Milk Production Traits Research Articles

A Meta-Analysis of the Effects of Dietary Betaine on Milk Production, Growth Performance, and Carcass Traits of Ruminants.

Betaine improves growth performance and health in monogastric animals under both thermoneutral and heat stress conditions, but results in ruminants have been more equivocal. This meta-analysis investigated the effects of betaine supplementation on productive performance, milk production and composition, and carcass traits of ruminants due to betaine supplementation. A comprehensive search for published studies investigating the effect of betaine was performed using Google Scholar, ScienceDirect, PubMed, and Scopus databases. Effect size analysis, random effects models, I2 statistics, and meta-regression analysis were utilized to assess differences in production parameters. Dietary betaine supplementation increased milk yield (+1.0 kg/d (weighted mean differences presented in this abstract), p < 0.001), dry matter intake (+0.15 kg/d, p < 0.001), and milk lactose (+0.05%, p = 0.010) in dairy cows housed under thermoneutral conditions. In the few studies conducted on small ruminants, there was an increase in milk yield in response to dietary betaine (0.45 kg/d, p = 0.040). Under heat stress conditions or grazing pasture during summer, dietary betaine increased milk yield (+1.0 kg/d, p < 0.001) and dry matter intake (+0.21 kg/d, p = 0.020). Dietary betaine increased final liveweight (+2.33 kg, p = 0.050) and back fat thickness (+0.74 cm, p < 0.001) in beef cattle. Dietary betaine increased final liveweight (0.14 kg, p = 0.010), daily gain (+0.019 kg/d, p < 0.001), and carcass weight (+0.80 kg, p < 0.001) but not backfat in small ruminants. These meta-analyses showed that dietary betaine increases liveweight in small ruminants and beef cattle and increases feed intake and milk yield in dairy cattle.

Computation of Heritability for Production and Reproduction Traits in Frieswal Cattle under Field Progeny Testing

Aims: To study the genetic parameter (heritability) for production and reproduction traits in Frieswal cattle under field progeny testing programme. Place and Duration of Study: G B Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, India, between March, 2023 and March, 2024. Methodology: The present study was conducted on 1163 Frieswal cattle comprised of five different sets maintained at six field units over a period from 2013-2021. The traits considered were age at sexual maturity (ASM), age at first calving (AFC), gestation period (GP), test day peak yield (TDPY), 305 days milk yield (305D-MY), fat percentage (FP), lactation length (LL), calving interval (CI), service period (SP), number of services per conception (NSPC), dry period (DP). The data were analyzed for the estimation of heritability by the software WOMBAT. Results: The heritability estimates of the traits namely; ASM, AFC, GP, TDPY, 305D-MY, FP, LL, CI, SP, NSPC and DP were 0.469±0.082, 0.467±0.082, 0.259±0.067, 0.248±0.059, 0.354±0.013, 0.413±0.069, 0.389±0.071, 0.394±0.071, 0.452±0.072, 0.072±0.046 and 0.08±0.06, respectively. Conclusion: Therefore, the heritability estimates were found to be low to high magnitude for different reproduction and production traits and further it has been concluded that, this study will aid breeders in selecting high-performing animals for future generations, taking into account the genetic factors that influence milk production and reproductive traits during early lactation.

Whole Genome Scan Uncovers Candidate Genes Related to Milk Production Traits in Barka Cattle.

In this study, our primary aim was to explore the genomic landscape of Barka cattle, a breed recognized for high milk production in a semi-arid environment, by focusing on genes with known roles in milk production traits. We employed genome-wide analysis and three selective sweep detection methods (ZFST, θπ ratio, and ZHp) to identify candidate genes associated with milk production and composition traits. Notably, ACAA1, P4HTM, and SLC4A4 were consistently identified by all methods. Functional annotation highlighted their roles in crucial biological processes such as fatty acid metabolism, mammary gland development, and milk protein synthesis. These findings contribute to understanding the genetic basis of milk production in Barka cattle, presenting opportunities for enhancing dairy cattle production in tropical climates. Further validation through genome-wide association studies and transcriptomic analyses is essential to fully exploit these candidate genes for selective breeding and genetic improvement in tropical dairy cattle.

