No abstract

The Slovak Pinzgau breed faces the bottleneck effect and the loss of diversity due to unequal use of founders and a significant population decline. Further population size reduction can lead to serious problems. Information obtained here and in other studies from high-throughput genotyping of 179 individuals was used to characterise genetic diversity and differentiation of Slovak Pinzgau, Austrian Pinzgau, Cika and Piedmontese cattle by Bayesian clustering algorithm. A gene flow network for the clusters estimated from admixture results was produced. The low estimate of genetic differentiation (F) in Pinzgau cattle populations indicated that differentiation among these populations is low, particularly owing to a common historical origin and high gene flow. Changes in the log marginal likelihood indicated Austrian Pinzgau as the most similar breed to Slovak Pinzgau. All populations except the Piedmontese one displayed two ways of gene flow among populations, indicating that Piedmontese cattle was involved in producing of the analysed breeds while these breeds were not involved in creation of Piedmontese. Genetic evaluation represents an important tool in breeding and cattle selection. It is more strategically important than ever to preserve as much of the livestock diversity as possible, to ensure a prompt and proper response to the needs of future generations. Information provided by the fine-scale genetic characterization of this study clearly shows that there is a difference in genetic composition of Slovak and Austrian populations, as well as the Cika and Piedmontese cattle. Despite its population size, the Slovak Pinzgau cattle have a potential to serve as a basic gene reserve of this breed, with European and world-wide importance.

The objective of the study was to evaluate inbreeding and genetic diversity inSlovak Spotted cattle. Reference population contained genealogic information on36949 animals (129 sires and 36820 cows) that were used in the analyses. Pedigreecompleteness indexes in the first three generations were on the level of 100 %, inthe 5th generation it was 60 %. Since 1970, inbreeding trend was positive withsignificant increasing in 1990. Average relationship was 0.8 %, inbreeding rate0.36 % and ΔF = 0.094 %. In the reference population 43 % animals was inbred, 68% of sires and 33 % cows, with also 67 % purebred cows, as well. Total geneticdiversity loss in the reference population and population of cows was the same,closely under 1%, in purebred cows 1.19 % and sires even due to higher inbreedinglevel 1.78 %. Genetic diversity loss was more influenced by the genetic drift 0.80%in the reference population, 1.47% in sire group, than by effective number offounder unequal contributions. F statistic showed fines superiority ofheterozygosity by sire lines subpopulations, in the whole sire group (FIS = - 0.12)and their minimal differentiation (FST = 0,098). Obtained results showed thatinbreedization process started in this population. Monitoring and better geneticmanagement are important from the point of its further sustainable development.

Moravčíková N., Simčič M., Mészáros G., Sölkner J., Kukučková V., Vlček M., Trakovická A., Kadlečík O., Kasarda R.. (2018): Genomic response to natural selection within alpine cattle breeds. Czech J. Anim. Sci., 63, 136-143.The aim of this study was to analyse the genomic regions that have been target of natural selection with respect to identifying the loci responsible mainly for fitness traits across six alpine cattle breeds. The genome-wide scan for selection signatures was performed using genotyping data from totally 465 animals. After applying data quality control, overall 35 873 single nucleotide polymorphisms were useable for the subsequent analysis. The detection of genomic regions affected by natural selection was carried out using the approach of principal component analysis. The analysis was based on the assumption that markers extremely related to the population structure are also candidates for local adaptation potential of the population. Based on the expected false discovery rate equal to 10% up to 1138 loci were identified as outliers. The strongest signals of selection were found in genomic regions on BTA 1, 2, 3, 6, 9, 11, 13, and 22. Most genes located in the identified regions have been previously associated with immunity system as well as body growth and muscle formation that mainly reflect the pressure of both natural and artificial selection in respect to adaptation of analysed breeds to the local environmental conditions. The results also signalized that those regions represent a correlated selection response in way to maintain the fitness of analysed breeds.

The aim of this study was to assess genetic structure of Slovak Pinzgau population based on polymorphism at molecular markers using statistical methods. Female offspring of 12 most frequently used bulls in Slovak Pinzgau breeding programme were investigated. Pinzgau cattle were found to have a high level of diversity, supported by the number of alleles observed across loci (average 5.31, range 2-11) and by the high within-breed expected heterozygosity (average 0.66, range 0.64-0.73). The state of genetic diversity is satisfying and standard for local populations. Detection of 12 possible subpopulation structures provided us with detailed information of the genetic structure. The Bayesian approach was applied, detecting three, as the most probable number of clusters. The similarity of each subpopulation using microsatellites was confirmed also by high-throughput molecular data. The observed inbreeding (F ROH =2.3%) was higher than that expected based on pedigree data (F PED =0.4%) due to the limited number of available generations in pedigree data. One of the most important steps in development of efficient autochthonous breed protection programs is characterization of genetic variability and assessment of the population structure. The chosen set of microsatellites confirmed the suitability in determination of the subpopulations of Pinzgau cattle in Slovakia. The state of genetic diversity at more detailed level was successfully performed using bovineSNP50 BeadChip.