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.

Identification of critical lncRNAs for milk fat metabolism in dairy cows using WGCNA and the construction of a ceRNAs network.

As key regulators, long non-coding RNAs (lncRNAs) play a crucial role in the ruminant mammary gland. However, the function of lncRNAs in milk fat synthesis from dairy cows is largely unknown. In this study, we used the weighted gene co-expression network analysis (WGCNA) to comprehensive analyze the expression profile data of lncRNAs from the group's previous Illumina PE150 sequencing results based on bovine mammary epithelial cells from high- and low-milk-fat-percentage (MFP) cows, and identify core_lncRNAs significantly associated with MFP by module membership (MM) and gene significance (GS). Functional enrichment analysis (Gene Ontology, Kyoto Encyclopedia of Genes and Genomes) of core_lncRNA target genes (co-localization and co-expression) was performed to screen potential lncRNAs regulating milk fat metabolism and further construct an interactive regulatory network of lipid metabolism-related competing endogenous RNAs (ceRNAs). A total of 4876 lncRNAs were used to construct the WGCNA. The MEdarkturquoise module among the 19 modules obtained was significantly associated with MFP (r = 0.78, p-value <0.05) and contained 64 core_lncRNAs (MM > 0.8, GS > 0.4). Twenty-four lipid metabolism-related lncRNAs were identified by core_lncRNA target gene enrichment analysis. TCONS_00054233, TCONS_00152292, TCONS_00048619, TCONS_00033839, TCONS_00153791 and TCONS_00074642 were key candidate lncRNAs for regulating milk fat synthesis. The 22 ceRNAs most likely to be involved in milk fat metabolism were constructed by interaction network analysis, and TCONS_00133813 and bta-miR-2454-5p were located at the network's core. TCONS_00133813_bta-miR-2454-5p_TNFAIP3, TCONS_00133813_bta-miR-2454-5p_ARRB1 and TCONS_00133813_bta-miR-2454-5p_PIK3R1 are key candidate ceRNAs associated with milk fat metabolism. This study provides a framework for the co-expression module of MFP-related lncRNAs in ruminants, identifies several major lncRNAs and ceRNAs that influence milk fat synthesis, and provides a new understanding of the complex biology of milk fat synthesis in dairy cows.

Integrative analysis of miRNAs and mRNAs revealed regulation of lipid metabolism in dairy cattle.

Lipid metabolism in bovine mammary epithelial cells has been the primary focus of the research of milk fat percentage of dairy cattle. Functional microRNAs can affect lipid metabolism by regulating the expression of candidate genes. The purpose of the study was to screen and identify differentially expressed miRNAs, candidate genes, and co-regulatory pathways related to the metabolism of milk fat. To achieve this aim, we used miRNA and transcriptome data from the mammary epithelial cells of dairy cattle with high (H, 4.85%) and low milk fat percentages (L, 3.41%) during mid-lactation. One hundred ninety differentially expressed genes and 33 differentially expressed miRNAs were significantly enriched in related regulatory networks, of which 27 candidate genes regulated by 18 differentially expressed miRNAs significantly enriched in pathways related to lipid metabolism (p < 0.05). Target relationships between PDE4D and bta-miR-148a, PEG10 and bta-miR-877, SOD3 and bta-miR-2382-5p, and ADAMTS1 and bta-miR-2425-5p were verified using luciferase reporter assays and quantitative RT-PCR. The detection of triglyceride production in BMECs showed that bta-miR-21-3p and bta-miR-148a promote triglyceride synthesis, whereas bta-miR-124a, bta-miR-877, bta-miR-2382-5p, and bta-miR-2425-5p inhibit triglyceride synthesis. The conjoint analysis could identify functional miRNAs and regulatory candidate genes involved in lipid metabolism within the co-expression networks of the dairy cattle mammary system, which contributes to the understanding of potential regulatory mechanisms of genetic element and gene signaling networks involved in milk fat metabolism.

