Estimation between herds genetic diversity of Holsteinized Black-and-White cattle in Leningrad region by Principal Components Analysis
To assess the genetic diversity of Holsteinized Black-and-White cattle in Leningrad Region, Principal Component Analysis (PCA) was used. For the analysis, six herds from Breeding plants with an average cows’ milk yield from 8,100 kg to 11,000 kg were selected. From each herd 45 - 85 cows were selected in random. The total number of cows was 373. All cows were genotyped by the ILLUMINA BovineSNP50 v.2 chip (Illumina Inc. USA) in Ireland (Weatherbys Co. UK). Editing of SNPs was performed according to the following criteria: minor alleles frequency of MAF < 0.01, share of errors in genotyping of SNPs less than 5%, reliability of matching of SNPs genotype to Hardy-Weinberg distribution (P < 0.0001). As a result of editing there are 41210 SNPs. To calculate between genetic diversity of the cows, EIGENSOFT program was used. The reliability of the obtained data was calculated by ANOVA. The reliability of the data for the three eigenvectors was as follows: the first vector (P <0.58), the second vector (P <3.3e-16), the third vector (P <5.9e-06). Therefore, the second and third eigenvectors can be used to estimate the data obtained. Pairwase between herds differences are maximal for herd 2 both for eigenvector 2 and 3. Highly significant pair of herds 3_6 for eigenvector 2 and 3_5 for eigenvector 3 were obtained. Thus, PCA method is effective in studying between herds genetic diversity of dairy cattle and can be recommended for use on other farm animals.