Milk Production Traits Research Articles

Toll like receptor 4 (TLR4) gene polymorphism and its association with somatic cell score and milk production traits in Indian dromedary camels

Our study aimed to explore the genetic variation in the Toll-like receptor 4 (TLR4) gene and establish its association with somatic cell score (SCS) and milk production traits in four Indian camel breeds namely Bikaneri, Kachchhi, Jaisalmeri and Mewari. TLR4 gene fragment of 573 bp spanning 5’ UTR, exon-1 and partial intron-1 region was amplified and genotyped using the PCR-sequence based typing method. Only one SNP located at position C472T was identified. Genotyping revealed two alleles (C and T) and three genotypes: CC, CT and TT. The genotype frequencies for CC, CT and TT were 0.116, 0.326 and 0.558 and allele frequencies for C and T alleles were 0.279 and 0.721, respectively. Association study inferred that the effect of genotype on SCS, lactation yield (LY) and peak yield (PY) was non-significant however heterozygote (CT) genotypes recorded lower SCS and higher LY and PY. It can be concluded that the TLR4 gene possesses limited genetic variation, depicting polymorphism at a single locus in Indian camel breeds with a predominance of the TT genotype. The association study indicated that heterozygote animals possess better udder health and production performance, the statistical significance of which needs to be established using a large data set.

Genetic variation in bovine LAP3 and SIRT1 genes associated with fertility traits in dairy cattle.

The genetic progress of fertility and reproduction traits in dairy cattle has been constrained by the low heritability of these traits. Identifying candidate genes and variants associated with fertility and reproduction could enhance the accuracy of genetic selection and expedite breeding process of dairy cattle with low-heritability traits. While the bovine LAP3 and SIRT1 genes exhibit well-documented associations with milk production traits in dairy cattle, their effect on cow fertility have not yet been explored. Eleven single nucleotide polymorphisms (SNPs), comprising five in the promoter (rs717156555: C > G, rs720373055: T > C, rs516876447: A > G, rs461857269: C > T and rs720349928: G > A), two in 5'UTR (rs722359733: C > T and rs462932574: T > G), two in intron 12 (rs110932626: A > G and rs43702363: C > T), and one in 3'UTR of exon 13 (rs41255599: C > T) in LAP3 and one in SIRT1 (rs718329990:T > C) genes, have previously been reported to be associated with various traits of milk production and clinical mastitis in Sahiwal and Karan Fries dairy cattle. In this study, the analysis primarily aimed to assess the impact of SNPs within LAP3 and SIRT1 genes on fertility traits in Sahiwal and Karan Fries cattle. Association studies were conducted using mixed linear models, involving 125 Sahiwal and 138 Karan Fries animals in each breed. The analysis utilized a designated PCR-RFLP panel. In the promoter region of the LAP3 gene, all variants demonstrated significant (P < 0.05) associations with AFC, except for rs722359733: C > T. However, specific variants with the LAP3 gene's promoter region, namely rs722359733: C > T, rs110932626: A > G, rs43702363: C > T, and rs41255599: C > T, showed significant associations with CI and DO in Sahiwal and Karan Fries cows, respectively. The SNP rs718329990: T > C in the promoter region of SIRT1 gene exhibited a significant association with CI and DO in Sahiwal cattle. Haplotype-based association analysis revealed significant associations between haplotype combinations and AFC, CI and DO in the studied dairy cattle population. Animals with H2H3 and H2H4 haplotype combination exhibited higher AFC, CI and DO than other combinations. These results affirm the involvement of the LAP3 and SIRT1 genes in female fertility traits, indicating that polymorphisms within these genes are linked to the studied traits. Overall, the significant SNPs and haplotypes identified in this study could have the potential to enhance herd profitability and ensure long-term sustainability on dairy farms by enabling the selection of animals with early age first calving and enhance reproductive performance in the dairy cattle breeding program.

Relationship Polymorphism of STAT5A Gene in Performance Production of Local Goats

The study was conducted on a sample of 30 local goats in Diyala governorate / Canaan district in one of the goat breeders' fields in the region for the period from 13/11/2022 to 1/5/2022 to determine the genotype of the gene STAT5A EXON-7 and Its relationship to milk production (daily milk production-DMP and total milk production-TMP) and growth traits (birth weight-BWT, weaning weight-WWT and total weight gain-TWG). The analysis showed three-point mutations (CC=18 CT=12 C47064T AA=17 AT=13 A47088T and GG=15 GA=15 G47162A). There was no significant effect of the genotypes of the three mutations on all studied traits DMP, TMP, BWT, WWT, TWG, and body dimensions of the newborn at birth and weaning, body dimensions of the newborn at birth and weaning. Keywords: Local goats, milk production, gene STAT5A EXON-7.

