Holstein Animals Research Articles

Structure of subopopulations of Aireshire, Holstin and Jersey cattle in the Southern Regions of Russia by CSN2 (rs43703011), CSN3 (rs43703016) and microsatellite locuses (BM1818, BM1824, BM2113, ETH10, ETH225, ETH3, INRA023, SPS115, TGLA126, TGLA122, TGLA227, TGLA53)

During studies using molecular biological methods, the following loci were genotyped: BM1818, BM1824, BM2113, ETH10, ETH225, ETH3, INRA023, SPS115, TGLA126, TGLA122, TGLA227, TGLA53, CSN2 (rs43703011) and CSN3 (rs43703 016) 3000 cow blood samples Ayrshire, Holstein and Jersey breeds from the herds of the Krasnodar and Stavropol territories. On average, the frequency of occurrence of homozygous genotypes for 12 microsatellite loci in Jersey cattle was 0.38, in Holstein and Ayrshire cattle – 0.30 and 0.27, respectively; the highest allelic diversity was found in Holstein cattle (9.0 ± 1.7 alleles per locus). It should be noted that there are significant differences in the genetic profile of Ayrshire cattle. For Ayrshire animals, the following alleles turned out to be typical (but rare in Jersey and Holstein cattle): 270 locus BM1818, 137 locus BM2113, 213 locus ETH10, 119 locus ETH3, 142 locus ETH225, 87 locus TGLA227, 166 locus TGLA53. In the studied subpopulation of Jersey cattle, the frequency of occurrence of the A2A2 genotype of the CSN2 locus (rs43703011) (beta casein) was 0.68, and in the Ayrshire and Holstein groups it was only 0.25 and 0.31, respectively. The BB genotype of the CSN3 locus (rs43703016) (casein kappa) was found in the Jersey group of animals with a frequency of 0.76, and in Ayrshires and Holsteins – 0.04 and 0.15, respectively. The genotyped groups of Jersey, Ayrshire and Holstein animals are significant in volume; we assume that the identified patterns are typical for cattle of these breeds in the south of Russia. We believe that the data obtained can be used in the future in practical work on classifying certain groups of livestock as typical Holstein, Ayrshire or Jersey and when creating herds that produce milk of a certain type (for example, type A2 milk).

Genome-Wide Association Study of Conformation Traits in Brazilian Holstein Cattle.

The linear conformation of animals exerts an influence on health, reproduction, production, and welfare, in addition to longevity, which directly affects the profitability of milk-producing farms. The objectives of this study were (1) to perform genome-wide association studies (GWASs) of conformation traits, namely the Rump, Feet and Legs, Mammary System, Dairy Strength, and Final Classification traits, and (2) to identify genes and related pathways involved in physiological processes associated with conformation traits in Brazilian Holstein cattle. Phenotypic and genotypic data from 2339 Holstein animals distributed across the states of Rio Grande do Sul, Paraná, São Paulo, and Minas Gerais were used. The genotypic data were obtained with a 100 K SNP marker panel. The single-step genome-wide association study (ssGWAS) method was employed in the analyses. Genes close to a significant SNP were identified in an interval of 100 kb up- and downstream using the Ensembl database available in the BioMart tool. The DAVID database was used to identify the main metabolic pathways and the STRING program was employed to create the gene regulatory network. In total, 36 significant SNPs were found on 15 chromosomes; 27 of these SNPs were linked to genes that may influence the traits studied. Fourteen genes most closely related to the studied traits were identified, as well as four genes that showed interactions in important metabolic pathways such as myogenesis, adipogenesis, and angiogenesis. Among the total genes, four were associated with myogenesis (TMOD2, TMOD3, CCND2, and CTBP2), three with angiogenesis (FGF23, FGF1, and SCG3), and four with adipogenesis and body size and development (C5H12orf4, CCND2, EMILIN1, and FGF6). These results contribute to a better understanding of the biological mechanisms underlying phenotypic variability in conformation traits in Brazilian Holstein cattle.

Genome-wide association analyses reveal copy number variant regions associated with reproduction and disease traits in Canadian Holstein cattle

This study aimed to evaluate the impact of copy number variants (CNVs) on 13 reproduction and 12 disease traits in Holstein cattle. Intensity signal files containing Log R ratio and B allele frequency information from 13,730 Holstein animals genotyped with a 95K SNP panel, and 8,467 Holstein animals genotyped with a 50K SNP panel were used to identify the CNVs. Subsequently, the identified CNVs were validated using whole genome sequence data from 126 animals, resulting in 870 high-confidence CNV regions (CNVRs) on 12,131 animals. Out of these, 54 CNVRs had frequencies higher than or equal to 1% in the population and were used in the genome-wide association analysis (one CNVR at a time, including the G matrix). Results revealed that 4 CNVRs were significantly (p-value < 3.7 × 10−5) associated with at least one of the traits analyzed in this study. Specifically, 2 CNVRs were associated with 3 reproduction traits (i.e., calf survival, first service to conception, and non-return rate), and 2 CNVRs were associated with 2 disease traits (i.e., metritis and retained placenta). These CNVRs harbored genes implicated in immune response, cellular signaling, and neuronal development, supporting their potential involvement in these traits. Further investigations to unravel the mechanistic and functional implications of these CNVRs on the mentioned traits are warranted.