Reisolation of Staphylococcus aureus from bovine milk following experimental inoculation is influenced by fat percentage and specific immunoglobulin G1 titer in milk.

The associations of management parameters, herd characteristics, and individual cow factors with bovine mastitis have been subject of many studies. The present study aimed to evaluate the association between milk composition parameters, including fat, protein, lactose, urea, and specific immunoglobulin levels, at the time of experimental bacterial inoculation of the mammary gland and subsequent shedding dynamics of Staphylococcus aureus. Sixty-eight cows were experimentally infected with S. aureus and closely monitored for 3 wk. Mixed model analyses were used to determine the influence of management and herd characteristics (farm and experimental group), individual cow factors (days in milk, milk yield, and quarter position), and a challenge-related parameter (inoculation dose) in combination with either the milk components fat, protein, lactose and urea, or the S. aureus-specific antibody isotype titers at the time of bacterial inoculation, on the number of S. aureus reisolated from milk after inoculation. A positive association was observed between the milk fat percentage and the number of S. aureus reisolated from quarter milk, and a negative relationship between the S. aureus-specific IgG1 titer in milk and the number of S. aureus. These findings should be considered in the development of a vaccine against S. aureus-induced bovine mastitis.

Non-targeted metabolomics identifies biomarkers in milk with high and low milk fat percentage.

Milk is widely recognized as an important food source with health benefits. Different consumer groups have different requirements for the content and proportion of milk fat; therefore, it is necessary to investigate the differential metabolites and their regulatory mechanisms in milk with high and low milk fat percentages (MFP). In this study, untargeted metabolomics was performed on milk samples from 13 cows with high milk fat percentage (HF) and 13 cows with low milk fat percentage (LF) using ultra-high performance liquid chromatography coupled with mass spectrometry (UHPLC-MS/MS). Forty-eight potential differentially labeled compounds were screened using the orthogonal partial least squares-discriminant analysis (OPLS-DA) combined with the weighted gene co-expression network analysis (WGCNA) method. Amino acid metabolism was the key metabolic pathway with significant enrichment of L-histidine, 5-oxoproline, L-aspartic acid, and L-glutamic acid. The negative correlation with MFP differentiated the HF and LF groups. To further determine the potential regulatory role of these amino acids on milk fat metabolism, the expression levels of marker genes in the milk fat synthesis pathway were explored. It was noticed that L-histidine reduced milk fat concentration primarily by inhibiting the triglycerides (TAG) synthesis pathway. L-aspartic acid and L-glutamic acid inhibited milk fat synthesis through the fatty acid de novo and TAG synthesis pathways. This study provides new insights into the mechanism underlying milk fat synthesis and milk quality improvement.

Integrated metagenomics and metabolomics analyses revealed biomarkers in ß-casein A2A2-type cows.

In Holstein cows, ß-casein, one of the most critical proteins in milk, exists in two main genotypes, A1 and A2. Herein, 45 Holstein cows [categorized into three groups based on ß-casein A1A1, A1A2, and A2A2 genotypes (N = 15)] with the same feeding management and litter size were enrolled to explore differences in rumen microflora and metabolites across various ß-casein genotypes. Rumen fluids were collected for metagenomics and metabolomics analyses. Metabolomics and weighted gene co-expression network analysis (WGCNA) revealed that arachidonic acid (AA), adrenic acid (AdA), glycocholic acid (GCA), and taurocholic acid (TCA) were significantly and positively correlated with milk fat % in dairy cows (p < 0.05). Furthermore, macro-genomics and Spearman's correlation analysis revealed significant positive correlations (p < 0.05) between the characteristic flora (g_Acetobacter, g_Pseudoxanthomonas, g_Streptococcus, and g_Pediococcus) and the five characteristic metabolites in the rumen of A2A2 dairy cows. Moreover, functional enrichment analysis revealed more genes enriched to the TRP channel's inflammatory mediator-regulated pathway and the mTOR signaling pathway in A2A2 genotyped cows. Additionally, the regulatory effects of AA on bovine mammary epithelial cells (BMECs) were examined using CCK-8, EdU, and qRT-PCR assays, revealing that AA promoted triglyceride (TG) synthesis and upregulated the milk fat marker genes including SREBF1, ACSS2, AGPAT6, and FASN. Overall, we identified characteristic microorganisms and metabolites in A2A2 Holstein cows and established that AA could be a biomarker for higher milk fat %.