Genomic dissection of the correlation between milk yield and various health traits using functional and evolutionary information about imputed sequence variants of 34,497 German Holstein cows

BackgroundOver the last decades, it was subject of many studies to investigate the genomic connection of milk production and health traits in dairy cattle. Thereby, incorporating functional information in genomic analyses has been shown to improve the understanding of biological and molecular mechanisms shaping complex traits and the accuracies of genomic prediction, especially in small populations and across-breed settings. Still, little is known about the contribution of different functional and evolutionary genome partitioning subsets to milk production and dairy health. Thus, we performed a uni- and a bivariate analysis of milk yield (MY) and eight health traits using a set of ~34,497 German Holstein cows with 50K chip genotypes and ~17 million imputed sequence variants divided into 27 subsets depending on their functional and evolutionary annotation. In the bivariate analysis, eight trait-combinations were observed that contrasted MY with each health trait. Two genomic relationship matrices (GRM) were included, one consisting of the 50K chip variants and one consisting of each set of subset variants, to obtain subset heritabilities and genetic correlations. In addition, 50K chip heritabilities and genetic correlations were estimated applying merely the 50K GRM.ResultsIn general, 50K chip heritabilities were larger than the subset heritabilities. The largest heritabilities were found for MY, which was 0.4358 for the 50K and 0.2757 for the subset heritabilities. Whereas all 50K genetic correlations were negative, subset genetic correlations were both, positive and negative (ranging from -0.9324 between MY and mastitis to 0.6662 between MY and digital dermatitis). The subsets containing variants which were annotated as noncoding related, splice sites, untranslated regions, metabolic quantitative trait loci, and young variants ranked highest in terms of their contribution to the traits’ genetic variance. We were able to show that linkage disequilibrium between subset variants and adjacent variants did not cause these subsets’ high effect.ConclusionOur results confirm the connection of milk production and health traits in dairy cattle via the animals’ metabolic state. In addition, they highlight the potential of including functional information in genomic analyses, which helps to dissect the extent and direction of the observed traits’ connection in more detail.

Multi-omics reveals the mechanism of rumen microbiome and its metabolome together with host metabolome participating in the regulation of milk production traits in dairy buffaloes.

Recently, it has been discovered that certain dairy buffaloes can produce higher milk yield and milk fat yield under the same feeding management conditions, which is a potential new trait. It is unknown to what extent, the rumen microbiome and its metabolites, as well as the host metabolism, contribute to milk yield and milk fat yield. Therefore, we will analyze the rumen microbiome and host-level potential regulatory mechanisms on milk yield and milk fat yield through rumen metagenomics, rumen metabolomics, and serum metabolomics experiments. Microbial metagenomics analysis revealed a significantly higher abundance of several species in the rumen of high-yield dairy buffaloes, which mainly belonged to genera, such as Prevotella, Butyrivibrio, Barnesiella, Lachnospiraceae, Ruminococcus, and Bacteroides. These species contribute to the degradation of diets and improve functions related to fatty acid biosynthesis and lipid metabolism. Furthermore, the rumen of high-yield dairy buffaloes exhibited a lower abundance of methanogenic bacteria and functions, which may produce less methane. Rumen metabolome analysis showed that high-yield dairy buffaloes had significantly higher concentrations of metabolites, including lipids, carbohydrates, and organic acids, as well as volatile fatty acids (VFAs), such as acetic acid and butyric acid. Meanwhile, several Prevotella, Butyrivibrio, Barnesiella, and Bacteroides species were significantly positively correlated with these metabolites. Serum metabolome analysis showed that high-yield dairy buffaloes had significantly higher concentrations of metabolites, mainly lipids and organic acids. Meanwhile, several Prevotella, Bacteroides, Barnesiella, Ruminococcus, and Butyrivibrio species were significantly positively correlated with these metabolites. The combined analysis showed that several species were present, including Prevotella.sp.CAG1031, Prevotella.sp.HUN102, Prevotella.sp.KHD1, Prevotella.phocaeensis, Butyrivibrio.sp.AE3009, Barnesiella.sp.An22, Bacteroides.sp.CAG927, and Bacteroidales.bacterium.52-46, which may play a crucial role in rumen and host lipid metabolism, contributing to milk yield and milk fat yield. The "omics-explainability" analysis revealed that the rumen microbial composition, functions, metabolites, and serum metabolites contributed 34.04, 47.13, 39.09, and 50.14%, respectively, to milk yield and milk fat yield. These findings demonstrate how the rumen microbiota and host jointly affect milk production traits in dairy buffaloes. This information is essential for developing targeted feeding management strategies to improve the quality and yield of buffalo milk.

