The transcriptome signature of the receptive bovine uterus determined at early gestation
Faculty of Pharmaceutical, Biomedical and Veterinary Sciences. Veterinary Sciences
, p. 1-13
Pregnancy success is critical to the profitability of cattle operations. However, the molecular events driving the uterine tissue towards embryo receptivity are poorly understood. This study aimed to characterize the uterine transcriptome profiles of pregnant (P) versus non-pregnant (NP) cows during early pregnancy and attempted to define a potential set of marker genes that can be valuable for predicting pregnancy outcome. Therefore, beef cows were synchronized (n=51) and artificially inseminated (n=36) at detected estrus. Six days after AI (D6), jugular blood samples and a biopsy from the uterine horn contralateral to the ovary containing the corpus luteum were collected. Based on pregnancy outcome on D30, samples were retrospectively allocated to the following groups: P (n=6) and NP (n=5). Both groups had similar plasma progesterone concentrations on D6. Uterine biopsies were submitted to RNA-Seq analysis in a Illumina platform. The 272,685,768 million filtered reads were mapped to the Bos Taurus reference genome and 14,654 genes were analyzed for differential expression between groups. Transcriptome data showed that 216 genes are differently expressed when comparing NP versus P uterine tissue (Padj≤0.1). More specifically, 36 genes were up-regulated in P cows and 180 are up-regulated in NP cows. Functional enrichment and pathway analyses revealed enriched expression of genes associated with extracellular matrix remodeling in the NP cows and nucleotide binding, microsome and vesicular fraction in the P cows. From the 40 top-ranked genes, the transcript levels of nine genes were re-evaluated using qRT-PCR. In conclusion, this study characterized a unique set of genes, expressed in the uterus 6 days after insemination, that indicate a receptive state leading to pregnancy success. Furthermore, expression of such genes can be used as potential markers to efficiently predict pregnancy success.