Genome-wide association and functional genomic analyses for body conformation traits in North American Holstein cattle.

Body conformation traits are directly associated with longevity, fertility, health, and workability in dairy cows and have been under direct genetic selection for many decades in various countries worldwide. The main objectives of this study were to perform genome-wide association studies and functional enrichment analyses for fourteen body conformation traits using imputed high-density single nucleotide polymorphism (SNP) genotypes. The traits analyzed include body condition score (BCS), body depth (BD), bone quality (BQ), chest width (CW), dairy capacity (DC), foot angle (FAN), front legs view (FLV), heel depth (HDe), height at front end (HFE), locomotion (LOC), rear legs rear view (RLRV), rear legs side view (RLSV), stature (ST), and a composite feet and legs score index (FL) of Holstein cows scored in Canada. De-regressed estimated breeding values from a dataset of 39,135 North American Holstein animals were used as pseudo-phenotypes in the genome-wide association analyses. A mixed linear model was used to estimate the SNP effects, which ranged from 239,533 to 242,747 markers depending on the trait analyzed. Genes and quantitative trait loci (QTL) located up to 100Kb upstream or downstream of the significant SNPs previously cited in the Animal QTLdb were detected, and functional enrichment analyses were performed for the candidate genes identified for each trait. A total of 20, 60, 13, 17, 27, 8, 7, 19, 4, 10, 13, 15, 7, and 13 genome-wide statistically significant SNPs for Bonferroni correction based on independent chromosomal segments were identified for BCS, BD, BQ, CW, DC, FAN, FLV, HDe, HFE, LOC, RLRV, RLSV, ST, and FL, respectively. The significant SNPs were located across the whole genome, except on chromosomes BTA24, BTA27, and BTA29. Four markers (for BCS, BD, HDe, and RLRV) were statistically significant when considering a much stricter threshold for the Bonferroni correction for multiple tests. Moreover, the genomic regions identified overlap with various QTL previously reported for the trait groups of exterior, health, meat and carcass, milk, production, and reproduction. The functional enrichment analyses revealed 27 significant gene ontology terms. These enriched genomic regions harbor various candidate genes previously reported as linked to bone development, metabolism, as well as infectious and immunological diseases.

Using registry data to identify individual dairy cows with abnormal patterns in routinely recorded somatic cell counts

Data from the Danish milk recording system routinely enter the Danish Cattle Database, including somatic cell counts (SCC) for individual animals. Elevated SCC can signal intramammary inflammation, suggesting subclinical mastitis. Detecting mastitis is pivotal to limit severity, prevent pathogen spread, and target treatment or culling. This study aimed to differentiate normal and abnormal SCC patterns using recorded registry data.We used registry data from 2010 to 2020 for dairy cows in herds with 11 annual milk recordings. To create consistency across herds, we used data from 13,996 unique animals and eight different herds, selected based on the amount of data available, only selecting Holstein animals and conventional herds. We fitted log10-transformed SCC to days in milk (DIM) using the Wilmink and Wood’s curve functions, originally developed for milk yield over the lactation. We used Nonlinear Least Square and Nonlinear Mixed Effect models to fit the log10-transformed SCC observations to DIM at animal level.Using mean squared residuals (MSR), we found a consistently better fit using a Wood’s style function. Detection of MSR outliers in the model fitting process was used to identify animals with log10(SCC) curves deviating from the expected “normal” curve for that same animal. With this study, we propose a method to identify single animals with SCC patterns that indicate abnormalities, such as mastitis, based on registry data. This method could potentially lead to a registry data-based detection of mastitis cases in larger dairy herds.

Methane Emission, Carbon Footprint and Productivity of Specialized Dairy Cows Supplemented with Bitter Cassava (Manihot esculenta Crantz).

