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.