Variation in Linkage Disequilibrium Patterns between Populations of Different Production Types

The aim of this study was to quantify the variation in linkage disequilibrium patterns between populations of Slovak Pinzgau, Austrian Pinzgau, Simmental, Charolais and Holstein. These comparisons included differences between the genetically close populations as well as between dairy and beef breed types. Total number of genes in regions with top 0.01 and 0.1 percentile was 202. The most significant SNPs for production, reproduction and functional traits were positioned in the chromosome 7, 9, 11, 14, 20 and 24 (H2AFY, MAP3K, FAM110B, UBXN2B, CYP7A1, SDCBP, NSMAF, PRKAA1, PTGER4, MIR2361, CDH18 and C9). Genome scans confirmed the presence of selective sweeps in the genomic regions that harbour candidate genes that are known to affect productive traits in cattle such as CAST, COQ3, GJA1, ACYP2, SPTBN1, EML6, RTN4, MAP3K7, PLAG1, CHCHD7, PENK, PRLR, GHR, C6, C7, LIFR, MOCOS, GALNT1, COLEC12, CETN1, TYMS, YES1, NDC80, LPIN2, MYOM1, MYL12A, MYL12B and DLGAP1. Although phenotypic diversity is not sufficiently large to be detected, investigating the polymorphisms presented in the regions of the genome that are involved in breeding traits can be very useful in terms of genetic improvement

Variation in Linkage Disequilibrium Patterns between Populations of Different Production Types

The aim of this study was to quantify the variation in linkage disequilibrium patterns between populations of Slovak Pinzgau, Austrian Pinzgau, Simmental, Charolais and Holstein. These comparisons included differences between the genetically close populations as well as between dairy and beef breed types. Total number of genes in regions with top 0.01 and 0.1 percentile was 202. The most significant SNPs for production, reproduction and functional traits were positioned in the chromosome 7, 9, 11, 14, 20 and 24 (H2AFY, MAP3K, FAM110B, UBXN2B, CYP7A1, SDCBP, NSMAF, PRKAA1, PTGER4, MIR2361, CDH18 and C9). Genome scans confirmed the presence of selective sweeps in the genomic regions that harbour candidate genes that are known to affect productive traits in cattle such as CAST, COQ3, GJA1, ACYP2, SPTBN1, EML6, RTN4, MAP3K7, PLAG1, CHCHD7, PENK, PRLR, GHR, C6, C7, LIFR, MOCOS, GALNT1, COLEC12, CETN1, TYMS, YES1, NDC80, LPIN2, MYOM1, MYL12A, MYL12B and DLGAP1. Although phenotypic diversity is not sufficiently large to be detected, investigating the polymorphisms presented in the regions of the genome that are involved in breeding traits can be very useful in terms of genetic improvement

Inbreeding and Genetic Diversity Loss in Slovak Pinzgau Breed

The objective of the paper was to evaluate trends in inbreeding and genetic diversity loss of Slovak Pinzgau. Genealogic information had good informative value. Inbreeding trends were positive in pedigree as well as reference populations. Intensity of inbreeding and average relationship have not reach the level of 1 % at which inbreeding gains per generation was low in the reference population. Almost the same results were obtained in the population of cows. Sires influenced inbreeding and its gain in reference population less than cows, but higher sires average relationship may create not optimistic prognosis for future sire inbreeding development. Total loss of genetic diversity in sire group was 3.17 % at which this level was more influenced by genetic drift (2.69 %) than bottleneck

Inbreeding and Genetic Diversity Loss in Slovak Pinzgau Breed

The objective of the paper was to evaluate trends in inbreeding and genetic diversity loss of Slovak Pinzgau. Genealogic information had good informative value. Inbreeding trends were positive in pedigree as well as reference populations. Intensity of inbreeding and average relationship have not reach the level of 1 % at which inbreeding gains per generation was low in the reference population. Almost the same results were obtained in the population of cows. Sires influenced inbreeding and its gain in reference population less than cows, but higher sires average relationship may create not optimistic prognosis for future sire inbreeding development. Total loss of genetic diversity in sire group was 3.17 % at which this level was more influenced by genetic drift (2.69 %) than bottleneck

Evaluating signatures of selection through variation in linkage disequilibrium among different cattle breeds