Genetic Association of APOA5 and AKT3 Genes with Milk Production Traits in Chinese Holstein Cows

Genome selection (GS) technology is an important means to improve the genetic improvement of dairy cows, and the mining and application of functional genes and loci for important traits is one of the important bases for accelerating genetic improvement. Our previous study found that the apolipoprotein A5 (APOA5) and AKT serine/threonine kinase 3 (AKT3) genes were differentially expressed in the liver tissue of Chinese Holstein cows at different lactation stages and influenced milk component synthesis and metabolism, so we considered these two genes as the candidates affecting milk production traits. In this study, we found in total six single nucleotide polymorphisms (SNPs), three in APOA5 and three in AKT3. Subsequent association analysis showed that the six SNPs were significantly associated with milk yield, fat yield, protein yield, or fat percentage (p ≤ 0.05). Three SNPs in APOA5 formed a haplotype block, which was found to be significantly associated with milk yield, fat yield, and protein yield (p ≤ 0.05). In addition, four SNPs were proposed to be functional mutations affecting the milk production phenotype, of which three, 15:g.27446527C&gt;T and 15:g.27447741A&gt;G in APOA5 and 16:g.33367767T&gt;C in AKT3, might change the transcription factor binding sites (TFBSs), and one is a missense mutation, 15:g.27445825T&gt;C in APOA5, which could alter the secondary structure and stability of mRNA and protein. In summary, we demonstrated the genetic effects of APOA5 and AKT3 on milk production traits, and the valuable SNPs could be used as available genetic markers for dairy cattle’s GS.

Genetic profile of milk production traits and analysis of correlations with reproductive performance in the Azawak Zebu in Niger

The effects of genetic factors on the lactation traits of the Azawak cattle breed are estimated from 11,998 monthly milk records from 1275 complete lactations from 471 Azawak cows bred at the Toukounous experimental centre (Niger), using a multi-trait animal model based on the REML method. The results show that heritability was moderate for persistency (h2 = 0.23), peak lactation (h2 = 0.34), milk yield at 305 days (h2 = 0.30), daily milk yield (h2 = 0.33) and total milk yield (h2 = 0.35). In addition, very high repeatability estimates ranging from 0.50 to 0.58 were associated with the last four traits. Significant phenotypic correlations varying from 0.23 to 0.40 existed between the two reproductive traits (age at first calving and calving interval) and the lactation traits. Similarly, the significant genetic correlations between the traits of milk production and reproduction traits were unfavorable, varying according to the lactation traits considered from 0.32 to 0.87 for age at first calving and from 0.48 to 0.97 for calving interval, indicating that selection for milk yield only should result in a longer calving interval and a later age at first calving. Estimates of the heritability of lactation traits are moderate, as are those of many functional reproductive traits, so the genetic gain from selection on milk production traits alone would be rapid, but antagonistic with reproductive performance.

PC Gene Affects Milk Production Traits in Dairy Cattle.

In previous work, we found that PC was differentially expressed in cows at different lactation stages. Thus, we deemed that PC may be a candidate gene affecting milk production traits in dairy cattle. In this study, we found the polymorphisms of PC by resequencing and verified their genetic associations with milk production traits by using an animal model in a cattle population. In total, we detected six single-nucleotide polymorphisms (SNPs) in PC. The single marker association analysis showed that all SNPs were significantly associated with the five milk production traits (p < 0.05). Additionally, we predicted that allele G of 29:g.44965658 in the 5' regulatory region created binding sites for TF GATA1 and verified that this allele inhibited the transcriptional activity of PC by the dual-luciferase reporter assay. In conclusion, we proved that PC had a prominent genetic effect on milk production traits, and six SNPs with prominent genetic effects could be used as markers for genomic selection (GS) in dairy cattle, which is beneficial for accelerating the improvement in milk yield and quality in Chinese Holstein cows.

