MiRVaS: A tool to predict the impact of genetic variants on miRNAs

Abstract

Genetic variants in or near miRNA genes can have profound effects on miRNA expression and targeting. As user-friendly software for the impact prediction of miRNA variants on a large scale is still lacking, we created a tool called miRVaS. miRVaS automates this prediction by annotating the location of the variant relative to functional regions within the miRNA hairpin (seed, mature, loop, hairpin arm, flanks) and by annotating all predicted structural changes within the miRNA due to the variant. In addition, the tool defines the most important region that is predicted to have structural changes and calculates a conservation score that is indicative of the reliability of the structure prediction. The output is presented in a tabseparated file, which enables fast screening, and in an HTML file, which allows visual comparison between wild- Type and variant structures. All separate images are provided for downstream use. Finally, we tested two different approaches on a small test set of published functionally validated genetic variants for their capacity to predict the impact of variants on miRNA expression.