Genetic mechanisms regulating the host response during mastitis

Mastitis is a very costly and common disease in the dairy industry. The study of the transcriptome from healthy and mastitic milk somatic cell samples using RNA-Sequencing technology can provide measurements of transcript levels associated with the immune response to the infection. The objective of this study was to characterize the Holstein milk somatic cell transcriptome from 6 cows to determine host response to intramammary infections. RNA-Sequencing was performed on 2 samples from each cow from 2 separate quarters, one classified as healthy (n = 6) and one as mastitic (n = 6). In total, 449 genes were differentially expressed between the healthy and mastitic quarters (false discovery rate <0.05, fold change >±2). Among the differentially expressed genes, the most expressed genes based on reads per kilobase per million mapped reads (RPKM) in the healthy group were associated with milk components (CSN2 and CSN3), and in the mastitic group they were associated with immunity (B2M and CD74). In silico functional analysis was performed using the list of 449 differentially expressed genes, which identified 36 significantly enriched metabolic pathways (false discovery rate <0.01), some of which were associated with the immune system, such as cytokine-cytokine interaction and cell adhesion molecules. Seven functional candidate genes were selected, based on the criteria of being highly differentially expressed between healthy and mastitic groups and significantly enriched in metabolic pathways that are relevant to the inflammatory process (GLYCAM1, B2M, CD74, BoLA-DRA, FCER1G, SDS, and NFKBIA). Last, we identified the differentially expressed genes that are located in quantitative trait locus regions previously known to be associated with mastitis, specifically clinical mastitis, somatic cell count, and somatic cell score. It was concluded that multiple genes within quantitative trait locus regions could potentially affect host response to mastitis-causing agents, making some cows more susceptible to intramammary infections. The identification of potential candidate genes with functional, statistical, biological, and positional relevance associated with host defense to infection will contribute to a better understanding of the underlying genetic architecture associated with mastitis. This in turn will improve the sustainability of agricultural practices by facilitating the selection of cows with improved host defense leading to increased resistance to mastitis.

Milk fat globule is an alternative to mammary epithelial cells for gene expression analysis in buffalo

Owing to the difficulty in obtaining mammary gland tissue from lactating animals, it is difficult to test the expression levels of genes in mammary gland. The aim of the current study was to identify if milk fat globule (MFG) in buffalo milk was an alternative to mammary gland (MG) and milk somatic cell (MSC) for gene expression analysis. Six buffalos in late lactation were selected to collect MFG and MSC, and then MG was obtained by surgery. MFG was stained with acridine orange to successfully visualise RNA and several cytoplasmic crescents in MFG. The total RNA in MFG was successfully isolated and the integrity was assessed by agarose gel electrophoresis. We analysed the cellular components in MFG, MG and MSC through testing the expression of cell-specific genes by qRT-PCR. The results showed that adipocyte-specific gene (AdipoQ) and leucocyte-specific genes (CD43, CSF1 and IL1α) in MFG were not detected, whereas epithelial cell marker genes (Keratin 8 and Keratin 18) in MFG were higher than in MSC and lower than in MG, fibroblast marker gene (vimentin) in MFG was significantly lower than in MG and MSC, milk protein genes (LALBA, BLG and CSN2) and milk fat synthesis-related genes (ACC, BTN1A1, FABP3 and FAS) in MFG were higher than in MG and MSC. In conclusion, the total RNA in MFG mainly derives from mammary epithelial cells and can be used to study the functional gene expression of mammary epithelial cells.

Technical note: Selection of suitable reference genes for studying gene expression in milk somatic cell of yak (Bos grunniens) during the lactation cycle

Quantitative real-time PCR is the most sensitive technique for gene expression analysis. Data normalization is essential to correct for potential errors incurred in all steps from RNA isolation to PCR amplification. The commonly accepted approach for normalization is the use of reference gene. Until now, no suitable reference genes have been available for data normalization of gene expression in milk somatic cells of lactating yaks across lactation. In the present study, we evaluated the transcriptional stability of 10 candidate reference genes in milk somatic cells of lactating yak, including ACTB, B2M, GAPDH, GTP, MRPL39, PPP1R11, RPS9, RPS15, UXT, and RN18S1. Four genes, RPS9, PPP1R11, UXT, and MRPL39, were identified as being the most stable genes in milk somatic cells of lactating yak. Using the combination of RPS9, PPP1R11, UXT, and MRPL39 as reference genes, we further assessed the relative expression of 4 genes of interest in milk somatic cells of yak across lactation, including ELF5, ABCG2, SREBF2, and DGAT1. Compared with expression in colostrum, the overall transcription levels of ELF5, ABCG2, and SREBF2 in milk were found to be significantly upregulated in early, peak, and late lactation, and significantly downregulated thereafter, before the dry period. A similar pattern was observed in the relative expression of DGAT1, but no significant difference was revealed in its expression in milk from late lactation compared with colostrum. Based on these results, we suggest that the geometric mean of RPS9, PPP1R11, UXT, and MRPL39 can be used for normalization of real-time PCR data in milk somatic cells of lactating yak, if similar experiments are performed.