Udder conformation traits are one of the most economic traits in dairy cows, greatly affecting animal health, milk production, and producer profitability in the dairy industry. Genetic analysis of udder structure and scores have been developed in Holstein cattle. In our research, we conducted a genome-wide association study for five udder traits, including anterior udder attachment (AUA), central suspensory ligament (CSL), posterior udder attachment height (PUAH), posterior udder attachment width (PUAW), and udder depth (UD), in which the fixed and random model circulating probability unification (FarmCPU) model was applied for the association analysis. The heritability and the standard errors of these five udder traits ranged from 0.04 ± 0.00 to 0.49 ± 0.03. Phenotype data were measured from 1000 Holstein cows, and the GeneSeek Genomic Profiler (GGP) Bovine 100 K SNP chip was used to analyze genotypic data in Holstein cattle. For GWAS analysis, 984 individual cows and 84,407 single-nucleotide polymorphisms (SNPs) remained after quality control; a total of 18 SNPs were found at the GW significant threshold (p < 5.90 × 10−7). Many candidate genes were identified within 200kb upstream or downstream of the significant SNPs, which include MGST1, MGST2, MTUS1, PRKN, STXBP6, GRID2, E2F8, CDH11, FOXP1, SLF1, TMEM117, SBF2, GC, ADGRB3, and GCLC. Pathway analysis revealed that 58 Gene Ontology (GO) terms and 18 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were enriched with adjusted p values, and these GO terms and the KEGG pathway analysis were associated with biological information, metabolism, hormonal growth, and development processes. These results could give valuable biological information for the genetic architecture of udder conformation traits in dairy Holstein cattle.

The objective of this research was to explore the effect of metformin on the lipoteichoic acid (LTA)–induced mastitis model using isolated primary bovine mammary epithelial cells (PBMECs). The PBMECs were exposed to either 3 mM metformin for 12 h as a metformin group (MET) or 100 μg/mL LTA for 6 h as LTA group (LTA). Cells pretreated with 3 mM metformin for 12 h followed by washing and 100 μg/mL LTA exposure for 6 h served as the MET + LTA group. Phosphate-buffered saline was added to cells as the control group. PBMECs pretreated with different metformin doses were analyzed by a flow cytometry (annexin V–fluorescein isothiocyanate assay) to detect the cell apoptotic rate. We performed quantitative reverse transcriptase–polymerase chain reaction and Western blot analysis to evaluate the inflammatory and oxidative responses to metformin and LTA by measuring cellular cytotoxicity, mRNA expression, and protein expression. Immunofluorescence was used to evaluate nuclear localization. The results showed that the gene expression of COX2, IL-1β, and IL-6 significantly increased in the cells challenged with LTA doses compared to control cells. In inflammatory PBMECs, metformin attenuated LTA-induced expression of inflammatory genes nuclear factor κB (NF-κB) p65, tumor necrosis factor α, cyclooxygenase 2, and interleukin 1β, as well as the nuclear localization and phosphorylation of NF-κBp65 protein, but increased the transcription of nuclear factor erythroid 2–related factor 2 (Nrf2) and Nrf2-targeted antioxidative genes heme oxygenase-1 (HO-1) and Gpx1, as well as the nuclear localization of HO-1 protein. Importantly, metformin-induced activation of Nrf2 is AMP-activated protein kinase (AMPK)–dependent; as metformin-pretreated PBMECs activated AMPK signaling via the upregulation of phosphorylated AMPK levels, cell pretreatment with metformin also reversed the translocation of Nrf2 that was LTA inhibited. This convergence between AMPK and Nrf2 pathways is essential for the anti-inflammatory effect of metformin in LTA-stimulated PBMECs. Altogether, our results indicate that metformin exerts anti-inflammation and oxidative stress through regulation of AMPK/Nrf2/NF-κB signaling pathway, which highlights the role of AMPK as a potential therapeutic strategy for treatment of bovine mastitis.

