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The current study reports the identification of previously undiscovered single-nucleotide polymorphisms (SNPs) in the bovine AGPAT3 gene and further investigates their associations with milk production traits. Our results demonstrate that the major allele C of the SNP g.12264 C > T is positively correlated with test-day milk yield, protein percentage and 305-day milk yield. Importantly, in silico analysis showed that the C/T transition at this locus gives rise to two new transcription factor binding sites (TFBS), E2F1 and Nkx3-2. Polymorphism g.18658 G > A was the only SNP associated with milk urea nitrogen (MUN) with the G allele related to an increase in milk urea nitrogen as well as fat percentage. The GG genotype of SNP g.28731 A > G was associated with the highest fat and protein percentage and lowest 305-day milk yield and somatic cell score (SCS). The association between AGPAT3 locus and milk production traits could be utilized in marker-assisted selection for the genetic improvement of milk production traits and, probably in conjunction with other traits, for selection to improve fitness of dairy cattle. [ABSTRACT FROM AUTHOR]

We established a mastitis model using exogenous infection of the mammary gland of Chinese Holstein cows with Staphylococcus aureus and extracted total RNA from S. aureus -infected and healthy mammary quarters. Differential expression of genes due to mastitis was evaluated using Affymetrix technology and results revealed a total of 1230 differentially expressed mRNAs. A subset of affected genes was verified via Q-PCR and pathway analysis. In addition, Solexa high-throughput sequencing technology was used to analyze profiles of miRNA in infected and healthy quarters. These analyses revealed a total of 52 differentially expressed miRNAs. A subset of those results was verified via Q-PCR. Bioinformatics techniques were used to predict and analyze the correlations among differentially expressed miRNA and mRNA. Results revealed a total of 329 pairs of negatively associated miRNA/mRNA, with 31 upregulated pairs of mRNA and 298 downregulated pairs of mRNA. Differential expression of miR-15a and interleukin-1 receptor-associated kinase-like 2 (IRAK2), were evaluated by western blot and luciferase reporter assays. We conclude that miR-15a and miR-15a target genes (IRAK2) constitute potential miRNA–mRNA regulatory pairs for use as biomarkers to predict a mastitis response. [ABSTRACT FROM AUTHOR]

The research reported in this Research Communication aimed to describe the influence of Toll-like receptor 4 gene polymorphisms on milk production traits in Chinese Holstein cows. Toll-like receptor 4 (TLR4) is an important member of the toll-like receptor gene family that is widely found in various organisms. Since TLR4 can identify molecular patterns from various pathogenic microorganisms and induce natural and acquired immunity, it plays an important role in disease resistance in dairy cows. Two single nucleotide polymorphisms (SNPs) of TLR4 (c.−226 G > C and c.2021 C > T) that were previously found to be associated with health traits were genotyped using Sequenom MassARRAY (Sequenom Inc., San Diego, CA) for Chinese Holstein cows (n = 866). The associations between SNPs or their haplotypes and milk production traits and somatic cell count were analyzed by the generalized linear model procedure of Statistics Analysis System software (SAS). The c.−226 G > C and c.2021 C > T showed low linkage disequilibrium (r 2 = 0·192). There was no association between these two SNPs and SCC, but significant effects were found for SNP c.−226 G > C on test-day milk yield, fat content, protein content, and total solid and milk urea nitrogen (P < 0·05), and SNP c.2021 C > T and the SNP haplotypes on test-day milk yield, fat content, protein content, lactose content and total solids (P < 0·05). The software MatInspector revealed that c.−226 G > C was located within several potential transcription factor binding sites, including transcription factor AP-2. The polymorphisms c.−226 G > C and c.2021 C > T had significant effects on the milk production for Chinese Holstein, and these SNP could be used for molecular marker-assisted selection of milk production. [ABSTRACT FROM AUTHOR]

This study aimed to describe the expression profiles of microRNAs (miRNAs) from mammary gland tissues collected from dairy cows with Streptococcus agalactiae-induced mastitis and to identify differentially expressed miRNAs related to mastitis. The mammary glands of Chinese Holstein cows were challenged with Streptococcus agalactiae to induce mastitis. Small RNAs were isolated from the mammary tissues of the test and control groups and then sequenced using the Solexa sequencing technology to construct two small RNA libraries. Potential target genes of these differentially expressed miRNAs were predicted using the RNAhybrid software, and KEGG pathways associated with these genes were analysed. A total of 18 555 913 and 20 847 000 effective reads were obtained from the test and control groups, respectively. In total, 373 known and 399 novel miRNAs were detected in the test group, and 358 known and 232 novel miRNAs were uncovered in the control group. A total of 35 differentially expressed miRNAs were identified in the test group compared to the control group, including 10 up-regulated miRNAs and 25 down-regulated miRNAs. Of these miRNAs, miR-223 exhibited the highest degree of up-regulation with an approximately 3-fold increase in expression, whereas miR-26a exhibited the most decreased expression level (more than 2-fold). The RNAhybrid software predicted 18 801 genes as potential targets of these 35 miRNAs. Furthermore, several immune response and signal transduction pathways, including the RIG-I-like receptor signalling pathway, cytosolic DNA sensing pathway and Notch signal pathway, were enriched in these predicted targets. In summary, this study provided experimental evidence for the mechanism underlying the regulation of bovine mastitis by miRNAs and showed that miRNAs might be involved in signal pathways during S. agalactiae-induced mastitis. [ABSTRACT FROM PUBLISHER]