The objective of this research was to determine the effect of cassava (Manihot esculenta Crantz) supplementation on enteric methane (CH4) emissions, carbon footprint, and production parameters in dairy cows. Daily concentrate supply for Jersey and Jersey * Holstein breeds was evaluated in four treatments (T): T1: 100% commercial concentrate; T2: 70% concentrate + 30% cassava leaves; T3: 70% concentrate + 30% cassava roots; and T4: 70% concentrate + 15% cassava leaves + 15% cassava root chips. Measurements of CH4 emissions were performed using the polytunnel technique. Average daily dry matter intake ranged from 7.8 to 8.5 kg dry matter (DM). Cassava leaves were characterized by a high crude protein (CP) content (171 g CP/kg DM), with 5 times more neutral detergent fiber (NDF) content than cassava root (587 vs. 108 g NDF/kg DM). Average enteric CH4 emissions per animal ranged from 194 to 234 g/d (p > 0.05). The carbon footprint was reduced by replacing 30% of the concentrate with cassava leaves and/or roots. Energy-corrected milk production was 1.15 times higher in Jersey * Holstein animals than Jersey cows (47 vs. 55 kg). Therefore, supplementation with cassava leaves and/or roots is a nutritionally and environmentally sustainable strategy.

Identification of genetic variants and individual genes associated with postpartum hypocalcemia in Holstein cows

Periparturient hypocalcemia is a complex metabolic disorder that occurs at the onset of lactation because of a sudden irreversible loss of Ca incorporated into colostrum and milk. Some cows are unable to quickly adapt to this demand and succumb to clinical hypocalcemia, commonly known as milk fever, whereas a larger proportion of cows develop subclinical hypocalcemia. The main goal of this study was to identify causative mutations and candidate genes affecting postpartum blood calcium concentration in Holstein cows. Data consisted of blood calcium concentration measured in 2513 Holstein cows on the first three days after parturition. All cows had genotypic information for 79 k SNP markers. Two consecutive rounds of imputation were performed: first, the 2513 Holstein cows were imputed from 79 k to 312 k SNP markers. This imputation was performed using a reference set of 17,131 proven Holstein bulls with 312 k SNP markers. Then, the 2513 Holstein cows were imputed from 312 k markers to whole-genome sequence data. This second round of imputation used 179 Holstein animals from the 1000 Bulls Genome Project as a reference set. Three alternative phenotypes were evaluated: (1) total calcium concentration in the first 24 h postpartum, (2) total calcium concentration in the first 72 h postpartum calculated as the area under the curve; and (3) the recovery of total calcium concentration calculated as the difference in total calcium concentration between 72 and 24 h. The identification of genetic variants associated with these traits was performed using a two-step mixed model-based approach implemented in the R package MixABEL. The most significant variants were located within or near genes involved in calcium homeostasis and vitamin D transport (GC), calcium and potassium channels (JPH3 and KCNK13), energy and lipid metabolism (CA5A, PRORP, and SREBP1), and immune response (IL12RB2 and CXCL8), among other functions. This work provides the foundation for the development of novel breeding and management tools for reducing the incidence of periparturient hypocalcemia in dairy cattle.

Quantitative trait loci exploration and characterization of gestation length in Holstein cattle

Gestation length (GL) is a moderately heritable trait in cattle with economic and management implications. This study aimed to characterize the gestation length of an Argentinian Holstein cattle population, understand contributing factors, and explore the GL effect on production performance. Further objectives were to estimate direct and maternal heritabilities for this trait and to identify genomic regions affecting it. Data consisted of GL records from 45,738 births corresponding to 17,004 Holstein cows and heifers. The effects of age and calving season over GL were analyzed using a Student's t-test for homoscedastic samples. The effects of the GL category (GL shorter than 1.5 SD, within ±1.5 SD, and longer than 1.5 SD from the mean) on production performance were studied by analysis of variance. A single-step genome-wide association study was performed using the BLUPF90 suite of programs with genotypes from 654 Holstein animals on 40,339 SNP. The results showed that the younger the age at calving, the shorter the GL. Moreover, gestations ending in warmer seasons were, in general, statistically shorter than those ending in colder seasons for both heifers and cows. Regarding the effect of GL on production performance, cows with gestation periods within ±1.5 SD from the population mean exhibited the highest 305-day cumulative milk, fat, and protein productions. Direct and maternal heritabilities for GL were 0.42 and 0.03, respectively. We detected a SNP suggestively associated with direct gestation length at 57.7 Mb on Bos taurus autosome 18, a locus included in a region described in the literature as associated with the trait. The information obtained on the environmental and genetic factors affecting GL in Argentinian Holstein cows contributes to characterizing the population in pursuit of improving the performance of national dairy cattle breeding systems.

