Assessment of genetic parameters in a subpopulation of Jersey cattle based on the study of STR markers and their potential impact on the variability of animal development indicators

The study of the relationship between genetic and phenotypic traits in cattle is a key area of breeding and genetics. Comparing these traits can enhance animal breeding efficiency and facilitate the development of more productive herds. Using STR markers, this study presents the first data on the genetic structure of Jersey replacement heifers in the North Caucasus region and demonstrates the influence of specific alleles at the studied loci on live weight during ontogenesis. The aim of the work was to study and characterize the genetic diversity and structure of a Jersey cow subpopulation in the North Caucasus using 16 microsatellite loci (BM1818, BM1824, BM2113, ETH3, ETH10, ETH225, INRA023, ILSTS006, SPS115, TGLA53, TGLA122, TGLA126, TGLA227, CSSM66, CSRM60, HAUT27), and also to identify allelic variants with potential influence on the live weight of replacement heifers at birth and at 6 months of age, and on average daily live weight gains from birth to 6 months. The work was conducted in 2023. The object of the study was replacement heifers (Bos taurus taurus) of the Jersey breed, Jester 534585 line ( n = 1074), bred at the breeding farm Agroalliance Invest LLC in the Stavropol Territory. Live weight dynamics were studied by weighing young stock at birth and at 6 months (GOST R 57784-2017. M., 2017). Blood samples were collected from the animals for genetic studies. Nucleic acid isolation and purification were performed using magnetic sorbent with the commercial kit M-Sorb-blood (Syntol R&D and Production LLC, Russia). Multiplex amplification was carried out on a T100 Thermal Cycler (Bio-Rad, USA) using the commercial Gene Profile Cattle kit (Syntol R&D and Production LLC, Russia). Amplicons obtained from the polymerase chain reaction were separated by capillary electrophoresis on an automated genetic analyzer Nanofor 05 (Syntol R&D and Production LLC, Russia). The obtained data were processed using GeneMarker v.3.0.1 software (SoftGenetics LLC, USA). Parameters of allele polymorphism and genetic diversity, including mean number of alleles (NA), effective number of alleles (NE), observed (HO) and expected (HE) heterozygosity, Shannon's information index (I), fixation index (FIS), Principal Coordinates Analysis (PCoA), probability of identity (PI), probability of identity between siblings (PISIBS), c2 (ChiSq) for Hardy-Weinberg equilibrium, degrees of freedom (DF), probability (Prob), and significance (Sigif), were calculated using the GenAlEx v.6.51b2 add-in for Microsoft Excel. Observed (HO) and expected (HE) heterozygosity in the Jersey subpopulation bred in the North Caucasus conditions for the aforementioned loci were 0.657±0.036 and 0.621±0.031, respectively, suggesting enhanced genetic adaptability to changing environmental conditions. The fixation index (FIS) of -0.056±0.011 indicated outcrossing (non-relative mating) within the subpopulation. The highest allele frequencies in the sample were observed for allele 135 bp of the BM2113 locus (83%) and allele 117 bp of the ETH3 locus (79 %). The average number of alleles per locus (NA) was 6.875±0.446, and the average number of effective alleles (NE) was 2.846±0.171. Shannon's information index (I) was 1.183±0.061, indicating a high degree of herd uniformity. A statistically significant influence was found for 7 loci (TGLA227, TGLA53, BM1824, CSSM66, TGLA122, BM1818, ILSTS006) on the live weight of young stock at 6 months and on average daily gains from 0 to 6 months, as well as for 2 loci (ETH3, ETH10) on live weight at birth and at 6 months. Consequently, allelic variants within these loci were identified that were associated with peak values for live weight and average daily gains. The profiles obtained from the microsatellite analysis can be used in population studies, as well as for planning breeding activities, maintaining heterozygosity levels in populations, and genetically monitoring selection processes.