg Horse, Bavarian Warmblood–Dutch Warmblood, and Bavarian Warmblood–Oldenburg Horse. The breeds’ contribution equalled about 6% of the total genetic variability. The overall proportion of individuals correctly assigned to a population corresponded to 82.4%. The posterior Bayesian approach revealed a hierarchical dynamic genetic structure in four clusters (hot-blooded, warm-blooded, cold-blooded, and pony). While most of the populations were genetically distinct from each other and well-arranged with solid breed structures, some of the entire sets showed signs of admixture and/or fragmentation.

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