Genome-wide association and functional genomic analyses for various hoof health traits in North American Holstein cattle

Hoof diseases are a major welfare and economic issue in the global dairy cattle production industry, which can be minimized through improved management and breeding practices. Optimal genetic improvement of hoof health could benefit from a deep understanding of the genetic background and biological underpinning of indicators of hoof health. Therefore, the primary objectives of this study were to perform genome-wide association studies, using imputed high-density genetic markers data from North American Holstein cattle, for 8 hoof-related traits: digital dermatitis, sole ulcer, sole hemorrhage, white line lesion, heel horn erosion, interdigital dermatitis, interdigital hyperplasia, and toe ulcer, and a hoof health index. De-regressed estimated breeding values from 25,580 Holstein animals were used as pseudo-phenotypes for the association analyses. The genomic quality control, genotype phasing, and genotype imputation were performed using the PLINK (version 1.9), Eagle (version 2.4.1), and Minimac4 software, respectively. The functional genomic analyses were performed using the GALLO R package and the DAVID platform. We identified 22, 34, 14, 22, 28, 33, 24, 43, and 15 significant markers for digital dermatitis, heel horn erosion, interdigital dermatitis, interdigital hyperplasia, sole hemorrhage, sole ulcer, toe ulcer, white line lesion disease, and the hoof health index, respectively. The significant markers were located across all autosomes, except BTA10, BTA12, BTA20, BTA26, BTA27, and BTA28. Moreover, the genomic regions identified overlap with various previously reported quantitative trait loci for exterior, health, meat and carcass, milk, production, and reproduction traits. The enrichment analyses identified 44 significant gene ontology terms. These enriched genomic regions harbor various candidate genes previously associated with bone development, metabolism, and infectious and immunological diseases. These findings indicate that hoof health traits are highly polygenic and influenced by a wide range of biological processes.

328 Comparison of Predicted Nutritional Requirements of Two Feeding Systems for Dairy Cattle Implemented in a Monte-Carlo Simulation Model of Herd Dynamics

Abstract There is increased interest in precision-feeding systems that account for individual-animal variation and temporal dairy herd dynamics to increase feed-efficiency and reduce environmental footprints. The Ruminant Farm Systems (RuFaS; Hansen et al., 2021) model simulates individual animals on a daily timestep using a stochastic, Monte Carlo framework to represent the phenotypic diversity and population dynamics expected in a dairy herd. Within RuFaS, individual animal nutrient requirements are used to inform pen-level diet formulations and feed delivery. However, nutritional requirements for feeding dairy cattle were recently updated via consideration of both animal and diet-related factors. Our aim was to calculate individual animal predictions for dry matter intake (DMI), as well as energy and metabolizable protein requirements, and compare the methods described in the 7th (NRC, 2001) and 8th (NASEM, 2021) editions of the Nutrient Requirements for Dairy Cattle. For that purpose, we simulated dairy herds (ca. 6,000 individual Holstein animals per simulation, mean adult body weight = 671 kg, standard deviation = 79, mean daily milk production = 39.8 kg·day-1·cow-1 , standard deviation = 7.5) for 10+ year time periods with an updated version of RuFaS. The simulated herds provided a wide range of values with which to test the nutrient requirement models, and their implications. The NASEM DMI estimates were less across the board but began to converge towards NRC calculated values at the larger simulated animal body weights. The principal differences in energy requirements between the two models (NRC vs. NASEM) were: 1) predicted requirements for pregnancy were significantly greater for NASEM than NRC across all life history stages; 2) NASEM displayed slightly greater energy requirements for growth in first and second lactation cows, and; 3) NASEM predicted decreased maintenance requirements for all heifer stages but the opposite was true for mature cows. Metabolizable protein requirements were greater following NASEM calculations in heifers over 300 kg, but strikingly similar to NRC-computed values for lactating cows. Overall, results from this modeling study align with our expectations and demonstrate successful implementation of the two nutrition models within the RuFaS model. These outputs confirm the usefulness of data obtained to explore applications of the two nutrient requirement models under different precision feeding management practices and, to some extent, to quantitatively evaluate their viability of the models in edge cases that can occur within the expected variation of a herd’s population. Future work will explore downstream consequences of the nutrient requirement models within the automated, least-cost ration formulation framework using nonlinear programming and metrics related to manure output and storage. These data will guide further developments of RuFaS as whole farm simulation model and provide insights into expected variation in nutritional requirements within a dynamic set of animals.

The marker effects of a single-step random regression model for 4 test-day traits in German Holsteins

