Pairwise comparison of mammalian transcriptomes associated with the effect of polyploidy on the expression activity of developmental gene modules

Abstract

Design and development of highly sensitive methods of bioinformatics are associated with the need to obtain information on the impact of epigenetic changes on gene activity. One factor causing such changes is polyploidy. Polyploidy maintains the balance of gene dosage and, therefore, can have only a slight effect on their expression. Currently, there is no unified concept with respect to the impact of polyploidy on transcriptomes. To clarify this issue, we developed an integrative bioinformatics method aimed at accessing weak effects of polyploidy on the activity of genes by implementing a pairwise cross-transcriptome analysis of mammalian tissues with varying degrees of ploidy. The advantage of this method is its ability to distinguish between variable speciesand tissue-specific effects and evolutionarily conserved ones. The applicability of the developed methodology was demonstrated by analysis of genetic modules and protein interaction networks involved in the coordination of developmental processes. We carried out analysis of full transcriptome data for human and mouse heart and liver. We discovered that genes activated by ploidy are enriched (i.e., are presented above the random level) in transcriptomes of biological processes of the Gene Ontology (GO) database and in pathways in the KEGG database related to organism development, morphogenesis, and stem cell biology (including the signaling pathways Hippo, Pi3K, WNT, Hedgehog, and TGF-s) to a greater extent than genes suppressed by ploidy. The structure and composition of the protein interaction networks constructed for ploidy regulated genes confirmed the results of analysis of gene modules. Thus, our data are the first to demonstrate that polyploidy can regulate the modules of organism development by increasing their activity.