Excavation and characterization of key circRNAs for milk fat percentage in Holstein cattle.

Milk fat percentage is one of the significant indicators governing the price and quality of milk and is regulated by a variety of non-coding RNAs. We used RNA sequencing (RNA-seq) techniques and bioinformatics approaches to explore potential candidate circular RNAs (circRNAs) regulating milk fat metabolism. After analysis, compared with low milk fat percentage (LMF) cows, 309 circRNAs were significantly differentially expressed in high milk fat percentage (HMF) cows. Functional enrichment and pathway analysis revealed that the main functions of the parental genes of differentially expressed circRNAs (DE-circRNAs) were related to lipid metabolism. We selected four circRNAs (Novel_circ_0000856, Novel_circ_0011157, novel_circ_0011944, and Novel_circ_0018279) derived from parental genes related to lipid metabolism as key candidate DE-circRNAs. Their head-to-tail splicing was demonstrated by linear RNase R digestion experiments and Sanger sequencing. However, the tissue expression profiles showed that only Novel_circ_0000856, Novel_circ_0011157, and Novel_circ_0011944 were expressed with high abundance in breast tissue. Based on the subcellular localization found that Novel_circ_0000856, Novel_circ_0011157, and Novel_circ_0011944 mainly function as competitive endogenous RNAs (ceRNAs) in the cytoplasm. Therefore, we constructed their ceRNA regulatory networks, and the five hub target genes (CSF1, TET2, VDR, CD34, and MECP2) in ceRNAs were obtained by CytoHubba and MCODE plugins in Cytoscape, as well as tissue expression profiles analysis of target genes. These genes play a key role as important target genes in lipid metabolism, energy metabolism, and cellular autophagy. The Novel_circ_0000856, Novel_circ_0011157, and Novel_circ_0011944 regulate the expression of hub target genes through interaction with miRNAs and constitute key regulatory networks that may be involved in milk fat metabolism. The circRNAs obtained in this study may act as miRNA sponges and thus influence mammary gland development and lipid metabolism in cows, which improves our understanding of the role of circRNAs in cow lactation.

Milk is an important food source, consisting of a complex mixture of lipids, proteins, carbohydrates, and other factors, of which milk fat not only affects the flavor and nutritional value of milk but also plays an important role in the metabolism of nutrients during human growth and development. To dig for potential circular RNAs (circRNAs) and their key regulatory networks that regulate milk fat, we used RNA sequencing (RNA-seq) to identify 309 circRNAs that are differentially expressed between the mammary epithelial cells (MECs) of cows with high and low milk fat percentage. We screened key circRNAs and their circRNA-miRNA-mRNA regulatory networks affecting milk fat by bioinformatic methods. It provides a new way to study lactation, milk quality, and breed improvement in dairy cows.

Variety of rumen microbial populations involved in biohydrogenation related to individual milk fat percentage of dairy cows.