ОЦЕНКА ПЛЕМЕННОЙ ЦЕННОСТИ КОРОВ СИММЕНТАЛЬСКОЙ ПОРОДЫ ПО ПОЖИЗНЕННОЙ ПРОДУКТИВНОСТИ В ЗАВИСИМОСТИ ОТ ВОЗРАСТА ВЫБЫТИЯ И ПРОИСХОЖДЕНИЯ

The purpose of research is to study the variability of genetic assessments of cows of different origins for traits of lifelong milk production when varying the age of retirement in the population of Simmental cattle in Russia. The analyzed database included breeding cows of the Simmental breed that were retired in the pe¬riod 2001–2020; the total number of livestock was 47,868 head. Calculation of the breeding value of productive longevity was carried out using the BLUPF90 program based on the BLUP Animal Model methodology. The share of Simmental cows of foreign selection that were eliminated after the 1st and 2nd lactations was 61.2 %, and those lactating longer than 6 lactations was only 4.0 %, while cows of Russian selection were 12.3 % less eliminated during the first two lactation and are able to produce longer. Phenotypic values of lifetime productivity in Simmental cows for an equal number of lactations are significantly higher in animals of foreign selection: from 824 kg of milk when leaving after the 1st lactation to 4,210 kg when leaving after the 10th lactation, from 35.3 to 188.5 kg by lifetime amount of fat and from 27.3 to 190.9 kg by lifetime amount of protein, respectively. The maximum estimates of breeding value for the lifetime productivity of a cow of fo¬reign selection reach +115.7 kg of milk fat and +91.3 kg of milk protein for a productive life by the 7th lactation.In cows of Russian selection, the predicted maximum breeding value estimates are achieved by the 9th lactation with indicators of +111.0 kg of milk fat and +88.4 kg of milk protein during the period of productive use. Lifetime milk productivity is significantly higher in Simmental cows of imported origin (by +824...+4210 kg), as well as estimates of breeding value (by +27.5...+35.9 kg), however, domestic Simmentals had a longer use period – on average for 2 lactations.

Associations Between BLG, CSN3, DGAT1, GH, PIT1, and PRL Gene Polymorphisms and Milk Production Traits in Holstein Dairy Cows: A Meta-Analysis.

The current meta-analysis was employed to combine the results of multiple studies into a single estimate related to B-LG, CSN3, DGAT1, PRL, GH, and PIT1 gene polymorphisms and their effects on milk production traits. The purpose of this meta-analysis was to investigateassociations between B-LG, CSN3, DGAT1, GH, PIT1, and PRLgene polymorphisms with milk production traits in Holstein dairy cows. An extensive search was done from 2002 to 2022year. Statistical analyses were performed by using Stata 11.2 software. Genetic models viz codominant (AA vs. AB, AA vs. BB, and AB vs. BB), dominant (AA + AB vs. BB), recessive (AA vs. AB + BB), and completely over-dominant (AA + BB vs. AB) were applied. The results of meta-analysis of association between B-LG genotypes with milk yield where found a significant (P < 0.05) and with fat and protein contents (P < 0.01). In CSN3 polymorphisms of A/A and A/B genotypes had a significant effect on fat yield (P < 0.05) and protein content (P < 0.01). DGAT1 polymorphisms had a significant effect on milk yield, fat yield, protein yield (P < 0.05), with fat and protein contents showed high effect (P < 0.01). No significant association was detected between GH and milk traits (P > 0.05). PIT1 genotype polymorphisms had a significant effect on milk yield (P < 0.05) and protein content (P < 0.01). PRL genotype polymorphisms were significantly associated with milk yield (P < 0.05), fat content and protein yield (P < 0.01). The B-LG, DGAT1,CSN3 and PRL gene polymorphisms could be utilized as good markers to improve milk production traits in the Holstein cattle breed.