Regulatory impacts of PPARGC1A gene expression on milk production and cellular metabolism in buffalo mammary epithelial cells

The PPARGC1A gene plays a fundamental role in regulating cellular energy metabolism, including adaptive thermogenesis, mitochondrial biogenesis, adipogenesis, gluconeogenesis, and glucose/fatty acid metabolism. In a previous study, our group investigated seven SNPs in Mediterranean buffalo associated with milk production traits, and the current study builds on this research by exploring the regulatory influences of the PPARGC1A gene in buffalo mammary epithelial cells (BuMECs). Our findings revealed that knockdown of PPARGC1A gene expression significantly affected the growth of BuMECs, including proliferation, cell cycle, and apoptosis. Additionally, we observed downregulated triglyceride secretion after PPARGC1A knockdown. Furthermore, the critical genes related to milk production, including the STATS, BAD, P53, SREBF1, and XDH genes were upregulated after RNAi, while the FABP3 gene, was downregulated. Moreover, Silencing the PPARGC1A gene led to a significant downregulation of β-casein synthesis in BuMECs. Our study provides evidence of the importance of the PPARGC1A gene in regulating cell growth, lipid, and protein metabolism in the buffalo mammary gland. In light of our previous research, the current study underscores the potential of this gene for improving milk production efficiency and overall dairy productivity in buffalo populations.

Genome-wide copy number variant analysis reveals candidate genes associated with milk production traits in water buffalo (Bubalus bubalis)

Buffaloes are vital contributors to the global dairy industry. Understanding the genetic basis of milk production traits in buffalo populations is essential for breeding programs and improving productivity. In this study, we conducted whole-genome resequencing on 387 buffalo genomes from 29 diverse Asian breeds, including 132 river buffaloes, 129 swamp buffaloes, and 126 crossbred buffaloes. We identified 36,548 copy number variants (CNV) spanning 133.29 Mb of the buffalo genome, resulting in 2,100 CNV regions (CNVR), with 1,993 shared CNVR being found within the studied buffalo types. Analyzing CNVR highlighted distinct genetic differentiation between river and swamp buffalo subspecies, verified by evolutionary tree and principal component analyses. Admixture analysis grouped buffaloes into river and swamp categories, with crossbred buffaloes displaying mixed ancestry. To identify candidate genes associated with milk production traits, we employed 3 approaches. First, we used Vst-based population differentiation, revealing 11 genes within CNVR that exhibited significant divergence between different buffalo breeds, including genes linked to milk production traits. Second, expression quantitative loci analysis revealed differentially expressed CNVR-derived genes (DECG) associated with milk production traits. Notably, known milk production-related genes were among these DECG, validating their relevance. Last, a GWAS identified 3 CNVR significantly linked to peak milk yield. Our study provides comprehensive genomic insights into buffalo populations and identifies candidate genes associated with milk production traits. These findings facilitate genetic breeding programs aimed at increasing milk yield and improving quality in this economically important livestock species.

Genetic parameters for udder conformation traits derived from Cartesian coordinates generated by robotic milking systems in North American Holstein cattle

Udder conformation is directly related to milk yield, cow health, workability, and welfare. Automatic milking systems (AMS, also known as milking robots) have become popular worldwide, and the number of dairy farms adopting these systems has increased considerably over the past years. In each milking visit, AMS record the location of the 4 teats as Cartesian coordinates in an xyz plan, which can then be used to derive udder conformation traits. Because AMS generate a large amount of data for individual cows per milking visit, they can contribute to an accurate assessment of important traits such as udder conformation without the addition of human classifier errors (in subjective scoring systems). Therefore, the primary objectives of this study were to estimate genomic-based genetic parameters for udder conformation traits derived from AMS records in North American Holstein cattle and to assess the genetic correlation between the derived traits for evaluating the feasibility of multitrait genomic selection for breeding cows that are more suitable for milking in AMS. The Cartesian teat coordinates measured during each milking visit were collected by 36 milking robots in 4,480 Holstein cows from 2017 to 2021, resulting in 5,317,488 records. A total of 4,118 of these Holstein cows were also genotyped for 57,600 SNPs. Five udder conformation traits were derived: udder balance (UB, mm), udder depth (UD, mm), front teat distance (FTD, mm), rear teat distance (RTD, mm), and distance front-rear (DFR, mm). In addition, 2 traits directly related to cow productivity in the system were added to the study: daily milk yield (DY) and milk electroconductivity (EC; as an indicator of mastitis). Variance components and genetic parameters for UB, UD, FTD, RTD, DFR, DY, and EC were estimated based on repeatability animal models. The estimates of heritability (± SE) for UB, UD, FTD, RTD, DFR, DY, and EC were 0.41 ± 0.02, 0.79 ± 0.01, 0.53 ± 0.02, 0.40 ± 0.02, 0.65 ± 0.02, 0.20 ± 0.02, and 0.46 ± 0.02, respectively. The repeatability estimates (± SE) for UB, UD, FTD, RTD, and DFR were 0.82 ± 0.01, 0.93 ± 0.01, 0.87 ± 0.01, 0.83 ± 0.01, and 0.88 ± 0.01, respectively. The strongest genetic correlations were observed between FTD and RTD (0.54 ± 0.03), UD and DFR (-0.47 ± 0.03), DFR and FTD (0.32 ± 0.03), and UD and FTD (-0.31 ± 0.03). These results suggest that udder conformation traits derived from Cartesian coordinates from AMS are moderately to highly heritable. Furthermore, the moderate genetic correlations between these traits should be considered when developing selection subindexes. The most relevant genetic correlations between traits related to cow milk productivity and udder conformation traits were between UD and EC (-0.25 ± 0.03) and between DFR and DY (0.30 ± 0.04), in which both genetic correlations are favorable. These findings will contribute to the design of genomic selection schemes for improving udder conformation in North American Holstein cattle, especially in precision dairy farms.

