Genome analysis in five Italian beef cattle breeds

Chianina, Marchigiana, Maremmana, Podolica and Romagnola are the main Italian beef cattle breeds, and the quality of their products is largely recognized worldwide. This paper aims to determine the genetic variability and population differentiation by heterozygosity and fixation indices using SNPs data. The dataset was composed of 3,581 animals (Chianina, n = 909; Marchigiana, n = 879; Maremmana, n = 334; Podolica, n = 555; Romagnola, n = 904). The blood samples were collected in ANABIC performance testing station from 1985 to 2019. All the animals were genotyped with the GeneSeek GGP-LDv4 33k SNP chip containing 30,111 SNPs. The genotype quality control for each breed was conducted separately, and SNPs with call rate smaller than 0.95 and minor allele frequency larger than 5% were used for further analysis. Heterozygosity and F IS index were estimated in PLINK v1.9, and F ST index was estimated using the hierstat package of R 4.0. 1 software. The genetic analysis highlighted low values of heterozygosity in the improved beef breeds compared to the heritage breeds; moreover, the low values of F IS indicated a positive effect of controlled genetic inbreeding in the studied breeds. The F ST ; analysis confirmed the historical origin of Marchigiana breed and the values are consistent with their common breeding programmes. In this study, the importance of monitoring genetic variability of Italian beef cattle breeds was emphasized in order to maintain breed identity and genetic diversity in the selection process. Keywords: bovine, SNPs, inbreeding References Bonadonna, T. (1976). Etnologia zootecnica. Turin, Italy: UTET. Bongiorni, S. et al. (2016). Transcriptomic investigation of meat tenderness in two Italian cattle breeds. Animal genetics, 47(3), 273-287. Cosentino, C. et al. (2018). Podolian cattle: reproductive activity, milk and future prospects. Italian Journal of Agronomy, 13(3). Dalvit, C. et al. (2008). Breed assignment test in four Italian beef cattle breeds. Meat Science, 80(2), 389-395. D’Andrea, M. et al. (2011). Genetic characterization and structure of the Italian Podolian cattle breed and its relationship with some major European breeds. Italian Journal of Animal Science, 10(4), e54. Goudet, J. (2005). Hierfstat, a package for R to compute and test hierarchical F‐statistics. Molecular Ecology Notes, 5(1), 184-186. Hall, SJG and Bradley, DG. (1995). Conserving livestock breed biodiversity. Tree, 10, 267–270. Holsinger, KE and Weir, BS. (2009). Genetics in geographically structured populations: defining, estimating and interpreting FST. Nature Reviews Genetics, 10(9), 639-650. Jordana, J. et al. (2003). Genetic structure of eighteen local south European beef cattle breeds by comparative F‐statistics analysis. Journal of Animal Breeding and Genetics, 120(2), 73-87. Lasagna, E. et al. (2015). Comparison of four Italian beef cattle breeds by means of functional genes. Italian Journal of Animal Science, 14(1), 3465. Maretto, F. et al. (2012). Genetic relationships among Italian and Croatian Podolian cattle breeds assessed by microsatellite markers. Livestock science, 150(1-3), 256-264. Moioli, B. et al. (2004). Genetic diversity between Piedmontese, Maremmana, and Podolica cattle breeds. Journal of Heredity, 95(3), 250-256. Purcell, S. et al. (2007). PLINK: a tool set for whole-genome association and population-based linkage analyses. The American journal of human genetics, 81(3), 559-575. Sbarra, F. et al. (2009). Heritability of performance test traits in Chianina, Marchigiana and Romagnola breeds. Italian Journal of Animal Science, 8(sup3), 107-109. Smaragdov, MG. et al. (2018). The Assessing the genetic differentiation of Holstein cattle herds in the Leningrad region using Fst statistics. Agricultural and Food Science, 27(2), 96-101. Vincenti, F. et al. (2007). The hypertrophic Marchigiana: physical and biochemical parameters for meat quality evaluation. Italian Journal of Animal Science, 6(sup1), 491-493. Wright, S. (1965). The interpretation of population structure by F-statistics with special regard to systems of mating. Evolution, 395-420.