Association of three single nucleotide polymorphisms in the LPIN1 gene with milk production traits in cows of the Yaroslavl breed.

Lipin-1 is a member of the evolutionarily conserved family of proteins and is expressed predominantly in adipose tissue and skeletal muscle. On the one hand, lipin-1 is an enzyme that catalyzes the dephosphorylation of phosphatidic acid to diacylglycerol (DAG) and thus participates in the metabolic pathways of biosynthesis of storage lipids in the cell, membrane phospholipids, and intracellular signaling molecules. On the other hand, lipin-1 is able to be transported from the cytoplasm to the nucleus and is a coactivator of lipid metabolism gene transcription. It was shown, using the analysis of single nucleotide polymorphism (SNP) associations, that the lipin-1 coding gene (LPIN1) is a promising candidate gene for milk production traits in Holstein and Brown Swiss cows. However, it is unclear how much of its effect depends on the breed. The Yaroslavl dairy cattle breed was created in the 18-19 centuries in Russia by breeding northern Great Russian cattle, which were short and poor productive, but well adapted to local climatic conditions and bad food base. It was shown by whole genome genotyping and sequencing that the Yaroslavl breed has unique genetics compared to Russian and other cattle breeds. The aim of the study was to assess the frequency of alleles and genotypes of three SNPs in the LPIN1 gene and to study the association of these SNPs with milk production traits in Yaroslavl cows. Blood samples from 142 cows of the Yaroslavl breed were obtained from two farms in the Yaroslavl region. Genotyping of SNPs was carried out by polymerase chain reaction-restriction fragment length polymorphism method. Associations of SNPs with 305-day milk yield, fat yield, fat percentages, protein yield, and protein percentages were studied from the first to the fourth lactation. Statistical tests were carried out using a mixed linear model, taking into account the relationship between individuals. We identified three SNPs - rs110871255, rs207681322 and rs109039955 with a frequency of a rare allele of 0.042-0.261 in Yaroslavl cows. SNP rs110871255 was associated with fat yield during the third and fourth lactations. SNP rs207681322 was associated with milk yield for the second, third and fourth lactations, as well as protein yield for the third lactation. Thus, we identified significant associations of SNPs rs207681322 and rs110871255 in the LPIN1 gene with a number of milk production traits during several lactations in Yaroslavl cows.

Relationship between evaluations of sires in pale-motley cattle population at different levels of management

Reproductive technologies have led to a wide and global distribution of genetic material from animals with high productivity. However, the distribution of semen from the same bulls to different regions (countries) may not always meet the expectations of livestock breeders. This aspect may be due to the fact that the genetic structure of the breeding stock, breeding goals and environmental conditions vary from region to region. The article presents the results of evaluating the breeding value of 286 sires used on the breeding stock of the pale-motley dairy cattle population in five regions of the Russian Federation (Belgorod, Voronezh, Kursk, Oryol regions and Altai Territory). The evaluation was carried out according to individual traits of daughters' milk productivity, and on multiple traits (selection index). Based on the results of the study, differences were identified in estimates of the breeding value of the same sires at the level of total information (population level) and in the herds of single regions (regional level). The accuracy of evaluating genotypes at the population management level was significantly higher (by 7–15 percent) than it was at regional levels. The correlations between the breeding value of the same sires at different levels of management (population-region) for single traits of daughter’s milk productivity were 0.522–0.960, for the complex of traits (selection index) – from 0.157 to 0.937. This indicates that when selecting the best sires at the level of an individual region, mistakes can reach 4–48 % for single milk productivity traits and from 6.3 to 84 % for their complex.

Transcriptome-Wide Association Study Reveals Potentially Candidate Genes Responsible for Milk Production Traits in Buffalo.

Identifying key causal genes is critical for unraveling the genetic basis of complex economic traits, yet it remains a formidable challenge. The advent of large-scale sequencing data and computational algorithms, such as transcriptome-wide association studies (TWASs), offers a promising avenue for identifying potential causal genes. In this study, we harnessed the power of TWAS to identify genes potentially responsible for milk production traits, including daily milk yield (MY), fat percentage (FP), and protein percentage (PP), within a cohort of 100 buffaloes. Our approach began by generating the genotype and expression profiles for these 100 buffaloes through whole-genome resequencing and RNA sequencing, respectively. Through comprehensive genome-wide association studies (GWAS), we pinpointed a total of seven and four single nucleotide polymorphisms (SNPs) significantly associated with MY and FP traits, respectively. By using TWAS, we identified 55, 71, and 101 genes as significant signals for MY, FP, and PP traits, respectively. To delve deeper, we conducted protein-protein interaction (PPI) analysis, revealing the categorization of these genes into distinct PPI networks. Interestingly, several TWAS-identified genes within the PPI network played a vital role in milk performance. These findings open new avenues for identifying potentially causal genes underlying important traits, thereby offering invaluable insights for genomics and breeding in buffalo populations.

