GlycoMiR: Mapping the miRNA-glycogene interactome

Glycosylation is a highly-regulated dynamic process that alters during the course of normal physiology and can drive disease states. MicroRNAs (miRs) are small, non-coding RNAs that regulate the either the translation or stability of messenger RNA transcripts (mRNA) primarily via interactions with their 3'untranslated regions (3'-UTRs). In recent work, our laboratory identified miRs as key regulators of glycosylation. A major goal of the NIH Roadmap Initiative is to enable integration of glycosylation into genetic networks, such as miR-mRNA target networks, which are increasingly used to understand drivers of pathological conditions (e.g. schizophrenia, ovarian cancer) Glycosylation genes (glycogenes) are overlooked in models stemming from miR data due to: 1) the low accuracy of miR target predictions for miR:glycogene interactions in the available miR target databases. 2) the low abundance of glycogene transcripts, which causes them to be missed in many of the transcriptomic-based validations of miR networks. And 3) a lack of knowledge in the general biomedical community about glycosylation pathways and the relationship between glycosylation enzymes, glycan structures and appropriate structural probes. To address these hurdles, we propose GlycoMiR, a public database of validated miR:glycogene interactions hosted at VirtualGlycome.org Creation of GlycoMiR will entail experimental validation of miR:glycogene interactions utilizing high-throughput cell microarray technology. GlycoMiR will enable mining of miR datasets to identify miR-regulated glycosylation enzymes, aid researchers in mapping these glycogenes onto biosynthetic pathways and provide guidance for validating the impact of miRs on the glycome. GlycoMiR is designed for compatibility with other major tools in development for glycobioinformatics. Overall, GlycoMiR will enable the researchers outside the glyco-community to integrate glycosylation into their analysis of disease models from miR target networks, filling a gap inhibiting broader integration of glycoscience into biomedical research.