VARIABILITY OF SIGNS OF MILK PRODUCTIVITY OF COWS DEPENDING ON THEIR LINEAL AFFILIATION

Data on the signs of milk productivity of cows of the Ukrainian Black-and-White dairy breed depending on their lineal affiliation are given. The research was conducted in SE DG "Oleksandrivske" Vinnytsia region (Forest-Steppe zone, n=714), the LLC JV "Imeni Volovikova" Rivne region (Polissya zone, n=1,840) and the SE "Experimental farm "Askaniyske" (Steppe zone, n=926 ) on firstborn and full-grown (III lactation) animals. It was found that cows of the Chif line 1427381 (6384 kg) were the most productive in the first lactation in the Forest Steppe zone, in the third - Eleveishn line 1491007 (7325), in the Polissya zone – Starbak line 352790 for both lactations (6126 and 6521 kg, respectively), and in the Steppe zone – Annas Adema 30587 lines (6570 kg and 7482 kg). The highest content of fat in the milk of the SE DG "Oleksandrivske" was found in the first-borns of the Valiant line 1650414 (3.65%) and in full-aged cows of the Starbak line 352790 (3.59%), in the LLC JV "Imeni Volovikova" – Eleveyshn 1491007 (3.67 %) and Valiant 1650414 (3.68%), in SE "Experimental farm "Askaniyske" – Chif 1427381 (4.19%) and Bell 1667366 (4.19%). It is worth noting that the lowest milk yield for the first lactation in the above-mentioned farms was observed, respectively, in cows of lines Haneve 1629391 (5465 kg), Valiant 1650414 (4545 kg) and Bell 1667366 (6055 kg), for the third lactation - in individuals of lines Valiant 1650414 (6633 kg), Eleveishn 1491007 (6058 kg) and Bella 1667366 (6464 kg). In the Forest Steppe zone, the first-borns of the Eleveyshn 1491007 and Starbak 352790 lines were the least fat-milk – 3.59%, and full-aged cows of the Chif 1427381 and Valiant 1650414 lines – 3.56%, in the Polissya zone – the Chif 1427381 and Starbak 352 lines – 3.62% 790 – 3, 62%, and in the Steppe zone – the Annas Adem 30587 line for both lactations – 3.95 and 3.89%, respectively. Variance analysis confirmed the conditionality of the phenotypic variability of the quantitative traits of milk production depending on the lineal belonging of cows established by the comparison of group averages. At the same time, the line had a more significant effect on hope than on fat. Depending on the farm and lactation, the strength of the influence on the milk fat content was in the range of 4.1–21.1%, and in the range of .4–12.4%. Therefore, the linear belonging of cows to some extent can serve as a criterion for predicting their milk productivity.