The single-step genomic model has become the golden standard for routine evaluation in livestock species, such as Holstein dairy cattle. The single-step genomic model with direct estimation of marker effects has been proven to be efficient in accurately accounting for millions of genotype records. For diverse applications including frequent genomic evaluation updates on a weekly basis, estimates of the marker effects from the single-step evaluations play a central role in genomic prediction. In this study we focused on exploring the marker effect estimates from the single-step evaluation. Phenotypic, genotypic, and pedigree data were taken from the official evaluation for German dairy breeds in April 2021. A multilactation random regression test-day model was applied to more than 242 million test-day records separately for 4 traits: milk, fat, and protein yields, and somatic cell scores (SCS). Approximately one million genotyped Holstein animals were considered in the single-step genomic evaluations including ∼21 million animals in pedigree. Deregressed multiple across-country breeding values of Holstein bulls having daughters outside Germany were integrated into the national test-day data to increase the reliability of genomic breeding values. To assess the stability and bias of the marker effects of the single-step model, test-day records of the last 4 yr were deleted, and the integrated bulls born in the last 4 yr were truncated from the complete phenotypic dataset. Estimates of the marker effects were shown to be highly correlated, with correlations ∼0.9, between the full and truncated evaluations. Regression slope values of the marker-effect estimates from the full on the truncated evaluations were all close to their expected value, being ∼1.03. Calculated using random regression coefficients of the marker effect estimates, drastically different shapes of the genetic lactation curve were seen for 2 markers on chromosome 14 for the 4 test-day traits. The contribution of individual chromosomes to the total additive genetic variances seemed to follow the polygenic inheritance mode for protein yield and SCS. However, chromosome 14 was found to make an exceptionally large contribution to the total additive genetic variance for milk and fat yields because of markers near the major gene DGAT1. For the first lactation test-day traits, we obtained ∼0 correlations of chromosomal direct genomic values between any pair of the chromosomes; no spurious correlations were found in our analysis, thanks to the large reference population. For trait milk yield, chromosomal direct genomic values appeared to have a large variation in the between-lactation correlations among the chromosomes, especially between first and second or third lactations. The optimal features of the random regression test-day model and the single-step marker model allowed us to track the differences in the shapes of genetic lactation curves down to the individual markers. Furthermore, the single-step random regression test-day model enabled us to better understand the inheritance mode of the yield traits and SCS (e.g., variable chromosomal contributions to the total additive genetic variance and to the genetic correlations between lactations).

Multitrait meta-analyses identify potential candidate genes for growth-related traits in Holstein heifers

Understanding the underlying pleiotropic relationships among growth and body size traits is important for refining breeding strategies in dairy cattle for optimal body size and growth rate. Therefore, we performed single-trait GWAS for monthly-recorded body weight (BW), hip height, body length, and chest girth from birth to 12 mo of age in Holstein animals, followed by stepwise multiple regression of independent or lowly-linked markers from GWAS loci using conditional and joint association analyses (COJO). Subsequently, we conducted a multitrait meta-analysis to detect pleiotropic markers. Based on the single-trait GWAS, we identified 170 significant SNPs, in which 59 of them remained significant after the COJO analyses. The most significant SNP, located at BTA7:3,676,741, explained 2.93% of the total phenotypic variance for BW6 (BW at 6 mo of age). We identified 17 SNPs with potential pleiotropic effects based on the multitrait meta-analyses, which resulted in 3 additional SNPs in comparison to those detected based on the single-trait GWAS. The identified quantitative trait loci regions overlap with genes known to influence human growth-related traits. According to positional and functional analyses, we proposed HMGA2, HNF4G, MED13L, BHLHE40, FRZB, DMP1, TRIB3, and GATAD2A as important candidate genes influencing the studied traits. The combination of single-trait GWAS and meta-analyses of GWAS results improved the efficiency of detecting associated SNPs, and provided new insights into the genetic mechanisms of growth and development in Holstein cattle.

Imputation accuracy from low- to medium-density SNP chips for US crossbred dairy cattle

This study aimed at evaluating the quality of imputation accuracy (IA) by marker (IAm) and by individual (IAi) in US crossbred dairy cattle. Holstein × Jersey crossbreds were used to evaluate IA from a low- (7K) to a medium-density (50K) SNP chip. Crossbred animals, as well as their sires (53), dams (77), and maternal grandsires (63), were all genotyped with a 78K SNP chip. Seven different scenarios of reference populations were tested, in which some scenarios used different family relationships and others added random unrelated purebred and crossbred individuals to those different family relationship scenarios. The same scenarios were tested on Holstein and Jersey purebred animals to compare these outcomes against those attained in crossbred animals. The genotype imputation was performed with findhap (version 4) software (VanRaden, 2015). There were no significant differences in IA results depending on whether the sire of imputed individuals was Holstein and the dam was Jersey, or vice versa. The IA increased significantly with the addition of related individuals in the reference population, from 86.70 ± 0.06% when only sires or dams were included in the reference population to 90.09 ± 0.06% when sire (S), dam (D), and maternal grandsire genomic data were combined in the reference population. In all scenarios including related individuals in the reference population, IAm and IAi were significantly superior in purebred Jersey and Holstein animals than in crossbreds, ranging from 90.75 ± 0.06 to 94.02 ± 0.06%, and from 90.88 ± 0.11 to 94.04 ± 0.10%, respectively. Additionally, a scenario called SPB+DLD(where PB indicates purebread and LD indicates low density), similar to the genomic evaluations performed on US crossbred dairy, was tested. In this scenario, the information from the 5 evaluated breeds (Ayrshire, Brown Swiss, Guernsey, Holstein, and Jersey) genotyped with a 50K SNP chip and genomic information from the dams genotyped with a 7K SNP chip were combined in the reference population, and the IAm and IAi were 80.87 ± 0.06% and 80.85 ± 0.08%, respectively. Adding randomly nonrelated genotyped individuals in the reference population reduced IA for both purebred and crossbred cows, except for scenario SPB+DLD, where adding crossbreds to the reference population increased IA values. Our findings demonstrate that IA for US Holstein × Jersey crossbred ranged from 85 to 90%, and emphasize the significance of designing and defining the reference population for improved IA.

