Pregnancy loss is an important economic loss in cattle industry. This study was conducted to identify pre- and / or post-implantation genes and cellular algorithms. For this purpose, transcriptome data of endometrium tissue were analyzed. These data refer to three heifer categories: high fertile (HF), sub-fertile (SF) and infertile (IF). After gene detection, genes were divided into two groups: Up-expressed genes, which were up-regulated in every comparison of either favorable fertility cases or unfavorable fertility cases (HF vs. SF, HF vs. IF, and SF vs. IF), and down-expressed genes, which were down-regulated in the mentioned comparisons. String database was applied to construct protein-protein interaction (PPI) networks and clusterone plugin was used to determine the significant sub-network. Enrichment analysis, which involves the gene ontology and functional pathway, was performed to enrich the results. Our results suggested that over-expression of SHCBP1, NOP14, PGM5, and DHX58 genes may have positive effect on the outcome of pregnancy, and down-expression of IMP3, ATP5O, and RPL7 genes could help the reproductive efficiency. The results of the present study showed that the genes in up-regulated clusters could manipulate epithelial differentiation, fundamental biological role, glucose metabolism, and immune response, which led to reduced pregnancy loss. Also the genes in down-regulated clusters may participate in the improvement of pregnancy outcome by inducing anti-apoptotic processes. This study proposes the pregnancy-associated key genes and pathways to improve pregnancy success in cattle and other domestic animals. Manuscript profile