Genome-Wide Analysis of Milk Production Traits and Selection Signatures in Serbian Holstein-Friesian Cattle.

To improve the genomic evaluation of milk-related traits in Holstein-Friesian (HF) cattle it is essential to identify the associated candidate genes. Novel SNP-based analyses, such as the genetic mapping of inherited diseases, GWAS, and genomic selection, have led to a new era of research. The aim of this study was to analyze the association of each individual SNP in Serbian HF cattle with milk production traits and inbreeding levels. The SNP 60 K chip Axiom Bovine BovMDv3 was deployed for the genotyping of 334 HF cows. The obtained genomic results, together with the collected phenotypic data, were used for a GWAS. Moreover, the identification of ROH segments was performed and served for inbreeding coefficient evaluation and ROH island detection. Using a GWAS, a polymorphism, rs110619097 (located in the intron of the CTNNA3 gene), was detected to be significantly (p < 0.01) associated with the milk protein concentration in the first lactation (adjusted to 305 days). The average genomic inbreeding value (FROH) was 0.079. ROH islands were discovered in proximity to genes associated with milk production traits and genomic regions under selection pressure for other economically important traits of dairy cattle. The findings of this pilot study provide useful information for a better understanding of the genetic architecture of milk production traits in Serbian HF dairy cows and can be used to improve lactation performances in Serbian HF cattle breeding programs.

Estimates of genetic parameters for rumination time, feed efficiency, and methane production traits in first-lactation Holstein cows

The large-scale recording of traits such as feed efficiency and methane emissions for use in genetic improvement programs is complex, costly, and time-consuming. Therefore, heritable traits that can be continuously recorded in dairy herds and are correlated to feed efficiency and methane emission traits could provide useful information for genetic evaluation. Rumination time has been suggested to be associated with feed efficiency, methane production (methane emission in g/day), and production traits at the phenotypic level. Therefore, the objective of this study was to investigate the genetic relationships among rumination time, feed efficiency, methane and production traits using 7,358 records from 656 first lactation Holstein cows. The estimated heritabilities were moderate for rumination time (0.45 ± 0.14), methane production (0.36 ± 0.12), milk yield (0.40 ± 0.08), fat yield (0.29 ± 0.06), protein yield (0.32 ± 0.07), and energy corrected milk (0.28 ± 0.07), while low and non-significant for feed efficiency (0.15 ± 0.07), which was defined as the residual of the multiple linear regression of DMI on ECM and MBW. A favorable negative genetic correlation was estimated between rumination time and methane production (-0.53 ± 0.24), while a positive favorable correlation was estimated between rumination time and energy corrected milk (0.49 ± 0.11). The estimated genetic correlation of rumination time with feed efficiency (-0.01 ± 0.17) was not significantly different from zero but showed a trend of a low correlation with dry matter intake (0.21 ± 0.13, P = 0.11). These results indicate that rumination time is genetically associated with methane production and milk production traits, but high standard errors indicate that further analyses should be conducted to verify these findings when more data for rumination time, methane production and feed efficiency become available.

Systematic Review of Single Nucleotide Polymorphisms of Cattle Beta-Lactoglobulin Gene and their Association with Milk Production Traits

Systematic Review of Single Nucleotide Polymorphisms of Cattle Beta-Lactoglobulin Gene and their Association with Milk Production Traits

Polymorphism Analysis of DGAT1 Gene and Novel Association Studies with Milk Production Traits in Domestic Dromedary Camel in India

Several polymorphisms related to different gene loci have been proven to affect milk production traits and milk composition in camel. The current investigation was carried out in order to determine the genetic polymorphism of the DGAT1 gene and its association with milk production traits in camels. The SNP analysis focused on a 773 bp long fragment of the DGAT1 gene that was amplified using specific primer pairs through PCR. The Novel dromedary sequencing results revealed partial exon-6,10; complete exon-7, 8, and 9 as well as complete intron-6, 7, 8, and 9 in the 773 bp DNA fragment. A single nucleotide variation was identified at position 463 C&gt;T of exon-8 in both Bikaneri and Kachchhi breeds. Association studies of genotypes of DGAT1 gene (CC and CT) with milk production and composition traits were examined using GLM in SPSS. The effect of breed on lactation yield and lactation length was found non-significant (P&gt;0.05) and the effect of breed on peak yield was found highly significant (P≤0.01) and on average daily milk yield was found significant (P≤0.05). Effect of genotype, year of calving, age of calving and parity on lactation length, lactation yield, peak yield and average daily milk yield were found non-significant (P&gt;0.05).

