Introduction: The placenta is a developing organ providing tight interrelation between the mother and fetus during the whole period of gestation. The main driver of development is gene expression. Detailing the placental tissue transcriptome changes underlying normal pregnancies could provide a valuable resource for genomic studies related to placental dysfunctions.

Aim: To utilize publicly available gene expression raw data to identify differentially expressed genes in the human placenta between second and first and third and second trimesters of physiological gestation and provide the biological interpretation of the results.

Methods: We downloaded gene expression data from our IGEA database available at http://igea.sysbio.org.ua/ (77 samples, 8 datasets, collected from open access data), integrated raw data by cross-normalization and batch-effect removal. We used: generalized linear models for differentially expressed genes (DEGs) identification (adjusted p-value (FDR)<0.05, fold change |logfc>1|); fastgreedy algorithm to elicit interrelated gene clusters among DEGs; Gene Ontology and the String web tool to reveal overrepresented differential biological processes and cellular pathways compared to the whole genome. 

Results: We identified 253 differentially expressed genes (DEGs) between the second and first trimester (comparison 2_1), 152 up- and 101 down-regulated, and 489 DEGs between third and second trimester (comparison 3_2), 221 up- and 268 downregulated. There are 4 elicited clusters: immune system process, organ and blood vessel development, cellular response to Zn and Cu ions, and JAK-STAT pathway signaling, in comparison 2_1, and 7 clusters: regulation of response to external stimulus, metabolic processes, tissue morphogenesis, regulation of signaling pathways via transmembrane serine/threonine protein kinase receptors, sodium transport, and transmembrane transport of chloride, and pregnancy-specific beta-1-glycoproteins, in comparison 3_2. Thus, it is the first study of open access and integrated data on gene expression profiles in the human placenta throughout gestation  underlying physiological pregnancy.

Conclusion: Our study will serve as a reference database to gain insight into the regulation of gene expression in the developing placentae and to compare with gene expression in placentae from complicated pregnancies.