Mutation of SOCS2 induces structural and functional changes in mammary development.

Lactation is an essential process for mammals. In sheep, the R96C mutation in suppressor of cytokine signaling 2 (SOCS2) protein is associated with greater milk production and increased mastitis sensitivity. To shed light on the involvement of R96C mutation in mammary gland development and lactation, we developed a mouse model carrying this mutation (SOCS2KI/KI). Mammary glands from virgin adult SOCS2KI/KI mice presented a branching defect and less epithelial tissue, which were not compensated for in later stages of mammary development. Mammary epithelial cell (MEC) subpopulations were modified, with mutated mice having three times as many basal cells, accompanied by a decrease in luminal cells. The SOCS2KI/KI mammary gland remained functional; however, MECs contained more lipid droplets versus fat globules, and milk lipid composition was modified. Moreover, the gene expression dynamic from virgin to pregnancy state resulted in the identification of about 3000 differentially expressed genes specific to SOCS2KI/KI or control mice. Our results show that SOCS2 is important for mammary gland development and milk production. In the long term, this finding raises the possibility of ensuring adequate milk production without compromising animal health and welfare.

Cellular and transcriptional diversity over the course of human lactation.

Human breast milk (hBM) is a dynamic fluid that contains millions of cells, but their identities and phenotypic properties are poorly understood. We generated and analyzed single-cell RNA-sequencing (scRNA-seq) data to characterize the transcriptomes of cells from hBM across lactational time from 3 to 632 d postpartum in 15 donors. We found that the majority of cells in hBM are lactocytes, a specialized epithelial subset, and that cell-type frequencies shift over the course of lactation, yielding greater epithelial diversity at later points. Analysis of lactocytes reveals a continuum of cell states characterized by transcriptional changes in hormone-, growth factor-, and milk production-related pathways. Generalized additive models suggest that one subcluster, LC1 epithelial cells, increases as a function of time postpartum, daycare attendance, and the use of hormonal birth control. We identify several subclusters of macrophages in hBM that are enriched for tolerogenic functions, possibly playing a role in protecting the mammary gland during lactation. Our description of the cellular components of breast milk, their association with maternal­infant dyad metadata, and our quantification of alterations at the gene and pathway levels provide a detailed longitudinal picture of hBM cells across lactational time. This work paves the way for future investigations of how a potential division of cellular labor and differential hormone regulation might be leveraged therapeutically to support healthy lactation and potentially aid in milk production.

Chi-miR-3880 mediates the regulatory role of interferon gamma in goat mammary gland.

A healthy mammary gland is a necessity for milk production of dairy goats. The role of chi-miR-3880 in goat lactation is illustrated in our previous study. Among the differentially expressed genes regulated by chi-miR-3880, one seventh were interferon stimulated genes, including MX1, MX2, IFIT3, IFI44L, and DDX58. As the inflammatory cytokine interferon gamma (IFNγ) has been identified as a potential marker of caseous lymphadenitis in lactating sheep, the interaction between IFNγ and immune-related microRNAs was explored in this study. Chi-miR-3880 was found to be one of the microRNAs downregulated by IFNγ in goat mammary epithelial cells (GMECs). The study illustrated that IFNγ/chi-miR-3880/DDX58 axis modulates GMEC proliferation and lipid formation through PI3K/AKT/mTOR pathway, and regulates apoptosis through Caspase-3 and Bcl-2/Bax pathways. The role of the axis in mammary involution was reflected by the expression of p53 and NF-κB. In conclusion, IFNγ/chi-miR-3880/DDX58 axis plays an important part in lactation.

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.

BACKGROUND: Over 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. RESULTS: In 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. CONCLUSION: Our 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.

Genomic regions, candidate genes, and pleiotropic variants associated with physiological and anatomical indicators of heat stress response in lactating sows.