The aim of presented investigation was to assess the overlap between selection signature discovered through analysis of variation in linkage disequilibrium and reported genomic regions associated with economic and traits of biological importance in cattle populations. The differences across Slovak Pinzgau, Austrian Pinzgau, Simmental and Holstein cattle and thus genome signatures of production and adaptation were found. The highest peak (top 0.01 percentile) was observed between Slovak and Austrian on chromosome 23, between Slovak Pinzgau and Simmental on chromosome 4 and between Slovak Pinzgau and Holstein on chromosomes 1, 7 and 20. Many candidate genes found have a known role in milk production (casein genes CSN1S1, CSN2, CSN1S2, CSN3; ABCG2, HBEGF, CAPN3, DGAT1, TG, GHR), reproduction (MGAT1, FGF1), feed efficiency (R3HDM1, ZRANB3), fertility (SPOCK1) and immune response (HSPA9, CD14, ARAP3, PCDH). Results of this study could be the basis for implementation of genomic selection programs in the Slovak Pinzgau cattle

The most important sires in Pinzgau population

Received: 2016-05-24 | Accepted: 2016-08-02 | Available online: 2017-06-20http://dx.doi.org/10.15414/afz.2017.20.01.28-30The aim of this study was to calculate the inbreeding coefficients of the most used sires in population of Slovak Pinzgau and summarize milk production of theirs daughters as main criterion in present in selection of sires besides pedigree based level of inbreeding of future progeny. The runs of homozygosity (ROH) greater than 4 Mb cover on average 1.9 % of genome, ROH ˃ 8 Mb cover 1.3 % and ROH ˃ 16 Mb cover 0.4. Obtained results were compared to genealogical pedigree analysis; the observed inbreeding was higher than that expected based on pedigree data (0.16 %), despite the fact that ROH > 16 Mb representing recent inbreeding approximately three generations ago. The average milk performance of evaluated Slovak Pinzgau cows has been 5259 kg of milk, 3.6 % of protein and 3.85 % of fat. These results are important for the management of the Pinzgau population in Slovakia due to more precise values of inbreeding obtained as well as knowledge about the ancient inbreeding which was not possible to estimate from the pedigree data.Keywords: inbreeding, milk performance, runs of homozygosity, Slovak Pinzgau cattleReferencesALBRECHTSEN A., NIELSEN F.C. and NIELSEN R. (2010) Ascertainment biases in SNP chips affect measures of population divergence. Molecular Biology and Evolution, vol. 27, pp. 2534-2547. doi: http://dx.doi.org/10.1093/molbev/msq148BJELLAND, D.W. et al. (2013) Evaluation of inbreeding depression in Holstein cattle using whole-genome SNP markers and alternative measures of genomic inbreeding. Journal of Dairy Science, vol. 96, pp. 4697-4706. doi:http://dx.doi.org/10.3168/jds.2012-6435CHARLESWORTH, D. and WILLIS, J. (2009) The genetics of inbreeding depression. Nature Reviews Genetics, vol. 10, pp. 783-796. doi:http://dx.doi.org/10.1038/nrg2664FERENČAKOVIĆ, M. et al. (2011) Runs of Homozygosity Reveal Genomewide Autozygosity in the Austrian Fleckvieh Cattle. Agriculturae Conspectus Scientificus, vol. 76, no. 4, pp. 325-328.GURGUL, A., et al. (2016) The use of runs of homozygosity for estimation of recent inbreeding in Holstein cattle. Journal of Applied Genetics, vol. 57, pp. 1-4. doi:http://dx.doi.org/10.1007/s13353-016-0337-6GUTIÉRREZ, J.P. et al. (2008) Individual increase in inbreeding allows estimating realised effective sizes from pedigrees. Genetics Selection Evolution, vol. 40, pp. 359-378. doi:http://dx.doi.org/10.1186/1297-9686-40-4-359MARRAS, G. et al. (2015) Analysis of runs of homozygosity and their relationship with inbreeding in five cattle breeds farmed in Italy. Animal Genetics, vol. 46, no. 2, pp. 110-121. doi:http://dx.doi.org/10.1111/age.12259PAVLÍK, I. et al. (2014) Joint genealogical analysis as a tool for diversity evaluation in Pinzgau cattle populations. Archive Tierzucht, vol. 57, no. 14, pp. 1-12. doi:http://dx.doi.org/10.7482/0003-9438-57-014PURCELL, S. et al. (2007) PLINK: a toolset for whole-genome association and population-based linkage analysis. The American Journal of Human Genetics, vol. 81, pp. 559-575. doi:http://dx.doi.org/10.1086/519795SAS Institute Inc: SAS/STAT Software. (2011) Cary NC: SAS Institute Inc: Version 9.3.THE BREEDING SERVICES OF THE SLOVAK REPUBLIC. (2014) Results of dairy herd milk recording in Slovak Republic for control year 2013-2014. [Online]. Available at http://pssr.sk/org/publ/2014/hd/rocenka/ml_13_14/rocenka/Mliekova_rocenka_2014.pdf. [Accessed: 1st March 2017]