Effect of extended heat stress in dairy cows on productive and behavioral traits

This study evaluates the response of dairy cows to short and extended heat stressing conditions (from 1 to 28 days), as expressed in changes in their behavior. Due to climate change, heat stress and strong heat waves are frequently affecting the productivity and behavior of dairy cows. In the five years under study from 2018 to 2022, two were characterized by extremely strong heat waves occurring in the region analyzed in this study (Northern Italy). The dairy cattle farm involved in this study is located in Northern Italy and includes about 1 600 Holstein Friesian lactating dairy cows. Phenotypic data were provided by the Afimilk system and compromised behavioral and productive traits. Behavioral traits analyzed were activity, rest time, rest bouts, rest ratio, rest per bout and restlessness. Production traits were daily milk yield, average milking time, somatic cell count, fat percentage, protein percentage and lactose percentage. Climate data came from the National Aeronautics and Space Administration/Prediction of Worldwide Energy Resources database. Heat stress was analyzed considering Temperature-Humidity Index (THI) averaged over 28 different time windows of continuous heat stress. Results showed that rest time and milk yield were the two traits most affected by the increased THI. Rest time was immediately affected by high THI, showing a marked decrease already from 1d window and maintaining this all over the other windows. Furthermore, results show that rest time and rest ratio were only slightly negatively correlated with milk yield (−0.14 and −0.15). In addition, heat stress has a different effect depending on parity and lactation stages on the studied traits. In conclusion, the results indicate that heat stress increases activity and compromises milk production, rest time and milk quality traits. Results further suggest that rest time can be a better parameter than activity to describe the effects of heat stress on dairy cattle. The novel approach used in this study is based on the use of different time windows (up to 28 days) before the emergence of undesired THI and allows to identify the traits that are immediately influenced by the undesirable THI values and those that are influenced only after a prolonged heat stress period.

Variation in protein metabolism biomarkers during the transition period and associations with health, colostrum quality, reproduction, and milk production traits in Holstein cows

The aims of this study were to assess (1) the variation of protein metabolism biomarkers and factors affecting them during the transition period, (2) the association of each biomarker with skeletal muscle reserves and their changes, and (3) the association of these biomarkers with postpartum health, colostrum quality, reproduction, and milk production. For this purpose, 238 multiparous Holstein cows from 6 herds were used in a prospective cohort study. Plasma concentrations of 3-methylhistidine (3-MH) and 1-methylhistidine (1-MH) and serum concentrations of total protein (TP), albumin (ALB), urea nitrogen (BUN), and creatinine (SCR) were determined for each cow at -21, -7, 7, 21, and 28 d relative to calving. Clinical diseases were recorded during the first 28 d postcalving, and presence of subclinical ketosis (scKET) was investigated at 7 and 21 d. Colostrum quality was estimated by Brix refractometry. Reproduction data by 150 d in milk (DIM) and milk production records were also available. Linear mixed models including the fixed effects of time point, herd, parity, body condition score (-21 d), duration of dry period and postparturient diseases were fitted to assess the variation in each biomarker's concentration. The association between the biomarkers' concentration during the prepartum period with the odds for each postparturient disease and for a combined trait (CD_1-28), defined as the presence of at least one clinical condition during the first 28 d after calving, were assessed with separate binary logistic models for time points -21 d and -7 d. The relationship of each biomarker's concentration with longissimus dorsi thickness (LDT) and the changes in LDT (ΔLDT) was assessed with pairwise correlations. Separate general linear models were used to assess the association of each biomarker with colostrum Brix values and milk production traits. Finally, the associated hazard for first artificial insemination (AI) and for pregnancy by 150 DIM (PREG_150DIM) was assessed with Cox proportional hazard models, whereas odds for pregnancy to the first AI (PREG_1stAI) were assessed with binary logistic models. The level of 3-MH was affected mainly by herd, time points, and their interaction. Higher 3-MH was associated with increased odds for metritis and CD_1-28, increased hazard for PREG_150 DIM and with increased milk production. 1-Methylhistidine was affected mainly by herd, scKET and occurrence of displaced abomasum. Higher 1-MH was associated with better colostrum quality, increased odds for scKET, increased hazard for first AI by 150 DIM and with decreased milk production. Both 3-MH and 1-MH were weakly to moderately negatively correlated with LDT and moderately to strongly negatively correlated with ΔLDT at the corresponding time periods. Additionally, higher TP was associated with increased odds for metritis and CD_1-28 and increased milk production, while higher ALB was associated with increased odds for scKET and increased milk production. Moreover, higher BUN was associated with decreased odds for scKET, increased odds for PREG_1stAI and increased milk production. Higher SCR was associated with decreased odds for retained fetal membranes, metritis, and CD_1-28. Periparturient protein metabolism is significantly associated with postpartum health, colostrum quality, reproduction, and milk production; mechanisms involved require further investigation.

