Gene profiling the window of implantation: Microarray analyses from human and rodent models

Abstract

Poor uterine receptivity leads to implantation defects or failure. Identification of uterine molecules crucial to uterine receptivity and/or embryo implantation provides the opportunity to design a diagnostic screening toolkit for uterine receptivity or targeted drug discovery for treating implantation-based infertility. In this regard, gene-profiling studies performed in humans and rodents have identified numerous genes involved in the transcriptional regulation of uterine receptivity and embryo implantation. In this article, we compared available uterine microarray datasets collected during the time of uterine receptivity and implantation in humans, mice and hamsters to uncover conserved gene sets. We also compared the transcriptome signature of women with unexplained infertility (UIF) and recurrent implantation failure (RIF) to gain insight into genes potentially dysregulated during endometrial receptivity or embryo implantation. Among numerous differentially expressed genes, few were revealed that might have molecular diagnostic screening potential for identifying the uterine receptive state during the time of implantation. Finally, functional annotation of gene sets uncovered altered uterine apoptosis or cell adhesion pathways in women with UIF and RIF, respectively. These conserved or divergent gene sets provide insights into the uterine receptive state for supporting blastocyst implantation.

Keywords: Endometrial receptivity; Gene expression; Implantation site; Recurrent implantation failure; Unexplained infertility.

Fig. 1

(A) Venn diagram illustrating the overlap of DEGs between microarray studies (each circle is color coded to microarray data sets described in Table 1). (B) Fisher's exact test was used to examine overlap of DEGs between microarray data sets. The P-value was converted to –log 10. High degrees of significant association are indicated by bright pink. (C) Shared DEGs are listed in the table. Shared DEGs were uploaded into the DAVID bioinformatics resource and clustered based on their known functions. Official gene symbols in bold typeface represent similar shared DEGs in RIF or UIF between human endometrial receptivity and mouse/hamster embryo implantation (see middle of Venn Diagrams, A). Similarly, shared functional annotation clusters are shown in bold.