Recent studies have proven that microvesicles are a valuable source of biomarkers in a number of physiological and pathophysiological states. The molecular content of exosomes and other vesicles in general and their miRNA cargo in particular can act as a unique biomarker signature and help identifying releasing cells and their circumstances.
While knowledge of the extensive target repertoire of individual miRNAs greatly expanded our understanding of miRNA functions, the high resolution down to single nucleotide alterations enabled by Next Generation Sequencing added a whole new layer of complexity by detecting a great abundance of miRNA isoforms named isomiRs. Displaying significant sequence and length heterogeneity, isomiRs can change the mRNA targeting behaviour, either subtly through supplementary or complementary binding at the 3’ end, or drastically by altering the seed sequence at the 5’ end. By taking these target gene shifts into account and using a consensus of predicted genes that reflects actual miRNA sequence distribution and binding efficiencies, the accuracy of predicted pathways and related diseases is greatly improved. To realize this approach we implement these ideas in a ‘bioinformatical pipeline’ which analyses the small RNA sequencing read data files in a fully automatic way.
The assessment of mRNA targets can help discern the physiological relevance of identified miRNA biomarkers and even uncover novel relationships. We apply this ‘pipeline’ to discover new integrative mRNA/miRNA regulation pattern in agri-veterinary research and to predict new biomarker signatures in human clinical diagnostics.