Our objective was to investigate the contribution of the rumen microbiome on the individual milk fat percentage (MFP) of Holstein dairy cows under the same nutritional and management conditions. From 92 early lactation dairy cows, the top 10 with the highest MFP (HF; n = 10) and the last 10 with the lowest MFP (LF; n = 10) were selected for the study. As a result, the milk trans-10, cis-12 C18:2 content was significant lower in the HF group than that in the LF group (P < 0.001). The rumen acetate to propionate ratio was significant higher in the HF group than that in the LF group (P = 0.035). According to the results of 16S rRNA gene sequencing, a minor but significant difference existed between the groups (P = 0.040). Three genera of the family Lachnospiraceae and four genera of the order Bacteroidales were identified to be the biomarkers for the LF group and HF group in the LEfSe analysis, respectively. Three microbial modules enriched by the family Lachnospiraceae were positively related to the milk trans-10, cis-12 C18:2 content (r s > 0.60, P < 0.05). According to the results of shotgun metagenome sequencing, three kinds of linoleic acid (LA) isomerase genes were present in the gene pools of the rumen microbiome. Among them, the relative abundance of Bifidobacterium LA isomerase (BBI) was higher in the HF group than that in the LF group (P = 0.007). Three metagenome-assembled genomes (MAGs) with LA isomerase genes were positively correlated to the milk trans-10, cis-12 C18:2 content (r s > 0.40, P < 0.05). Furthermore, all of these three MAGs were found to be able to produce lactate. Taken together, these results indicate that the increased relative abundance of microbial population with the trans-10 biohydrogenation pathway within the rumen microbiome contributes to the decrease of MFP via the increase of rumen trans-10, cis-12 C18:2 production. This study provides a new perspective for the development of measures for improving the milking performance of dairy cows.

CircRNA screening and ceRNA network construction for milk fat metabolism in dairy cows.

Background: Milk fat is one of the main reference elements for evaluating milk quality and is a primary objective trait in dairy cattle breeding. In recent years, circular RNAs (circRNAs) have been found to play crucial roles in many biological processes. However, the function and expression profiles of circRNAs in milk fat synthesis in cows are not completely understood. We performed RNA sequencing to analyze the genome-wide expression of circRNA transcripts in bovine mammary epithelial cells (BMECs) from cows with extreme differences in milk fat percentage. We identified candidate differential circRNAs associated with milk fat metabolism using functional enrichment analysis and constructed a lipid metabolism-related competing endogenous RNA (ceRNA) interactive regulatory network. Results: A total of 290 circRNAs were significantly differentially expressed (DE-circRNAs) in high milk fat percentage (HMF) cows compared to that in low milk fat percentage (LMF) cows. Of the 290 circRNAs, 142 were significantly upregulated and 148 were significantly downregulated. Enrichment analysis (Gene Ontology and Kyoto Encyclopedia of Genes and Genomes) identified four DE-circRNAs (circ_0001122, circ_0007367, circ_0018269, and circ_0015179) that potentially regulate milk fat metabolism. Among them, circ_0001122, circ_0007367, and circ_0015179 had relatively high expression levels in cow mammary gland tissue compared to other tissues (heart, liver, kidney, uterus, ovaries, and small intestine) of cows. The regulatory networks circ_0001122:miR-12043:LIPG, circ_0007367:miR-331-3p:CIDEA/PML, and circ_0018269:miR-11989:RORC/HPX are potential networks to explore the mechanism of milk fat regulation. Conclusions: These results reveal the possible role of circRNAs in milk fat metabolism in dairy cows. Several important circRNAs and ceRNAs affecting milk fat synthesis were identified, providing insights into the complex biology of milk fat synthesis as well as a novel theoretical perspective for future research on lactation, milk quality, and breed improvement in dairy cows.

Screening and Conjoint Analysis of Key lncRNAs for Milk Fat Metabolism in Dairy Cows.