Comparative genetic characteristics of microsatellite profile of holstein and purebred kholmogorsky bulls

Relevance. Due to widespread metisation the Kholmogorskaya breed is on the verge of complete extinction, which requires the development of measures aimed at preserving not only the animals themselves, but also their genetic diversity. Microsatellites can be considered the most convenient for analyzing the genetic state of a population, due to the high level of their polymorphism.Methods. The material for genetic examination was cryocon-served sperm of bulls-producers belonging to the RSUP «Komi» for breeding work (Syktyvkar). Samples from 64 pure-bred Kholmogorsky and 36 with different levels of Holstein breeding bulls were selected for analysis. The allelic structure of STR markers was determined in the laboratory of DNA technologies of FGBNU «VNIIplem». The genetic and statistical analysis was carried out according to the methods generally accepted in biology and animal science.Results. Among purebred bulls 9 privat-alleles were identified, and in crossbreed producers — 13. The most polymorphic among Holstein animals were loci TGLA122 (Na = 10) and TGLA227 (Na = 11), in purebred animals — TGLA227 (Na = 9) and TGLA53 (Na = 10). The maximum correspondence between the number of actual and effective alleles was observed at the BM1824 locus, and the minimum at TGLA227. The Shannon index was the highest for the locus TGLA122 (2,046) in crossbreeds and for TGLA53 (2,011) in purebred bulls, and the lowest for BM1818 (1,050 and 1,174). The diversity of the allelofund of the analyzed loci in the metalized animals was slightly higher (by 0.26). The average fixation index in crossbreeds deviated towards a slight deficit of heterozygosity (0.017), and in purebred bulls an excess (-0.025). The greatest genetic relationship between the two samples was observed at the SPS115 locus (0.996), and the smallest at CSSM66 (0.827).

Features of conformation type of black-andwhite cows of different origin estimated by linear classification method

The research was carried out in the aspect of studying features of conformation type cows of Ukrainian Black-and-White dairy and Holstein breeds estimated by linear classification method. Basis for research was the herd of company "Ukrlandfarming" private enterprise "Burynske", Pidlisniv branch in Sumy region. The aim was to conduct a comparative analysis of experimental breeds according to the assessment of linear classification and determine the impact of final score for type on milk productivity first-born cows. In general, first-born cows of both breeds were characterized by good linear estimation, especially on a 100-score scale. However, animals of Holstein breed in comparison with Ukrainian Black-and-White dairy were better in terms of body parts, which characterize the dairy type by 1.3 score, body - by 0.8 score, udder - by 1.2 score and the final assessment - by 0.8 score (P &lt;0.001). On the trait of chest width, Holstein animals were inferior to their Ukrainian Black-and-White dairy breeds with reliable difference of 1.3 score, but exceeded in angularity - by 1.2 score, strength of fore udder parts attachment - on 0.8 score, central ligament - by 1.1 score (P &lt;0.001). The final estimation level of first-born cows for conformation type directly proportionally determined their milk productivity in 305 days of the first lactation. Cows of Holstein and Ukrainian Black-andWhite dairy breed with score - "very good" exceeded their peers with score - "good with plus" for milking by 785 and 589 kg (P˂0.01) respectively, and with score of "good" - by 1705 and 1502 kg (P˂0.001). The use in the selection process of dairy cattle, in determining cows breeding value, linear classification method will be a very effective means of objective definition breed features of conformation type. The presence of correlative relationship between the final score and milk productivity level will contribute to the effectiveness of selection in the indirect sampling of animals on these traits. Key words: Holstein, Ukrainian Black-andWhite dairy, linear type assessment, conformation, milk yield.