Genetic parameters for novel mastitis traits defined by combining test-day somatic cell score and differential somatic cell count in the first lactation of Japanese Holsteins

In this study, we aimed to improve current udder health genetic evaluations by addressing the limitations of monthly sampled somatic cell score (SCS) for distinguishing cows with robust innate immunity from those susceptible to chronic infections. The objectives were to (1) establish novel somatic cell traits by integrating SCS and the differential somatic cell count (DSCC), which represents the combined proportion of polymorphonuclear leukocytes and lymphocytes in somatic cells and (2) estimate genetic parameters for the new traits, including their daily heritability and genetic correlations with milk production traits and SCS, using a random regression test-day model (RRTDM). We derived 3 traits, namely ML_SCS_DSCC, SCS_4_DSCC_65_binary, and ML_SCS_DSCC_binary, by using milk loss estimates at corresponding SCS and DSCC levels, thresholds established in previous studies, and a threshold established from milk loss estimates, respectively. Data consisted of test-day records collected during January 2021 through March 2022 from 265 herds in Hokkaido, Japan. From these records, we extracted records between 7 to 305 d in milk (DIM) in the first lactation to fit the RRTDM. The model included the random effect of herd-test-day, the fixed effect of year-month, fixed lactation curves nested with calving age groups, and random regressions with Legendre polynomials of order 3 for additive genetic and permanent environmental effects. The analysis was performed using Gibbs sampling with Gibbsf90+ software. The averages (ranges) of daily heritability estimates over lactation were 0.086 (0.075 to 0.095) for SCS, 0.104 (0.073 to 0.127) for ML_SCS_DSCC, 0.137 (0.014 to 0.297) for SCS_4_DSCC_65_binary, and 0.138 (0.115 to 0.185) for ML_SCS_DSCC_binary; the heritability curve for SCS_4_DSCC_65_binary was erratic. Genetic correlations within the trait decreased as the DIM interval widened, especially for those integrating DSCC, indicating that these traits should be analyzed using RRTDM rather than repeatability models. The averages (ranges) of genetic correlations with milk yield over lactation were 0.01 (-0.22 to 0.28) for SCS, -0.05 (-0.40 to 0.13) for ML_SCS_DSCC, -0.08 (-0.17 to 0.09) for SCS_4_DSCC_65_binary, and -0.08 (-0.22 to 0.27) for ML_SCS_DSCC_binary. Compared with SCS, the newly defined traits exhibited slightly stronger negative genetic correlations with milk yield. Especially in late lactation stages, the genetic correlation between ML_SCS_DSCC and milk yield was significantly below zero, with a posterior median of -0.40. Furthermore, the new traits showed positive correlations with SCS, having estimates varying from 0.68 to 0.85 for ML_SCS_DSCC, 0.14 to 0.47 for SCS_4_DSCC_65_binary, and 0.61 to 0.66 for ML_SCS_DSCC_binary, depending on DIM. Considering that ML_SCS_DSCC and ML_SCS_DSCC_binary have relatively high heritability (compared with SCS) and favorable genetic correlations with milk production traits and SCS, their incorporation into breeding programs appears promising. Nevertheless, their genetic relationships with (sub)clinical mastitis require further investigation.