Accurately estimating the genetic parameters and revealing more genetic variants underlying milk production and quality are conducive to the genetic improvement of dairy cows. In this study, we estimate the genetic parameters of five milk-related traits of cows—namely, milk yield (MY), milk fat percentage (MFP), milk fat yield (MFY), milk protein percentage (MPP), and milk protein yield (MPY)—based on a random regression test-day model. A total of 95,375 test-day records of 9,834 cows in the lower reaches of the Yangtze River were used for the estimation. In addition, genome-wide association studies (GWASs) for these traits were conducted, based on adjusted phenotypes. The heritability, as well as the standard errors, of MY, MFP, MFY, MPP, and MPY during lactation ranged from 0.22 ± 0.02 to 0.31 ± 0.04, 0.06 ± 0.02 to 0.15 ± 0.03, 0.09 ± 0.02 to 0.28 ± 0.04, 0.07 ± 0.01 to 0.16 ± 0.03, and 0.14 ± 0.02 to 0.27 ± 0.03, respectively, and the genetic correlations between different days in milk (DIM) within lactations decreased as the time interval increased. Two, six, four, six, and three single nucleotide polymorphisms (SNPs) were detected, which explained 5.44, 12.39, 8.89, 10.65, and 7.09% of the phenotypic variation in MY, MFP, MFY, MPP, and MPY, respectively. Ten Kyoto Encyclopedia of Genes and Genomes pathways and 25 Gene Ontology terms were enriched by analyzing the nearest genes and genes within 200 kb of the detected SNPs. Moreover, 17 genes in the enrichment results that may play roles in milk production and quality were selected as candidates, including CAMK2G, WNT3A, WNT9A, PLCB4, SMAD9, PLA2G4A, ARF1, OPLAH, MGST1, CLIP1, DGAT1, PRMT6, VPS28, HSF1, MAF1, TMEM98, and F7. We hope that this study will provide useful information for in-depth understanding of the genetic architecture of milk production and quality traits, as well as contribute to the genomic selection work of dairy cows in the lower reaches of the Yangtze River.

Reproduction is an important production activity for dairy cows, and their reproductive performance can directly affect the level of farmers’ income. To better understand the genomic regions and biological pathways of reproduction-related traits of dairy cows, in the present study, three body shape traits—Loin Strength (LS), Rump Angle (RA), and Pin Width (PW)—were selected as indicators of the reproductive ability of cows, and we conducted genome-wide association analyses on them. The heritability of these three traits was medium, ranging from 0.20 to 0.38. A total of 11 significant single-nucleotide polymorphisms (SNPs) were detected associated with these three traits. Bioinformatics analysis was performed on genes close to the significant SNPs (within 200 Kb) of LS, RA, and PW, and we found that these genes were totally enriched in 20 gene ontology terms and six KEGG signaling pathways. Finally, the five genes CDH12, TARP, PCDH9, DTHD1, and ARAP2 were selected as candidate genes that might affect LS. The six genes LOC781835, FSTL4, ATG4C, SH3BP4, DMP1, and DSPP were selected as candidate genes that might affect RA. The five genes USP6NL, CNTN3, LOC101907665, UPF2, and ECHDC3 were selected as candidate genes that might affect the PW of Chinese Holstein cows. Our results could provide useful biological information for the improvement of body shape traits and contribute to the genomic selection of Chinese Holstein cows.

Feet and leg conformation traits are considered one of the most important economical traits in dairy cattle and have a great impact on the profitability of milk production. Therefore, identifying the single nucleotide polymorphisms (SNPs), genes and pathways analysis associated with these traits might contribute to the genomic selection and long-term plan selection for dairy cattle. We conducted genome-wide association studies (GWASs) using the fixed and random model circulating probability unification (FarmCPU) method to identify SNPs associated with bone quality, heel depth, rear leg side view and rear leg rear view of Chinese Holstein cows. Phenotypic measurements were collected from 1000 individuals of Chinese Holstein cattle and the GeneSeek Genomic Profiler Bovine 100 K SNP chip was utilized for individual genotyping. After quality control, 984 individual cows and 84,906 SNPs remained for GWAS work; as a result, we identified 20 significant SNPs after Bonferroni correction. Several candidate genes were identified within distances of 200 kb upstream or downstream to the significant SNPs, including ADIPOR2, INPP4A, DNMT3A, ALDH1A2, PCDH7, XKR4 and CADPS. Further bioinformatics analyses showed 34 gene ontology terms and two signaling pathways were significantly enriched (p ≤ 0.05). Many terms and pathways are related to biological quality, metabolism and development processes; these identified SNPs and genes could provide useful information about the genetic architecture of feet and leg traits, thus improving the longevity and productivity of Chinese Holstein dairy cattle.