BACKGROUND: Heat stress (HS) poses significant threats to the sustainability of livestock production. Genetically improving heat tolerance could enhance animal welfare and minimize production losses during HS events. Measuring phenotypic indicators of HS response and understanding their genetic background are crucial steps to optimize breeding schemes for improved climatic resilience. The identification of genomic regions and candidate genes influencing the traits of interest, including variants with pleiotropic effects, enables the refinement of genotyping panels used to perform genomic prediction of breeding values and contributes to unraveling the biological mechanisms influencing heat stress response. Therefore, the main objectives of this study were to identify genomic regions, candidate genes, and potential pleiotropic variants significantly associated with indicators of HS response in lactating sows using imputed whole-genome sequence (WGS) data. Phenotypic records for 18 traits and genomic information from 1,645 lactating sows were available for the study. The genotypes from the PorcineSNP50K panel containing 50,703 single nucleotide polymorphisms (SNPs) were imputed to WGS and after quality control, 1,622 animals and 7,065,922 SNPs were included in the analyses. RESULTS: A total of 1,388 unique SNPs located on sixteen chromosomes were found to be associated with 11 traits. Twenty gene ontology terms and 11 biological pathways were shown to be associated with variability in ear skin temperature, shoulder skin temperature, rump skin temperature, tail skin temperature, respiration rate, panting score, vaginal temperature automatically measured every 10 min, vaginal temperature measured at 0800 h, hair density score, body condition score, and ear area. Seven, five, six, two, seven, 15, and 14 genes with potential pleiotropic effects were identified for indicators of skin temperature, vaginal temperature, animal temperature, respiration rate, thermoregulatory traits, anatomical traits, and all traits, respectively. CONCLUSIONS: Physiological and anatomical indicators of HS response in lactating sows are heritable but highly polygenic. The candidate genes found are associated with important gene ontology terms and biological pathways related to heat shock protein activities, immune response, and cellular oxidative stress. Many of the candidate genes with pleiotropic effects are involved in catalytic activities to reduce cell damage from oxidative stress and cellular mechanisms related to immune response.

Identification and characterization of whole blood gene expression and splicing quantitative trait loci during early to mid-lactation of dairy cattle.

BACKGROUND: Characterization of regulatory variants (e.g., gene expression quantitative trait loci, eQTL; gene splicing QTL, sQTL) is crucial for biologically interpreting molecular mechanisms underlying loci associated with complex traits. However, regulatory variants in dairy cattle, particularly in specific biological contexts (e.g., distinct lactation stages), remain largely unknown. In this study, we explored regulatory variants in whole blood samples collected during early to mid-lactation (22-150 days after calving) of 101 Holstein cows and analyzed them to decipher the regulatory mechanisms underlying complex traits in dairy cattle. RESULTS: We identified 14,303 genes and 227,705 intron clusters expressed in the white blood cells of 101 cattle. The average heritability of gene expression and intron excision ratio explained by cis-SNPs is 0.28 ± 0.13 and 0.25 ± 0.13, respectively. We identified 23,485 SNP-gene expression pairs and 18,166 SNP-intron cluster pairs in dairy cattle during early to mid-lactation. Compared with the 2,380,457 cis-eQTLs reported to be present in blood in the Cattle Genotype-Tissue Expression atlas (CattleGTEx), only 6,114 cis-eQTLs (P < 0.05) were detected in the present study. By conducting colocalization analysis between cis-e/sQTL and the results of genome-wide association studies (GWAS) from four traits, we identified a cis-e/sQTL (rs109421300) of the DGAT1 gene that might be a key marker in early to mid-lactation for milk yield, fat yield, protein yield, and somatic cell score (PP4 > 0.6). Finally, transcriptome-wide association studies (TWAS) revealed certain genes (e.g., FAM83H and TBC1D17) whose expression in white blood cells was significantly (P < 0.05) associated with complex traits. CONCLUSIONS: This study investigated the genetic regulation of gene expression and alternative splicing in dairy cows during early to mid-lactation and provided new insights into the regulatory mechanisms underlying complex traits of economic importance.

Mining key circRNA-associated-ceRNA networks for milk fat metabolism in cows with varying milk fat percentages.

