SUMMARY
Received: 2020-10-22 Accepted: 2021-02-08 Available online: 2021-02-28https://doi.org/10.15414/afz.2021.24.mi-apa.7-10The study presents an approach to detect selection signals by the scan of runs of homozygosity (ROH) in two beef cattle populationsbred Slovakia. The frequency and distribution of runs of homozygosity in the genome are affected by natural and artificial selection,recombination rate and structure of the population. After quality control, the final data set included 43,427 single nucleotidepolymorphisms with overall length 2,504 Mb. Across the genome, sixteen regions under strong selection pressure with a totallength of 73.94 Mb were identified. The functional analysis of selection signals revealed several quantitative trait loci for bodystructure, fitness and milk production. In the region with a high frequency of ROH reflecting the intense artificial selection genesrelated mainly to muscle development (MSNT, ROCK1, LAMTOR5) were observed. Besides, genes related to the control of theimmune system (PTX3, FGL2) and reproduction (ADCYAP1R1) were localized within selection signals. The results confirm theintention to improve the production and reproduction traits of Charolais and Limousine cattle according to established breedingobjectives for each breed.Keywords: beef production, genomic region, homozygosity, quantitative traits, signatures of selectionReferencesClarke, A.M. et al. (2009). Intake, live animal scores/measurements and carcass composition and value of late-maturing beefand dairy breeds. Livestock Science, 126, 57–68.Connor, E.E. et al. (2008). Effects of increased milking frequency on gene expression in the bovine mammary gland. BMCGenom, 9, 362.Ferencakovi c, M. et al. (2013). Estimating autozygosity from high-throughput information: effects of SNP density andgenotyping errors. Genetics Selection Evolution, 76(4), 325–329.Gaud et, P. et al. (2011). Phylogenetic-based propagation of functional annotations within the Gene Ontology consortium.Brief Bioinform., 12(5), 449–462.Chang, C.C. et al. (2015). Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience, 25(4).Marras , G. et al. (2015). Analysis of runs of homozygosity and their relationship with inbreeding in five cattle breeds farmedin Italy. Animal Genetics, 4,110–121.Morav cíkov á, N. et al. (2018). Genomic Response to Natural Selection within Alpine Cattle Breeds. Czech J. Anim. Sci., 63(4),136–143.Purfield, D.C. et al. (2012). Runs of homozygosity and population history in cattle. BMC Genet, 13.Randhawa , I.A.S. et al. (2016). A Meta-Assembly of Selection Signatures In cattle. PLOS One, 11(4).Sifuentes, A.M. et al. (2015). Loci asociados con enfermedades genéticas y calidad de carne en bovinos Charolais mexicanos.Revista Mexicana De Ciencias Pecuarias, 6(4), 361–375.Szmato la, T. et al. (2016). Characteristics of runs of homozygosity in selected cattle breeds maintained in Poland. LivestockScience, 188, 72–80.Szmato la, T. et al. (2019). A Comprehensive Analysis of Runs of Homozygosity of Eleven Cattle Breeds Representing DifferentProduction Types. Animals, 9(12).Trukhach ev, V. et al. (2015). Myostatin gene (MSTN) polymorphism with a negative effect on meat productivity in DzhalginskyMerino sheep breed. J. BioSci. Biotechnol., 4(2), 191–199.Turner, S.D. (2017). qqman: an R package for visualizing GWAS results using Q-Q and manhattan plots. bioRxiv.Williams , J.L. (2015). Inbreeding and purging at the genomic Level: the Chillingham cattle reveal extensive, non-random SNPheterozygosity. Animal Genetics, 47(1), 19–27.Wyatt , A.R. et al. (2013). Protease-activated alpha-2-macroglobulin can inhibit amyloid formation via two distinct mechanisms.FEBS Lett, 587(5), 398–403.Zavar ez, L.B. et al. (2015). Assessment of autozygosity in Nellore cows (Bos indicus) through high-density SNP genotypes.Frontiers in Genetics, 6(5).Zhang, Y. et al. (2015). Runs of homozygosity and distribution of functional variants in the cattle genome. BMC Genomics, 16,542.