Long noncoding RNAs (lncRNAs) play an important regulatory role in various biological processes as a key regulatory factor. However, the complete expression profile of lncRNAs in dairy cows and its function in milk fat synthesis are unknown. In this study, RNA sequencing (RNA-seq) was used to research the whole genome expression of lncRNAs and mRNA transcripts in high and low milk fat percentage (MFP) bovine mammary epithelial cells (BMECs), and joint analysis was carried out. We identified a total of 47 differentially expressed genes (DEGs) and 38 differentially expressed lncRNAs (DELs, Padj <0.05), enrichment analysis screened out 11 candidate DEGs that may regulate milk fat metabolism. Downregulated differential gene ENPP2 (The expression level in BMECs of high milk fat dairy cows was lower than that of low milk fat cows) and upregulated differential gene BCAT1 are more likely to participate in the milk fat metabolism, and its function needs further experiments verification. The enrichment analysis of target genes predicted by DELs identified 7 cis (co-localization) and 10 trans (co-expression) candidate target genes related to milk lipid metabolism, corresponding to a total of 18 DELs. Among them, the targeting relationship between long intervening/intergenic noncoding RNA (lincRNA) TCONS_00082721 and FABP4 is worthy of attention. One hundred and fifty-six competing endogenous RNAs (ceRNAs) interaction regulation networks related to milk fat metabolism were constructed based on the expression information of DELs, differential microRNAs (miRNAs), and lipid metabolism-related target genes. The regulatory network centered on miR-145 will be the focus of subsequent experimental research. The ceRNAs regulatory network related to TCONS_00082721 and TCONS_00172817 are more likely to be involved in milk fat synthesis. These results will provide new ways to understand the complex biology of dairy cow milk fat synthesis and provide valuable information for breed improvement of Chinese Holstein cow.

Analysis of Non-Genetic Factors Affecting Wood's Model of Daily Milk Fat Percentage of Holstein Cattle.

This research paper aimed to explore the characteristics of Holstein cattle's milk fat percentage lactation curve and its influencing factors. The Wood model was used for fitting the lactation curve of 398,449 DHI test-day milk fat percentage records of Holstein cows from 2018 to 2020 in 12 dairy farms in Jiangsu province, and the influencing factors­including farm size, parity, calving season, calving interval, and 305-days milk production­on the parameters of the lactation curve were analyzed. The results showed that the non-genetic factors such as dairy farm size, calving season, parity, calving interval, and 305-days milk yield have a significant impact on milk fat percentage (p < 0.01); the average R2 of the daily milk fat percentage curve was 0.9699; the lowest milk fat percentage was 3.54%; the time to reach the lowest milk fat percentage was 126 days; and the persistence of milk fat percentage was 3.59%. All of these factors explored in this study fit at different levels above 0.96. The Wood model performed well in the fitting and analysis of the milk fat percentage curve of Holstein cattle in Jiangsu Province. This study provides a reference for improving the milk fat percentage of Holstein cattle.

Sequence Variation in the Bovine Lipin-1 Gene (LPIN1) and Its Association with Milk Fat and Protein Contents in New Zealand Holstein-Friesian × Jersey (HF × J)-cross Dairy Cows.

Lipin-1 is known to play a regulatory role in tissues that function in lipid metabolism. In dairy cows, the lipin-1 gene (LPIN1) is highly expressed in the mammary gland, but its function in milk production is less understood. In this study, we used PCR-single strand conformation polymorphism analysis to investigate sequence variation in three regions of bovine LPIN1 in New Zealand Holstein-Friesian × Jersey (HF × J)-cross dairy cows, including part of the 5' non-coding region, the region containing the LPIN1ß-spliced exon, and the sixth coding exon that encodes the putative transcriptional activating domain of the protein. No variation was found in the LPIN1ß-spliced exon, but two sequence variants containing one single nucleotide polymorphism (SNP) were identified in the 5' non-coding region and four sequence variants containing four non-synonymous SNPs were identified in the sixth coding exon. Among the three common variants of the sixth coding exon, variant C was found to be associated with an increase in milk fat percentage (presence 4.96 ± 0.034% vs. absence 4.81 ± 0.050%; p = 0.006) and milk protein percentage (presence 4.09 ± 0.017% vs. absence 3.99 ± 0.025%; p = 0.001), but no associations (p > 0.01) were detected for milk yield. These results suggest that variation in LPIN1 affect the synthesis of fat and proteins in milk and has potential as a gene-marker to improve milk production traits.