BACKGROUND: Cow milk fat is an essential indicator for evaluating and measuring milk quality and cow performance. Growing research has identified the molecular functions of circular RNAs (circRNAs) necessary for mammary gland development and lactation in mammals. METHOD: The present study analyzed circRNA expression profiling data in mammary epithelial cells (MECs) from cows with highly variable milk fat percentage (MFP) using differential expression analysis and weighted gene co-expression network analysis (WGCNA). RESULTS: A total of 309 differentially expressed circRNAs (DE-circRNAs) were identified in the high and low MFP groups. WGCNA analysis revealed that the pink module was significantly associated with MFP (r = - 0.85, P = 0.007). Parental genes of circRNAs in this module were enriched mainly in lipid metabolism-related signaling pathways, such as focal adhesion, ECM-receptor interaction, adherens junction and AMPK. Finally, six DE-circRNAs were screened from the pink module: circ_0010571, circ_0007797, circ_0002746, circ_0003052, circ_0004319, and circ_0012840. Among them, circ_0002746, circ_0003052, circ_0004319, and circ_0012840 had circular structures and were highly expressed in mammary tissues. Subcellular localization revealed that these four DE-circRNAs may play a regulatory role in the mammary glands of dairy cows, mainly as competitive endogenous RNAs (ceRNAs). Seven hub target genes (GNB1, GNG2, PLCB1, PLCG1, ATP6V0C, NDUFS4, and PIGH) were obtained by constructing the regulatory network of their ceRNAs and then analyzed by CytoHubba and MCODE plugins in Cytoscape. Functional enrichment analysis revealed that these genes are crucial and most probable ceRNA regulators in milk fat metabolism. CONCLUSIONS: Our study identified several vital circRNAs and ceRNAs affecting milk fat synthesis, providing new research ideas and a theoretical basis for cow lactation, milk quality, and breed improvement.

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

BACKGROUND: Claw 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. RESULTS: All 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. CONCLUSIONS: Our 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.

Genetic parameters for novel climatic resilience indicators derived from automatically-recorded vaginal temperature in lactating sows under heat stress conditions.

BACKGROUND: Longitudinal records of automatically-recorded vaginal temperature (TV) could be a key source of data for deriving novel indicators of climatic resilience (CR) for breeding more resilient pigs, especially during lactation when sows are at an increased risk of suffering from heat stress (HS). Therefore, we derived 15 CR indicators based on the variability in TV in lactating sows and estimated their genetic parameters. We also investigated their genetic relationship with sows' key reproductive traits. RESULTS: The heritability estimates of the CR traits ranged from 0.000 ± 0.000 for slope for decreased rate of TV (SlopeDe) to 0.291 ± 0.047 for sum of TV values below the HS threshold (HSUB). Moderate to high genetic correlations (from 0.508 ± 0.056 to 0.998 ± 0.137) and Spearman rank correlations (from 0.431 to 1.000) between genomic estimated breeding values (GEBV) were observed for five CR indicators, i.e. HS duration (HSD), the normalized median multiplied by normalized variance (Nor_medvar), the highest TV value of each measurement day for each individual (MaxTv), and the sum of the TV values above (HSUA) and below (HSUB) the HS threshold. These five CR indicators were lowly to moderately genetically correlated with shoulder skin surface temperature (from 0.139 ± 0.008 to 0.478 ± 0.048) and respiration rate (from 0.079 ± 0.011 to 0.502 ± 0.098). The genetic correlations between these five selected CR indicators and sow reproductive performance traits ranged from - 0.733 to - 0.175 for total number of piglets born alive, from - 0.733 to - 0.175 for total number of piglets born, and from - 0.434 to - 0.169 for number of pigs weaned. The individuals with the highest GEBV (most climate-sensitive) had higher mean skin surface temperature, respiration rate (RR), panting score (PS), and hair density, but had lower mean body condition scores compared to those with the lowest GEBV (most climate-resilient). CONCLUSIONS: Most of the CR indicators evaluated are heritable with substantial additive genetic variance. Five of them, i.e. HSD, MaxTv, HSUA, HSUB, and Nor_medvar share similar underlying genetic mechanisms. In addition, individuals with higher CR indicators are more likely to exhibit better HS-related physiological responses, higher body condition scores, and improved reproductive performance under hot conditions. These findings highlight the potential benefits of genetically selecting more heat-tolerant individuals based on CR indicators.