Genomic analysis uncovers novel candidate genes related to adaptation to tropical climates and milk production traits in native goats

BackgroundSince domestication, both evolutionary forces and human selection have played crucial roles in producing adaptive and economic traits, resulting in animal breeds that have been selected for specific climates and different breeding goals. Pakistani goat breeds have acquired genomic adaptations to their native climate conditions, such as tropical and hot climates. In this study, using next-generation sequencing data, we aimed to assess the signatures of positive selection in three native Pakistani goats, known as milk production breeds, that have been well adapted to their local climate.ResultsTo explore the genomic relationship between studied goat populations and their population structure, whole genome sequence data from native goat populations in Pakistan (n = 26) was merged with available worldwide goat genomic data (n = 184), resulting in a total dataset of 210 individuals. The results showed a high genetic correlation between Pakistani goats and samples from North-East Asia. Across all populations analyzed, a higher linkage disequilibrium (LD) level (– 0.59) was found in the Pakistani goat group at a genomic distance of 1 Kb. Our findings from admixture analysis (K = 5 and K = 6) showed no evidence of shared genomic ancestry between Pakistani goats and other goat populations from Asia. The results from genomic selection analysis revealed several candidate genes related to adaptation to tropical/hot climates (such as; KITLG, HSPB9, HSP70, HSPA12B, and HSPA12B) and milk production related-traits (such as IGFBP3, LPL, LEPR, TSHR, and ACACA) in Pakistani native goat breeds.ConclusionsThe results from this study shed light on the structural variation in the DNA of the three native Pakistani goat breeds. Several candidate genes were discovered for adaptation to tropical/hot climates, immune responses, and milk production traits. The identified genes could be exploited in goat breeding programs to select efficient breeds for tropical/hot climate regions.

5 Rumen microbiome and metabolome in dairy cattle performance

Abstract Cattle rumen microbiome converts fibrous feed to nutrients that directly influence cattle’s growth and performance. Recent research has revealed the composition and function of rumen microbiome can affect many economically important traits in cattle such as feed efficiency, milk/meat yield and quality, methane emission, metabolic health and so on. In this presentation, the research on the assessment of to what extent the rumen microbiome and its metabolites, as well as host metabolites contribute to milk production and quality traits will be focused and discussed. It has been evident that some dairy cows can produce large amounts of milk under the same nutritional and management conditions. Recent research has revealed that in addition to host genetics and diet, parity and days in milk of dairy cows can affect the rumen microbiota, and both core and pan rumen bacteriome can potentially contribute to variations of milk production traits. Additionally, the analysis of rumen metagenomics and metabolomics of dairy cows with varied milk production yield showed that some key bacterial taxa (for example, Prevotella species), and their functions (such as branched-chain amino acids biosynthesis, methanogenesis), some rumen microbial metabolites (mainly amino acids, carboxylic acids, and fatty acids) significantly differed between high and low production cows. Further integrated analysis with serum metabolomics of the cos revealed the varied contributions of rumen microbial composition, functions, metabolites, and the serum metabolites to the milk protein yield of a dairy cow, a potential new trait that can be used for high-quality milk production, respectively. The fundamental understanding of the role of rumen microbiome and its metabolome contributing to milk yield and protein yield traits can provide novel insights into future manipulation of rumen microbiome to enhance milk production and quality.

Clustering of countries based on dairy productivity characteristics of Holstein cattle for breeding material selection.

The aim of any breeding process is to create a herd based on certain parameters that reflect an ideal animal vision. Targeted herding involves selecting the source of breeding material to be imported from another country. Therefore, there is a problem in selecting a breeding material importer to rapidly form a uterine canopy with the required properties. The purpose of this study was to evaluate a set of predictive milk productivity traits in Holstein cattle across countries. This research was based on records of 819,358 recorded animals from 28 countries born after January 1, 2018, from open databases. We used the Euclidean metric to construct dendrograms characterizing the similarity of countries according to the complex milk productivity traits of the daughters of bulls. The Ward method was used to minimize intracluster variance when forming clusters and constructing the corresponding diagrams. Principal component analysis was used to reduce dimensionality and eliminate the effect of multicollinearity. The principal components were selected using the Kaiser-Harris criteria. A ranking of multidimensional complex milk productivity traits in different countries over the past 5 years was performed. A group of leading countries led by the USA was established according to the studied indicators, and the possible reasons for such a division into groups were described. The pressure of purposeful artificial selection prevails in comparison with the pressure of natural selection concerning milk productivity traits in a certain group of countries, which allows specialists to choose suppliers when buying breeding animals and materials. The findings are based solely on data from recorded animals, which may not represent the entire breed population within each country, especially in regions where record-keeping may be inconsistent. It is expected that further studies will include regional data from large enterprises not part of Interbull, with mandatory verification and validation. An important element of such work is seen as the ability to compare the milk productivity of populations from different countries using a different scale, as well as studying the differentiation of countries by other selection traits of dairy.