Genomic evaluation of feed efficiency in US Holstein heifers

There is growing interest in improving feed efficiency (FE) traits in dairy cattle. The objectives of this study were to estimate the genetic parameters of RFI and its component traits (Dry matter intake (DMI), metabolic body weight (MBW) and average daily gain (ADG)) of Holstein heifers, and to develop a system for genomic evaluation for RFI in Holstein dairy calves. The RFI data were collected from 6,563 growing Holstein heifers (initial BW = 261 ± 52 kg; initial age = 266 ± 42 d) for 70 d, across 182 trials conducted between 2014 and 2022 at the STgenetics Ohio Heifer Center (South Charleston, Ohio) as part of EcoFeed® program which aims to improve FE by genetic selection. RFI was estimated as the difference between a heifer's actual feed intake and its expected feed intake, which was determined by regression of DMI against mid-point MBW, age, and ADG across each trial. A total of 61,283 single nucleotide polymorphisms were used in genomic analyses. Animals with phenotypes and genotypes were used as training population and 4 groups of prediction population, each with 2,000 animals, were selected from a pool of Holstein animals with genotypes, based on their relationship with the training population. All traits were analyzed using univariate animal model in DMU version 6 software. Pedigree information and genomic information were used to specify genetic relationships to estimate the variance components and genomic estimated breeding values (GEBVs), respectively. Breeding values of prediction population were estimated by using the 2-step approach, i.e., deriving the prediction equation of GEBVs from training population for the estimation of GEBVs of prediction population with only genotypes. Reliability of breeding values were obtained by approximation based on partitioning a function of accuracy of training population GEBVs and magnitudes of genomic relationships between individuals in the training and prediction population. Heifers had DMI (mean ± SD) of 8.11 ± 1.59 kg over the period of trial with growth rate of 1.08 ± 0.25 kg/d. The heritability estimates (mean ± SE) of RFI, MBW, DMI, and growth rate were 0.24 ± 0.02, 0.23 ± 0.02, 0.27 ± 0.02, and 0.19 ± 0.02, respectively. The range of genomic predicted transmitted abilities (gPTAs) of training population (-0.94 to 0.75) was higher compared with the range of gPTAs (-0.82 to 0.73) of different groups of prediction population. Average reliability of breeding values from training population was 58% and that of prediction population was 39%. The genomic prediction of RFI provided new tools to select for feed efficiency of heifers. Future research should be directed to find the relationship between RFI of heifers and cows, to select individuals based on their lifetime production efficiencies.

Metabolic indicators and their relationship with reproductive efficiency in dairy cows in the high tropics

The specialized herds of the high tropics of Nariño are characterized by semi-intensive breeding models, that is, feeding based on grazing and supplementation. The objective was to analyze the milk production of grazing Holstein cows under conditions of the high tropics, taking into account the energetic and protein metabolites, and their relationship with the dry matter intake (CMS/Kg/d), the body condition (BC), and the reproductive variables. Three periods of lactation were evaluated, thus, between 4-10 days (P1), 45-55 days (P2), and between 185-200 days (P3). The investigation was carried out in four dairy production farms. The forage supply consisted of a mixture of Lolium hybridum, Cenchrus clandestinus Hoschst ex Chiov, Holcus lanatus and Trifolium repens, plus commercial concentrate. A total of 24 Holstein animals (six per productive system) from three births onwards were used, from which blood samples were obtained to determine: non-esterified fatty acids (NEFA), beta-hydroxybutyrate (BHB), triglycerides, cholesterol, glucose, total protein (PT), and blood urea nitrogen (BUN). The results showed that milk production during P1 is influenced by CC and body weight (Kg) by +0.04 liters of milk per unit of change in this variable. In P2, the positive incidence variables were PT, BUN, glucose, NEFA, BHB, triglycerides, and cholesterol, and in P3, the increase in CMS made it possible to show that as lactation progresses in more than 180 days, the animals substantially improve their body condition; likewise the NEFA and BHB indicators are related to a better reproductive response.

Comparison of cattle derived from in vitro fertilization, multiple ovulation embryo transfer, and artificial insemination for milk production and fertility traits

The use of assisted-reproduction technologies such as in vitro fertilization (IVF) is increasing, particularly in dairy cattle. The question of consequences in later life has not yet been directly addressed by studies on large animal populations. Studies on rodents and early data from humans and cattle suggest that in vitro manipulation of gametes and embryos could result in long-term alteration of metabolism, growth, and fertility. Our goal was to better describe these presumed consequences in the population of dairy cows produced by IVF in Québec (Canada) and to compare them to animals conceived by artificial insemination (AI) or multiple ovulation embryo transfer (MOET). To do so, we leveraged a large phenotypic database (2.5 million animals and 4.5 million lactations) from milk records in Québec aggregated by Lactanet (Sainte-Anne-de-Bellevue, QC, Canada) and spanning 2012 to 2019. We identified 304,163, 12,993, and 732 cows conceived by AI, MOET, and IVF, respectively, for a total of 317,888 Holstein animals from which we retrieved information for 576,448, 24,192, and 1,299 lactations (total = 601,939), respectively. Genetic energy-corrected milk yield (GECM) and Lifetime Performance Index (LPI) of the parents of cows were used to normalize for genetic potential across animals. When compared with the general Holstein population, MOET and IVF cows outperformed AI cows. However, when comparing those same MOET and IVF cows with only herdmates and accounting for their higher GECM in the models, we found no statistical difference between the conception methods for milk production across the first 3 lactations. We also found that the rate of Lifetime Performance Index improvement of the IVF population during the 2012 to 2019 period was less than the rate observed in the AI population. Fertility analysis revealed that MOET and IVF cows also scored 1 point lower than their parents on the daughter fertility index and had a longer interval from first service to conception, with an average of 35.52 d compared with 32.45 for MOET and 31.87 for AI animals. These results highlight the challenges of elite genetic improvement while attesting to the progress the industry has made in minimizing epigenetic disturbance during embryo production. Nonetheless, additional work is required to ensure that IVF animals can maintain their performance and fertility potential.

