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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 rate0.05, 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 rate0.01), 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.

The technological properties of milk have significant importance for the dairy industry. Citrate, a normal constituent of milk, forms one of the main buffer systems that regulate the equilibrium between Ca 2+ and H + ions. Higher-than-normal citrate content is associated with poor coagulation properties of milk. To identify the genes responsible for the variation of citrate content in milk in dairy cattle, the metabolic steps involved in citrate and fatty acid synthesis pathways in ruminant mammary tissue using RNA sequencing were studied. Genetic markers that could influence milk citrate content in Holstein cows were used in a marker-trait association study to establish the relationship between 74 single nucleotide polymorphisms (SNP) in 20 candidate genes and citrate content in 250 Holstein cows. This analysis revealed 6 SNP in key metabolic pathway genes [isocitrate dehydrogenase 1 (NADP+), soluble ( IDH1 ); pyruvate dehydrogenase (lipoamide) β ( PDHB ); pyruvate kinase ( PKM2 ); and solute carrier family 25 (mitochondrial carrier; citrate transporter), member 1 ( SLC25A1 )] significantly associated with increased milk citrate content. The amount of the phenotypic variation explained by the 6 SNP ranged from 10.1 to 13.7%. Also, genotype-combination analysis revealed the highest phenotypic variation was explained combining IDH1 _23211, PDHB _5562, and SLC25A1 _4446 genotypes. This specific genotype combination explained 21.3% of the phenotypic variation. The largest citrate associated effect was in the 3′ untranslated region of the SLC25A1 gene, which is responsible for the transport of citrate across the mitochondrial inner membrane. This study provides an approach using RNA sequencing, metabolic pathway analysis, and association studies to identify genetic variation in functional target genes determining complex trait phenotypes.

To fine map a quantitative trait locus (QTL) affecting milk production traits previously associated with microsatellite RM188, we implemented an interval mapping analysis by using microsatellite markers in a large Israeli Holstein half-sib sire family, and linkage disequilibrium (LD) mapping in a large set of US Holstein bulls. Interval mapping located the target QTL to the near vicinity of RM188. For the LD mapping, we identified 42 single nucleotide polymorphisms (SNP) in 15 genes in a 12-Mb region on bovine chromosome 4. A total of 24 tag SNP were genotyped in 882 bulls belonging to the University of California Davis archival collection of Holstein bull DNA samples with predicted transmitted ability phenotypes. Marker-to-marker LD analysis revealed 2 LD blocks, with intrablock r 2 values of 0.10 and 0.46, respectively; outside the blocks, r 2 values ranged from 0.002 to 0.23. A standard additive/dominance model using the generalized linear model procedure of SAS and the regression module of HelixTree software were used to test marker-trait associations. Single nucleotide polymorphism 9 on ARL4A, SNP10 on XR_027435.1, SNP12 on ETV1, SNP21 on SNX13, and SNP24 were significantly associated with milk production traits. We propose the interval encompassing ARL4A and SNX13 genes as a candidate region in bovine chromosome 4 for a concordant QTL related to milk protein traits in dairy cattle. Functional studies are needed to confirm this result.