Prevalence of growth hormone receptor gene polymorphisms and their association with milk production and fertility-related traits of cross-bred dairy cows in Sri Lanka

This study investigated the association of selected growth hormone receptor (GHR) gene SNPs with selected fertility and milk production-related phenotypes of cross-bred dairy cows (n = 153) reared on three National Livestock Development Board farms in Sri Lanka. Selected cows were genetically screened for SNPs in the exon 08 (n = 153) and 5’ upstream (n = 118) regions of the GHR gene using the target sequencing method. The relationships between different genotypes and fertility traits (average calving interval, average number of services per conception, and age at first calving) and milk production-related traits (average total lactation yield, average lactation length, and average milk yield) were analyzed using the General Linear Model in SPSS. Among the identified Four GHR SNPs, rs1099014416 was significantly associated with average calving interval and age at first calving. Cows with GG genotype exhibited younger age at first calving (918.51 ± 113.42 days) and longer calving intervals (543.41 ± 43.29 days) compared to cows with GT (1275.18 ± 38.31, 515.09 ± 24.49 days) and TT (1212.89 ± 88.22, 364.52 ± 54.01 days) genotypes. Other SNPs did not show associations with the studied traits. SNP rs109014416 has the potential to be used as a genetic marker for fertility-related traits in the selection of cross-bred dairy cows in Sri Lanka which should be validated with a larger population.

A Million-Cow Validation of a Chromosome 14 Region Interacting with All Chromosomes for Fat Percentage in U.S. Holstein Cows.

A genome-wide association study (GWAS) of fat percentage (FPC) using 1,231,898 first lactation cows and 75,198 SNPs confirmed a previous result that a Chr14 region about 9.38 Mb in size (0.14-9.52 Mb) had significant inter-chromosome additive × additive (A×A) effects with all chromosomes and revealed many new such effects. This study divides this 9.38 Mb region into two sub-regions, Chr14a at 0.14-0.88 Mb (0.74 Mb in size) with 78% and Chr14b at 2.21-9.52 Mb (7.31 Mb in size) with 22% of the 2761 significant A×A effects. These two sub-regions were separated by a 1.3 Mb gap at 0.9-2.2 Mb without significant inter-chromosome A×A effects. The PPP1R16A-FOXH1-CYHR1-TONSL (PFCT) region of Chr14a (29 Kb in size) with four SNPs had the largest number of inter-chromosome A×A effects (1141 pairs) with all chromosomes, including the most significant inter-chromosome A×A effects. The SLC4A4-GC-NPFFR2 (SGN) region of Chr06, known to have highly significant additive effects for some production, fertility and health traits, specifically interacted with the PFCT region and a Chr14a region with CPSF1, ADCK5, SLC52A2, DGAT1, SMPD5 and PARP10 (CASDSP) known to have highly significant additive effects for milk production traits. The most significant effects were between an SNP in SGN and four SNPs in PFCT. The CASDSP region mostly interacted with the SGN region. In the Chr14b region, the 2.28-2.42 Mb region (138.46 Kb in size) lacking coding genes had the largest cluster of A×A effects, interacting with seventeen chromosomes. The results from this study provide high-confidence evidence towards the understanding of the genetic mechanism of FPC in Holstein cows.

Exploring the presence of genotype-by-environment interactions between dairy cow herds milking once-a-day or twice-a-day for the entire lactation

The objective was to explore if the regression of phenotypic performance for six milk production traits on the respective estimate of genetic merit for that trait differed by herd milking frequency; variance components for each trait in the two milking frequency environments were also estimated as well as the genetic correlation between the same trait in both environments. The data used included 12,581 lactations from 5,456 cows in 32 spring-calving once-a-day (OAD) milking herds. Each OAD herd was matched with three contemporary twice-a-day (TAD)-milking herds; 35,823 lactations from 15,188 cows in 96 TAD herds were used. Mean yield was 20% (fat yield) to 31% (milk yield) lower in OAD herds. Milk protein concentration was 11% higher in OAD herds, while milk fat concentration was 16% higher in OAD herds. The mean back-transformed somatic cell score (SCS) was 100,390 cells/mL in OAD herds and 72,493 cells/mL in TAD herds. The association between each milk production trait and its respective estimate of genetic merit differed by herd milking frequency; the estimated regression coefficients were larger in TAD for just milk yield and SCS. The genetic correlation between the same trait in OAD versus TAD was all ≥0.73 with the exception of SCS (genetic correlation of 0.48) which suggests some re-ranking of sires between environments. In conclusion, differences in the scale of the genetic variance were evident for both milking frequencies and possible re-ranking was evident for SCS.