Comprehensive analysis of differences in the physiochemical composition of foremilk and hindmilk of grazing indigenous and crossbred dairy goats; implications for growth, milk production and industry.

This study was conducted on 90 grazing Hair, Alpine × Hair F1 (AHF1), and Saanen × Hair F1 (SHF1) crossbred goats in three farms located around the Taurus Mountains in Konya, Türkiye. The study investigated variation in milk production, physico-chemical traits of milk fractions (foremilk, hindmilk and total milk), and growth traits. Genotype, parity, offspring sex, birth type, and flock factors significantly influenced milk production and quality traits of milk fractions (P < 0.05 to P < 0.01). Does with male/single offspring produced less milk, but with higher nutrient density (P < 0.05). Hindmilk was 272%, 31% and 61% richer in fat, total solids and energy content than foremilk, respectively (P < 0.001). However, the protein, lactose and solids-non-fat content of hindmilk was on average 7% lower than that of foremilk (P < 0.001). Physico-chemical quality traits of foremilk, hindmilk and total milk had a strong negative correlation with daily milk yield (P < 0.05 to P < 0.001). Live weight and average daily gains (ADG) of kids were influenced by maternal parity, flock, offspring sex and birth type (P < 0.05). The overall Kleiber ratios (KR) from birth to 2 months, birth to 3 months, birth to 6 months and 3 to 6 months of age were 21.0 ± 0.22, 17.1 ± 0.11, 10.5 ± 0.06 and 8.5 ± 0.21g/kg of metabolic weight, respectively. It was concluded that these findings are critical for milk sampling protocols, offspring growth strategies, product development and precision livestock management.

Validation of Bos taurus SNPs for Milk Productivity of Sahiwal Breed (Bos indicus), Pakistan.

The aim of the present study was the validation of the already reported Bos taurus SNPs in the Sahiwal breed. A total of nine SNPs of the casein gene were studied. Out of nine, seven Bos taurus SNPs of casein protein genes were found to be significantly associated with milk productivity traits. The genomic DNA was extracted from the mammary alveolar endothelial cells of a flock of 80 purebred Sahiwal lactating dams available at Khizrabad Farm near Sargodha. New allele-specific primers were designed from the NCBI annotated sequence database of Bos taurus to obtain 100 nt-long PCR products. Each dam was tested separately for all the SNPs investigated. Animals with genotype GG for the SNPs rs43703010, rs10500451, and 110323127, respectively, exhibited high milk yield. Similarly, animals with genotype AA for the SNPs rs11079521, rs43703016, and rs43703017 showed high milk yield consistently. For the SNP rs43703015, animals with genotype CC showed high milk productivity. These above-mentioned SNPs have previously been reported to significantly up-regulate casein protein contents in Bos taurus. Our results indicated SNPs that significantly affect the milk protein contents may also significantly increase per capita milk yield. These finding suggest that the above-mentioned reported SNPs can also be used as genetic markers of milk productivity in Sahiwal cattle.

Polymorphisms of CYP7A1 and HADHB Genes and Their Effects on Milk Production Traits in Chinese Holstein Cows.