Individual animal variability in rumination, activity, and lying behavior during the periparturient period of dairy cattle

The aim of the current study was to determine individual animal variability in rumination, activity, and lying behavior during the periparturient period within the context of dairy cattle nutrition, social, and physical environment. Holstein animals (nulliparous = 77, parous = 219) from one sand-bedded, freestall dairy in northwest Wisconsin were enrolled −17 d in milk (DIM, d 0 = calving), when they were fitted with an automated monitoring device (Hi-Tag, SCR Engineers Ltd.). At −11 DIM, animals were fitted with HOBO Pendant G Data Loggers. The HOBO Pendant G Data Loggers were fitted 6 d later because they were set up to collect data for 22 d (d −11 to 11), to avoid constant handling of the animals that could alter their behavior. Prepartum, nulliparous and parous animals were housed separately. Postpartum (1 to 17 ± 3 DIM), primiparous and multiparous cows were commingled. Samples of the total mixed ration were submitted for wet chemistry analysis and determination of physically effective NDF (peNDF). Temperature and humidity data were collected using RH Temp probes (HOBO Pro Series) installed in each of the pens, and the percentages of 30-min intervals within a day with temperature-humidity index ≥68 (PctTHI68) were calculated. Stocking density (cows per stall) during the pre- and postpartum periods were calculated daily. Prepartum data from nulliparous and parous animals were analyzed separately, and postpartum data from primiparous and multiparous animals were analyzed together. Prepartum, nulliparous and parous animals explained 83.9 and 64.5% of the variability in rumination, 70.7 and 60.9% of the variability in activity, and 38.1 and 63.6% of the variability in lying time, respectively. Postpartum, animal explained 49.7, 56.8, and 35.6% of the variability in rumination, activity, and lying time, respectively. Although stocking density, PctTHI68, peNDF, crude protein, and ether extract were associated with the variability in rumination, activity, and lying time, they explained ≤6.6% of the daily variability in these behaviors. We conclude that, within the conditions of the collaborating commercial herd, individual animal is the most important factor explaining daily variability in rumination, activity, and lying time.

ЭФФЕКТЫ СТЕРОИДНЫХ ГОРМОНОВ НА ТРОМБОЦИТАРНЫЙ СОСТАВ В ОРГАНИЗМЕ МОЛОДЫХ ЖИВОТНЫХ ГОЛШТИНО-ФРИЗСКОЙ ПОРОДЫ

In modern veterinary medicine, reference books with population “classical intervals” are used to decipher laboratory blood tests, but they do not reflect the biological specificity of the organism, such as sex, breed, age, and environment. Therefore, this work provides an assessment of the ability of steroid hormones (progesterone and cortisol) to regulate the platelet composition of blood in the body of young Holstein animals, as well as the determination of reference limits for hemostasis parameters. Young animals (n=10) were selected as the object of the study, selected for the experimental group on the principle of approximate analogues, from which blood was taken at 3, 6, 9, 12 and 15 months of age and hemostasis parameters were determined. It was found that the number of platelets from 3 to 15 months of age increases by 1.50 times (p≤0.05). At the same time, the concentration of progesterone and cortisol in the blood of heifers shows the least variability from the 3rd to the 9th months of rearing, increasing by 2.13 and 2.29 times, respectively. From the 3rd to the 9th month of heifer rearing, statistically significant correlations were found only in pairs with cortisol: Cortisol - Platelets (r=0.74±0.23–0.97±0.08), Cortisol - Megalotlatembocytes (r=- 0.77±0.22–-0.89±0.17). Starting from 9 months of age, progesterone significantly correlates with the number of platelets (r=0.72±0.23–0.92±0.08), thrombocrit (r=0.90±0.14–0.93±0, 13) and megalotlatelets (r=-0.90±0.15–-0.95±0.11).