Computational prediction of miRNA/mRNA duplexomes at the whole human genome scale reveals functional subnetworks of interacting genes with embedded miRNA annealing motifs. (October 2020)

• Record Type: Journal Article
• Authors: Pasquier, Claude; Robichon, Alain
• Is Part Of: Computational biology and chemistry. Volume 88(2020)
• Publication Date: 2020-10
• Subjects: miRNA -- mRNA collection -- RNA annealing -- subclasses of mRNA; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2020.107366
• Languages: English
• ISSNs: 1476-9271

Abstract

Graphical abstract: Highlights: A genome-wide-scale computational search of pairing motifs in mRNAs with miRNAs reveals a strong discriminatory distribution. The mRNA collection can be arbitrarily subdivided into six categories depending on the density of miRNA matching motifs. miRNAs can potentially target one unique mRNA, while few miRNAs can target very large numbers of mRNAs. The network of genes presenting a large number of motifs for miRNA annealing overlaps with the network of genetic interaction. A robust network of genes with no motifs can also be redefined as a network of interacting genes. Abstract: Perfect annealing between microRNAs (miRNAs) and messenger RNAs (mRNAs) was computationally searched at a broad scale in the human genome to determine whether theoretical pairing is restrictively represented in functional subnetworks or is randomly distributed. Massive RNA interference (RNAi) pairing motifs in genes constitute a remarkable subnetwork that displays highly genetically and biochemically interconnected genes. These analyses show unexpected repertoires of genes defined by their congruence in comatching with miRNAs at numerous sites and by their interconnection based on protein/protein interactions or proteins regulating the activity of others. This offers insights into the putatively coregulated homeostasis of large networks of genes by RNAi, whereas other networks seem to be independent of this regulatory mode. Genes accordingly defined by theoretical RNAi pairing cluster mainly in subnetworks related to cellular, metabolic and developmental processes and their regulation. Indeed, genes harboring numerous potential sites of hybridization with miRNAs are highly enriched with GO terms depicting the abovementioned processes and are grouped in a subnetwork of genes that are significantly more highly connected than they would be according to a random distribution. The significant number of interacting genes that present numerous potential comatches with miRNAs suggests that they may be under the control of the integrative and concerted action of multiple miRNAs.