Our preliminary research proposed the cytochrome P450 family 7 subfamily A member 1 (CYP7A1) and hydroxyacyl-coenzyme A dehydrogenase trifunctional multienzyme complex beta subunit (HADHB) genes as candidates for association with milk-production traits in dairy cattle because of their differential expression across different lactation stages in the liver tissues of Chinese Holstein cows and their potential roles in lipid metabolism. Hence, we identified single-nucleotide polymorphisms (SNPs) of the CYP7A1 and HADHB genes and validated their genetic effects on milk-production traits in a Chinese Holstein population with the goal of providing valuable genetic markers for genomic selection (GS) in dairy cattle, This study identified five SNPs, 14:g.24676921A>G, 14:g.24676224G>A, 14:g.24675708G>T, 14:g.24665961C>T, and 14:g.24664026A>G, in the CYP7A1 gene and three SNPs, 11:g.73256269T>C, 11:g.73256227A>C, and 11:g.73242290C>T, in HADHB. The single-SNP association analysis revealed significant associations (p value ≤ 0.0461) between the eight SNPs of CYP7A1 and HADHB genes and 305-day milk, fat and protein yields. Additionally, using Haploview 4.2, we found that the five SNPs of CYP7A1 formed two haplotype blocks and that the two SNPs of HADHB formed one haplotype block; notably, all three haplotype blocks were also significantly associated with milk, fat and protein yields (p value ≤ 0.0315). Further prediction of transcription factor binding sites (TFBSs) based on Jaspar software (version 2023) showed that the 14:g.24676921A>G, 14:g.24675708G>T, 11:g.73256269T>C, and 11:g.73256227A>C SNPs could alter the 5' terminal TFBS of the CYP7A1 and HADHB genes. The 14:g.24665961C>T SNP caused changes in the structural stability of the mRNA for the CYP7A1 gene. These alterations have the potential to influence gene expression and, consequently, the phenotype associated with milk-production traits. In summary, we have confirmed the genetic effects of CYP7A1 and HADHB genes on milk-production traits in dairy cattle and identified potential functional mutations that we suggest could be used for GS of dairy cattle and in-depth mechanistic studies of animals.

Factors Affecting the Milk Production Traits and Lactation Curve of the Indigenous River Buffalo Populations in Bangladesh.

Household buffalo dairy farming is gaining popularity nowadays in Bangladesh because of the outstanding food value of buffalo milk as well as the lower production cost of buffalo compared to cattle. An initiative has recently been taken for the genetic improvement of indigenous dairy buffaloes. The present study was carried out to determine the influence of some environmental factors like age, parity, season of calving, calving interval, dry period on the lactation yield, and lactation curve of indigenous dairy buffaloes of Bangladesh. A total of 384 indigenous dairy buffaloes from the 3rd and 4th parity of seven herds under two different agroecological zones covering four seasons were selected and ear tagged for individual buffalo milk recording. A milk yield of 300 days (MY300d) was calculated following the International Committee for Animal Recording (ICAR) and the data were evaluated using the generalized linear model (GLM). In production traits, the mean of calculated lactation period (CLP), calculated lactation yield (CLY), and milk yield of 300 days (MY300d) of the overall population were 267.28 days, 749.36 kg, and 766.92 kg, respectively, whereas calving interval (CI) and dry period (DP) as reproductive traits were 453.06 days and 185.78 days, respectively. The season of calving, age of buffalo cows, population or herd, agroecological zone, calving interval, and dry period had significant effects on production traits (p < 0.05 to p < 0.001). The season of calving, level of milk production of 300 days, population, and agroecological zone significantly affected the reproduction traits (p < 0.01 to p < 0.001). Parity was found to be non-significant for both types of traits. The average peak yield of test day (TD) milk production was highest at TD4 (4.47 kg, 98th day of lactation). The average MY300d of milk production was the highest in the Lalpur buffalo population (1076.13 kg) and the lowest in the buffalo population of Bhola (592.44 kg). The correlations between milk production traits (CLP, CLY, and MY-300d) and reproduction traits (CI and DP) were highly significant (p < 0.01 to p < 0.001). Positive and high correlation was found within milk traits and reproduction traits, but correlation was negative between milk traits and reproduction traits. Therefore, these non-genetic factors should be considered in the future for any genetic improvement program for indigenous dairy buffaloes in Bangladesh.

Identification of candidate genes associated with milk production and mastitis based on transcriptome-wide association study.