The canine melanophilin gene polymorphisms in Slovakian Rough-haired Pointer

The aim of this study was to determine the population genotypic structure based on polymorphisms located in exon 1 (c.-22G>A) and exon 7 (R199H) of canine gene encoding melanophilin (MLPH). The genomic DNA were obtained from in total 49 samples of Slovakian Rough-haired Pointer and analysed using PCR-RFLP methods. The prevalence of G allele has been found in case of both identified loci. The highest frequency has been observed for heterozygous animals and its sufficient proportion was confirmed also by the coefficient of heterozygosity (0.71 or 0.67) and the FIS index values (-0.45 or -0.47). The FST index showed expected high degree of genetic similarity between analysed populations resulted from their breeding purposes and common founders. The genotyping of such polymorphisms can be perspective mainly due to the fact that the MLPH gene was associated with the coat colour dilution and also alopecia not only in human but as well as in dog populations

Genome-wide mixed model association study in population of Slovak Pinzgau cattle

The aim of this study was to detect the position of genomic regions associated with milk production and milk components in Pinzgau cattle. The dataset consisted of milk yield records of in total 7729 cows of 35 sires representing active bulls (19 animals) and DNA material stored in gene bank (16 animals) of Pinzgau cattle in Slovakia. In total 130087 test-day records of milk, protein and fat yield were used for the association analysis. The Illumina BovineSNP50 BeadChip V2 was used and after quality control final dataset consisted of 41,487 autosomal loci covering overall length 2,500,315 kb of the genome. Identification of genomic regions associated with milk production and composition were performed using GEMMA software with use of linear mixed model approach based on genetic-relationship matrix estimated from SNP genotypes to model correlation between the phenotypes. Based on this were found SNPs in the regions of important QTLs significantly associated with milk yield, dressing percentage, protein yield, SCS score, marbling score and fat yield

GENOMIC DETERMINATION OF THE MOST IMPORTANT FATHER LINES OF SLOVAK PINZGAU COWS

The aim of this study was to assess genetic structure of Slovak Pinzgau populationbased on polymorphism at molecular markers using statistical methods. Femaleoffspring of 12 most frequently used bulls in Slovak Pinzgau breeding programmewere 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 detailedinformation of the genetic structure. The Bayesian approach was applied, detectingthree, as the most probable number of clusters. The similarity of eachsubpopulation using microsatellites was confirmed also by high-throughputmolecular data. The observed inbreeding (FROH=2.3%) was higher than thatexpected based on pedigree data (FPED=0.4%) due to the limited number ofavailable generations in pedigree data. One of the most important steps indevelopment of efficient autochthonous breed protection programs ischaracterization of genetic variability and assessment of the population structure.The chosen set of microsatellites confirmed the suitability in determination of thesubpopulations of Pinzgau cattle in Slovakia. The state of genetic diversity at moredetailed level was successfully performed using bovineSNP50 BeadChip

GENETIC MARKERS AND BIOSTATISTICAL METHODS AS APPROPRIATE TOOLS TO PRESERVE GENETIC RESOURCES

The aim of presented study was to assess the most suitable way how to distinguishdifferent breeds based on molecular markers. One of the most difficult aspects ofquality assurance schemes is their reliability. The verification of fraud needs greatefforts in control strategies. The use of DNA markers has been shown to be auseful tool for individual identification. It is necessary to use modern statisticalmethod based on data mining and supervised learning. Supervised patternrecognition techniques use the information about the class membership of thesamples to a certain group (class or category) in order to classify new unknownsamples in one of the known classes on the basis of its pattern of measurements.Large scale of supervised learning oriented method was used for traceability andidentification on individual level. A result of provided study shows the possibilityto classify unknown samples according to genetic data. Model is also useful forclassification on many logical levels as brand, region and many others. If we takein the account only Slovak and Austrian Pinzgau cattle, based on SNP chip data, itis not possible to separate them using Bayesian approach. Once we considered withthe admixture of breeds involved in the historical development as well asinbreeding, selection signatures and migration, we were able to separate evengenetically similar breeds. It is possible distinguish between closely relatedpopulations based on different markers. We just need to select the appropriate typeof analysis