PSXI-28 Gene signature patterns in endometrium through co-expression network analysis associated with fertility in beef heifers.

Abstract Reproductive efficiency in beef cattle is crucial to the sustainability and profitability of the cow-calf industry. Despite this fact, reproductive failure and pregnancy loss are among the most prevalent issues influencing efficiency and management decisions. Successful establishment and maintenance of pregnancy are dependent on both embryo viability and a receptive uterine endometrium (UE). Failure of the endometrium to establish a healthy, receptive environment during the pre-placentation window is a leading cause of early pregnancy loss. Thus, we hypothesized that differences in the gene expression and co-expression in caruncular endometrial tissue will affect biological processes and pathways, leading to varying reproductive outcomes. Thus, we measured the endometrial gene expression of Angus-Simmental crossbred heifers classified as either fertile or subfertile. The heifers underwent estrus synchronization and a fixed-time artificial insemination (AI) protocol, and pregnancy was determined 42 days post-AI using ultrasound and palpation. Heifers pregnant to AI (n = 7) were classified as fertile, while those that failed to conceive both by AI and natural service (n = 5) were classified as sub-fertile. Pregnancies were terminated in fertile heifers, and heifers from both groups were allowed to resume normal cyclicity prior to harvest. At slaughter, uterine tracts were collected, and RNA was extracted from the endometrium for mRNA-sequencing. After filtering and quality control of the RNA-Seq data, differential expression analyses of genes (DEGs) were performed using DESeq2. We identified 894 DEGs between the groups, with 226 upregulated and 668 downregulated genes in the sub-fertile group (p ≤ 0.05, absolute log2 fold change ≥ 0.5). The DEGs were used for co-expression network and differential connectivity (DK) analyses using the PCIT and Cytoscape software. The significantly correlated gene pairs (|r| > 0.99) were filtered. The gene co-expression network analysis identified 42 and 344 hub genes in the fertile and sub-fertile groups, respectively. Interestingly, the hub genes in the fertile group included ADRA2C (adrenergic receptor alpha 2C), PPP1R14D (protein phosphatase 1), MEX3B (RNA binding phosphoprotein) as the ones with the highest number of network connections, while KCNE1 (potassium voltage-gated channels), CYP11A1 (cytochrome P450), interleukins (IL15 and IL1B), and PTGS2 (prostaglandin-endoperoxide synthase 2) were the hub genes with the highest network connectivity in the sub-fertile group. The differential connectivity between the networks of each group revealed a gain in connectivity due to the rewiring of major regulators in the sub-fertile group. The hub genes from the sub-fertile group were over-represented for ovarian steroidogenesis, phagosome, and the TNF-signaling pathway. A detailed understanding of the underlying biological mechanisms of the top targets and a follow-up study are warranted to validate the potential candidates identified in this study.