Endometrosis is a periglandular fibrosis associated with dysfunction of affected glandular epithelial cells that is the most common cause of reduced fertility in mares, although it is not fully understood. The etiology of the disease is still partially unknown. This study focuses on understanding the genetic mechanisms potentially underlying endometrosis in mares using the Next Generation Sequencing (NGS) technique. Endometrial samples, used in the study, were obtained in the anestrus phase both from healthy mares and those diagnosed with endometrosis. The NGS data were analyzed for gene involvement in biological processes and pathways (e.g. STAR, KOBAS-I, STRING, and ClustVis software). Bioinformatic analysis revealed differential expression of 55 transcripts. In tissues with endometrosis, most genes displayed upregulated expression. The protein-protein interaction analysis disclosed a substantial transcript network including transcripts related to metabolism e.g. sulfur metabolism (SELENBP1), ovarian steroidogenesis, steroid hormone biosynthesis, and chemical carcinogenesis (CYP1B1), COXs (COX4I1, COX3, UQCRFS1) as well as transcripts related to immune response e.g. MMP7, JCHAIN, PIGR, CALR, B2M, FCGRT. Interestingly, the latter has been previously linked with various pathologies including cancers in the female reproductive system. In conclusion, this study evaluated genes that are not directly impacted by sex hormone feedback, but that create a metabolic and immune environment in tissues, thus influencing fertility and pregnancy in mares with endometrosis. Moreover, some of the identified genes may be implicated in tumorigenesis of endometrial lesions. These data may be useful as a starting point in further research, such as the development of targeted strategies for rapid diagnosis and/or prevention of this pathology based on gene and protein-protein interactions.
Keywords: Endometrosis; Mare; Next Generation Sequencing.
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