Investigating the impact of paternal age, paternal heat stress, and estimation of non-genetic paternal variance on dairy cow phenotype.

BACKGROUND: Linear models that are commonly used to predict breeding values in livestock species consider paternal influence solely as a genetic effect. However, emerging evidence in several species suggests the potential effect of non-genetic semen-mediated paternal effects on offspring phenotype. This study contributes to such research by analyzing the extent of non-genetic paternal effects on the performance of Holstein, Montbéliarde, and Normande dairy cows. Insemination data, including semen Batch Identifier (BI, a combination of bull identification and collection date), was associated with various traits measured in cows born from the insemination. These traits encompassed stature, milk production (milk, fat, and protein yields), udder health (somatic cell score and clinical mastitis), and female fertility (conception rates of heifers and cows). We estimated (1) the effects of age at collection and heat stress during spermatogenesis, and (2) the variance components associated with BI or Weekly aggregated BI (WBI). RESULTS: Overall, the non-genetic paternal effect estimates were small and of limited biological importance. However, while heat stress during spermatogenesis did not show significant associations with any of the traits studied in daughters, we observed significant effects of bull age at semen collection on the udder health of daughters. Indeed, cows born from bulls collected after 1500 days of age had higher somatic cell scores compared to those born from bulls collected at a younger age (less than 400 days old) in both Holstein and Normande breeds (+ 3% and + 5% of the phenotypic mean, respectively). In addition, across all breeds and traits analyzed, the estimates of non-genetic paternal variance were consistently low, representing on average 0.13% and 0.09% of the phenotypic variance for BI and WBI, respectively (ranging from 0 to 0.7%). These estimates did not significantly differ from zero, except for milk production traits (milk, fat, and protein yields) in the Holstein breed and protein yield in the Montbéliarde breed when WBI was considered. CONCLUSIONS: Our findings indicate that non-genetic paternal information transmitted through semen does not substantially influence the offspring phenotype in dairy cattle breeds for routinely measured traits. This lack of substantial impact may be attributed to limited transmission or minimal exposure of elite bulls to adverse conditions.

A common regulatory haplotype doubles lactoferrin concentration in milk.

BACKGROUND: Bovine lactoferrin (Lf) is an iron absorbing whey protein with antibacterial, antiviral, and antifungal activity. Lactoferrin is economically valuable and has an extremely variable concentration in milk, partly driven by environmental influences such as milking frequency, involution, or mastitis. A significant genetic influence has also been previously observed to regulate lactoferrin content in milk. Here, we conducted genetic mapping of lactoferrin protein concentration in conjunction with RNA-seq, ChIP-seq, and ATAC-seq data to pinpoint candidate causative variants that regulate lactoferrin concentrations in milk. RESULTS: We identified a highly-significant lactoferrin protein quantitative trait locus (pQTL), as well as a cis lactotransferrin (LTF) expression QTL (cis-eQTL) mapping to the LTF locus. Using ChIP-seq and ATAC-seq datasets representing lactating mammary tissue samples, we also report a number of regions where the openness of chromatin is under genetic influence. Several of these also show highly significant QTL with genetic signatures similar to those highlighted through pQTL and eQTL analysis. By performing correlation analysis between these QTL, we revealed an ATAC-seq peak in the putative promotor region of LTF, that highlights a set of 115 high-frequency variants that are potentially responsible for these effects. One of the 115 variants (rs110000337), which maps within the ATAC-seq peak, was predicted to alter binding sites of transcription factors known to be involved in lactation-related pathways. CONCLUSIONS: Here, we report a regulatory haplotype of 115 variants with conspicuously large impacts on milk lactoferrin concentration. These findings could enable the selection of animals for high-producing specialist herds.

Effect of temperature-humidity index on the evolution of trade-offs between fertility and production in dairy cattle.

