In this study, the authors focused on the evaluation of the genetic parameters of longevity, milk yield traits, and type traits in dairy cattle populations in the Republic of Serbia. The total dataset used consisted of production records and pedigree data for 32,512 Holstein cows that calved from 1981 to 2015. The animal model was applied to determine the variance and covariance components and genetic parameters of the analyzed traits by applying the restricted maximum likelihood (REML) approach and using the programs VCE6 and PEST. The heritability of longevity traits was estimated using the Survival Kit V6.0 software package. Variance and covariance were estimated for five production traits: milk yield (MY), fat yield (FY), protein yield (PY), milk fat content (MC), and protein content (PC), and three longevity traits: length of productive life (LPL), lifetime milk yield (LMY), and the number of lactations achieved (NL) as well as for 18 standard type traits. Heritabilities for the milk, fat, and protein yield traits were 0.20 (MY), 0.15 (FY), and 0.19 (PY), respectively. The estimated coefficients of heritability for the longevity traits were higher when using the Weibull proportional hazards model compared to the traditional linear methods and ranged from 0.08 for NL to 0.10 for LPL. Heritability values for the type traits varied from a low of 0.10 (RLSsv—rear legs set–side view) to medium values of 0.32 (ST-stature). Genetic correlations were found between MY and the following longevity traits: LPL, LMY, and NL with values of −0.18, −0.11, and −0.09, respectively. Genetic correlations were found between MY and a number of linear type traits and varied from 0.02 (between MY and RUH-rear udder height) to 0.28 (between MY and FUA-fore udder attachment). Genetic correlations between the 18 investigated type traits ranged from −0.33 between TL (top line) and RTP (rear teats position) to 0.71 between AN (angularity) and RUH (rear udder height). Genetic correlations between most linear type traits and longevity traits (LPL, LMY, and NL) were generally negative and very low. The highest positive genetic correlation was found between UD and LPL (r_xy = 0.38).

In this paper, six univariate and two multivariate best linear unbiased prediction (BLUP) models were tested for the estimation of breeding values (BV) in Holstein Friesian cattle in Serbia. Two univariate models were formed using the numerator relationship matrix (NRM), four using the genomic relationship matrix (GRM). Multivariate models contained only an NRM. Two cases were studied, the first when only first lactations were observed, and the second when all lactations were observed using a repeatability model. A total of 6041 animals were included, and of them, 2565 had data on milk yield (MY), milk fat yield (FY), milk fat content (FC), milk protein yield (PY) and milk protein content (PC). Finally, out of those 2565 cows, 1491 were genotyped. A higher accuracy of BV was obtained when using a combination of NRM and GRM compared to NRM alone in univariate analysis, while multivariate analysis with repeated measures gave the highest accuracy with all 6041 animals. When only genotyped animals were observed, the highest accuracy of the estimated BV was calculated by the ssGBLUPp model, and the lowest by the univariate BLUP model. In conclusion, the current breeding programs in Serbia should be changed to use multivariate analysis with repeated measurements until the optimal size of the reference population, which must include genotyping data on both bulls and cows, is reached.

Pedigree analysis of the Lipizzan horse populations from Bosnia and Herzegovina and Serbia: Structure, inbreeding and genetic variability | Biljana Rogic, Ljuba Strbac, Sladjana Preradovic, Bozo Vazic | Agricultural Journals

The use of genomic data makes it possible to examine genetic variability and calculate the genetic parameters of the population in an efficient and precise way. The aim of this research was to analyse linkage disequilibrium (LD), contemporary effective population size (Ne c), haplotype block structure, minor allele frequency (MAF), observed (H O) and expected heterozygosity (H E), calculate the genomic relationship matrix and perform a principal component analysis (PCA) in the Serbian Holstein-Friesian cattle population using SNP data from the GGP Bovine 100K chip. After quality control (QC), 83 208 SNPs and 1 575 cows were retained for further analysis. LD on autosomes had an average value of ≥ 0.2 up to a distance of 50-60 kb (r 2 = 0.211), while on BTX r 2 ≥ 0.2 was represented at distances of 80-90 kb (r 2 = 0.211). LD differed between chromosomes. The average H O for autosomes and X chromosome SNPs was 0.412 and 0.422, respectively. 81.30% of SNPs that passed QC had MAF > 0.2. The total number of haplotype blocks in the studied population was 15 642. On average, blocks contained 2.932 SNPs. The average block length was 32.657 kb and ranged from a minimum of 0.019 kb (BTA21 and BTA26) to a maximum of 999.562 kb (BTX). The estimated value of Ne c in the this cattle population was 142. The results of PCA showed a significant variability of genotypes in the population, but there was no clear stratification of the population. The obtained results will serve as a basis for future genomic analyses such as the detection of QTLs for important economic traits and the implementation of genomic selection.

Summary: The Lipizzan horse breed was established in the 16 ^th century in Lipica and later spread throughout Central and Eastern Europe. In addition to six classical stallion lines, 17 classical mare family lines were established in the old Lipica stud. Additional 44 mare family lines, including local lines, were established in other Lipizzan studs. The founders of the classical Lipizzan mare family lines date back to the period between the 18 ^th and 20 ^th century and came from various breeds, including the Karst, Spanish, Italian, Kladruber and Arabian horses. The history of the Lipizzan mare family lines is well described and supported by the availability of 44 nucleotide sequences of the mtDNA control region. In this study, the mtDNA control region of 23 Serbian Lipizzans, representing the established Lippizan mare family lines, as well as the local mare family line Zora, have been sequenced. The objective of this study was to test whether the Zora mare family line could be distinguished from other Lipizzan mare family lines according to the mtDNA sequence. Sequences were aligned to the entire set of mtDNA control region sequences representing 44 Lipizzan mtDNA haplotypes. Based on the alignment, a median-joining network was constructed. The individuals in this study formed a cluster with the existing Lipizzan mare family lines. However, a total of ten individuals belonging to the local Zora mare family line formed a compact cluster close to the mtDNA haplotypes, representing the classical mare family lines Wera, Betalka, and Monteaura. Additional pedigree data are needed to clarify the origin of the mtDNA haplotype variant identified in this study.