Genetic research for the assessment of mastitis and milk production traits simultaneously has a long history. The main issue that arises in this context is the known existence of a positive correlation between the risk of mastitis and lactation performance due to selection. The transcriptome-wide association study (TWAS) approach endeavors to combine the expression quantitative trait loci and genome-wide association study summary statistics to decode complex traits or diseases. Accordingly, we used the farmgtex project results as a complete bovine database for mastitis and milk production. The results of colocalization and TWAS approaches were used for the detection of functional associated candidate genes with milk production and mastitis traits on multiple tissue-based transcriptome records. Also, we used the david database for gene ontology to identify significant terms and associated genes. For the identification of interaction networks, the genemania and string databases were used. Also, the available z-scores in TWAS results were used for the calculation of the correlation between tissues. Therefore, the present results confirm that LYNX1, DGAT1, C14H8orf33, and LY6E were identified as significant genes associated with milk production in eight, six, five, and five tissues, respectively. Also, FBXL6 was detected as a significant gene associated with mastitis trait. CLN3 and ZNF34 genes emerged via both the colocalization and TWAS approaches as significant genes for milk production trait. It is expected that TWAS and colocalization can improve our perception of the potential health status control mechanism in high-yielding dairy cows.

Mendelian randomization analysis of 34,497 German Holstein cows to infer causal associations between milk production and health traits

BackgroundClaw diseases and mastitis represent the most important health issues in dairy cattle with a frequently mentioned connection to milk production. Although many studies have aimed at investigating this connection in more detail by estimating genetic correlations, they do not provide information about causality. An alternative is to carry out Mendelian randomization (MR) studies using genetic variants to investigate the effect of an exposure on an outcome trait mediated by genetic variants. No study has yet investigated the causal association of milk yield (MY) with health traits in dairy cattle. Hence, we performed a MR analysis of MY and seven health traits using imputed whole-genome sequence data from 34,497 German Holstein cows. We applied a method that uses summary statistics and removes horizontal pleiotropic variants (having an effect on both traits), which improves the power and unbiasedness of MR studies. In addition, genetic correlations between MY and each health trait were estimated to compare them with the estimates of causal effects that we expected.ResultsAll genetic correlations between MY and each health trait were negative, ranging from − 0.303 (mastitis) to − 0.019 (digital dermatitis), which indicates a reduced health status as MY increases. The only non-significant correlation was between MY and digital dermatitis. In addition, each causal association was negative, ranging from − 0.131 (mastitis) to − 0.034 (laminitis), but the number of significant associations was reduced to five nominal and two experiment-wide significant results. The latter were between MY and mastitis and between MY and digital phlegmon. Horizontal pleiotropic variants were identified for mastitis, digital dermatitis and digital phlegmon. They were located within or nearby variants that were previously reported to have a horizontal pleiotropic effect, e.g., on milk production and somatic cell count.ConclusionsOur results confirm the known negative genetic connection between health traits and MY in dairy cattle. In addition, they provide new information about causality, which for example points to the negative energy balance mediating the connection between these traits. This knowledge helps to better understand whether the negative genetic correlation is based on pleiotropy, linkage between causal variants for both trait complexes, or indeed on a causal association.

Association of &lt;i&gt;FGF2&lt;/i&gt; gene polymorphism with economically significant traits of Holstein cows of the Republic of Tatarstan

Improving the reproductive functions of dairy cows may be possible through the use of marker-associated breeding. The FGF2 gene is a candidate gene for bovine fertility, in early pregnancy and affects fetal embryonic development and embryonic mortality. The study of the interaction of the gene of the basic fibroblast growth factor 2 (FGF2 – SNP11646 [A → G]) and economic indicators was carried out on 270 full-aged cows of Holstein population of indigenous selection of Breeding Farm Integrated Agricultural Production Center of the Republic of Tatarstan. In the observed population, the G allele (0.591) and the AG genotype (42.6%) are the most common, and the genetic balance, according to the Hardy-Weinberg law, is preserved. Pearson's consensus criterion is 2χ=3.84, respectively, the expected distribution of FGF2 gene alleles in the study group coincides with the observed one. The maximum live weight at the first fruitful insemination was in full–aged cows carrying the homozygous allele A at the FGF2 gene locus – 435.5 kg, which is higher than in livestock with the GG genotype – by 17.7 kg (4.2 %; p &lt; 0.01). The Doha fertility index for the studied population is average. It was revealed during the study that the level of fertility, with a high degree of reliability, is higher in individuals with the AG genotype – 6.2%, for the same group the earliest age of the first fruitful insemination was noted. A high level of maleness leads to milk losses in cows heterozygous for the FGF2 gene locus, exceeding milk losses observed for the AA genotype by 32.7 % (p &lt; 0.001). There is an inverse correlation between high milk productivity and reproduction traits of cattle, which affects the economic efficiency of dairy production.