BACKGROUND: In the current context of climate change, livestock production faces many challenges to improve the sustainability of systems. Dairy farming, in particular, must find ways to select animals that will be able to achieve sufficient overall production while maintaining their reproductive ability in environments with increasing temperatures. With future forecasted climate conditions in mind, this study used data from Holstein and Montbeliarde dairy cattle to: (1) estimate the genetic-by-temperature-humidity index (THI) interactions for female fertility, and (2) evaluate the production-fertility trade-off with increasing values of THI. RESULTS: Two-trait random regression models were fitted for conception rate (fertility) and test-day protein yield (production). For fertility, genetic correlations between different THI values were generally above 0.75, suggesting weak genotype-by-THI interactions for conception rate in both breeds. However, the genetic correlations between the conception rate breeding values at the current average THI (THI = 50, corresponding to a 24-h average temperature of 8 °C at 50% relative humidity) and their slopes (i.e., potential reranking) for heat stress scenarios (THI > 70), were different for each breed. For Montbeliarde, this correlation tended to be positive (i.e., overall the best reproducers are less affected by heat stress), whereas for Holstein it was approximately zero. Finally, our results indicated a weak antagonism between production and fertility, although for Montbeliarde this antagonism intensified with increasing THI. CONCLUSIONS: Within the range of weather conditions studied, increasing temperatures are not expected to exacerbate the fertility-production trade-off. However, our results indicated that the animals with the best breeding values for production today will be the most affected by temperature increases, both in terms of fertility and production. Nonetheless, these animals should remain among the most productive ones during heat waves. For Montbeliarde, the current selection program for fertility seems to be adequate for ensuring the adaptation of fertility traits to temperature increases, without adverse effects on production. Such a conclusion cannot be drawn for Holstein. In the future, the incorporation of a heat tolerance index into dairy cattle breeding programs would be valuable to promote the selection of animals adapted to future climate conditions.

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.

Single and longitudinal genome-wide association studies for dairy traits available in goats with three recorded lactations.

Milk yield and composition phenotypes are systematically recorded across several lactations in goats, but the majority of genome-wide association studies (GWAS) performed so far have rather ignored the longitudinal nature of such data. Here, we have used two different GWAS approaches to analyse data from three lactations recorded in Murciano-Granadina goats. In Analysis 1, independent GWAS have been carried out for each trait and lactation, while a single longitudinal GWAS, jointly considering all data, has been performed in Analysis 2. In both analyses, genome-wide significant QTL for lactose percentage on chromosome 2 (129.77-131.01 Mb) and for milk protein percentage on the chromosome 6 (74.8-94.6 Mb) casein gene cluster region were detected. In Analysis 1, several QTL were not replicated in all three lactations, possibly due to the existence of lactation-specific genetic determinants. In Analysis 2, we identified several genome-wide significant QTL related to milk yield and protein content that were not uncovered in Analysis 1. The increased number of QTL identified in Analysis 2 suggests that the longitudinal GWAS is particularly well suited for the genetic analysis of dairy traits. Moreover, our data confirm that variability within or close to the casein complex is the main genetic determinant of milk protein percentage in Murciano-Granadina goats.

Weighted single step GWAS reveals genomic regions associated with economic traits in Murrah buffaloes.

The objective of the present study was to identify genomic regions influencing economic traits in Murrah buffaloes using weighted single step Genome Wide Association Analysis (WssGWAS). Data on 2000 animals, out of which 120 were genotyped using a double digest Restriction site Associated DNA (ddRAD) sequencing approach. The phenotypic data were collected from NDRI, India, on growth traits, viz., body weight at 6M (month), 12M, 18M and 24M, production traits like 305D (day) milk yield, lactation length (LL) and dry period (DP) and reproduction traits like age at first calving (AFC), calving interval (CI) and first service period (FSP). The biallelic genotypic data consisted of 49353 markers post-quality check. The heritability estimates were moderate to high, low to moderate, low for growth, production, reproduction traits, respectively. Important genomic regions explaining more than 0.5% of the total additive genetic variance explained by 30 adjacent SNPs were selected for further analysis of candidate genes. In this study, 105 genomic regions were associated with growth, 35 genomic regions with production and 42 window regions with reproduction traits. Different candidate genes were identified in these genomic regions, of which important are OSBPL8, NAP1L1 for growth, CNTNAP2 for production and ILDR2, TADA1 and POGK for reproduction traits.

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.

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.

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 ß-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.

Genetic covariance components for measures of nitrogen utilization in grazing dairy cows.

Improved nitrogen utilization of dairy production systems should improve not only the economic output of the systems but also the environmental metrics. One strategy to improve efficiency is through breeding programs. Improving a trait through breeding is conditional on the presence of exploitable genetic variability. Using a database of 1,291 deeply phenotyped grazing dairy cows, the genetic variability for 2 definitions of nitrogen utilization was studied: nitrogen use efficiency (i.e., nitrogen output in milk and meat divided by nitrogen available) and nitrogen balance (i.e., nitrogen available less nitrogen output in milk and meat). Variance components for both variables were estimated using animal repeatability linear mixed models. Genetic variability was detected for both nitrogen utilization metrics, even though their heritability estimates were low (<0.10). Validation of genetic evaluations revealed that animals divergent for nitrogen use efficiency or nitrogen balance indeed differed phenotypically, further demonstrating that breeding for improved nitrogen efficiency should result in a shift in the population mean toward better efficiency. Nitrogen use efficiency and nitrogen balance were not genetically correlated with each other (<|0.28|), and neither metric was correlated with milk urea nitrogen (<|0.12|). Nitrogen balance was unfavorably correlated with milk yield, showing the importance of including the nitrogen utilization metrics in a breeding index to improve nitrogen utilization without negatively impacting milk yield. In conclusion, improvement of nitrogen utilization through breeding is possible, even if more nitrogen utilization phenotypic data need to be collected to improve the selection accuracy considering the low heritability estimates.

Genetic analysis of lactation consistency in US Holsteins using temporal variation in daily milk weights.

The ability of a dairy cow to perform reliably over time is an interesting trait to include in dairy cattle breeding programs aimed at improving dairy cow resilience. Consistency, defined as the quality of performing as expected each day of the lactation, could be highly associated with resilience, defined as animal's ability to maintain health and performance in the presence of environmental challenges, including pathogens, heat waves, and nutritional changes. A total of 51,415,022 daily milk weights collected from 2018 to 2023 were provided for 255,191 multiparous Holstein cows milked 3 times daily in conventional parlor systems on farms in 32 states. The temporal variance (TEMPVAR) of milk yield from 5 to 305 d postpartum was computed as the log-transformed variance of daily deviations between observed and expected individual milk weights. Lower values of TEMPVAR imply smaller day-to-day deviations from expectations, indicating consistent performance, whereas larger values indicate inconsistent performance. Expected daily milk weights were computed using 3 nonparametric and parametric regression models: (1) loceally estimated scatterplot smoothing regression with a 0.75 span; (2) polynomial quantile regression using the median (0.5 quantile), and (3) polynomial quantile regression using a 0.7 quantile. The univariate statistical model included age at first calving and herd-year-season as fixed effects and cow as a random effect. Heritability estimates (standard errors) of TEMPVAR phenotypes calculated over the entire lactation ranged between 0.227 (0.011) and 0.237 (0.011), demonstrating that cows are genetically predisposed to display consistent or inconsistent performance. Estimated genetic correlations calculated using a multiple-trait model between TEMPVAR traits and between lactations were high (>0.95), indicating TEMPVAR is repeatable across lactations and robust to the model used to compute expected daily milk yield. Higher TEMPVAR phenotypes reflect more variation in performance, hence greater inconsistency, which is undesirable. Therefore, correlations between predicted transmitting abilities (PTA) for TEMPVAR and milk yield of 0.57 indicate that high-producing cows exhibit more day-to-day variation in performance. Correlations with productive life and livability were -0.38 and -0.48, respectively. Correlations between PTA for TEMPVAR and those of postpartum health traits were also negative, ranging from -0.41 to -0.08. Given that health traits are derived from disease resistance measurements, and higher health trait PTA are preferred, our results indicate that more consistent cows tend to have fewer health problems and greater longevity. Overall, our findings suggest that temporal variation in daily milk weights can be used to identify consistent animals that maintain expected performance throughout the lactation, which will enable selection for greater resilience to management and environmental perturbations.