Validation of human microRNA target pathways enables evaluation of target prediction tools.

Fabian Kern,Tim Kehl,Ernesto Aparicio-Puerta,Caroline Diener,Hagen Von Briesen,Oliver Küchler,Tobias Fehlmann,Christina Backes,Hans-Peter Lenhof,Martin Hart,Karin Danz,Stefanie Rheinheimer,Eckart Meese,Mustafa Kahraman,Sylvia Wagner,Nicole Ludwig,Lena Krammes,Andreas Keller

doi:10.1093/nar/gkaa1161

Abstract

MicroRNAs are regulators of gene expression. A wide-spread, yet not validated, assumption is that the targetome of miRNAs is non-randomly distributed across the transcriptome and that targets share functional pathways. We developed a computational and experimental strategy termed high-throughput miRNA interaction reporter assay (HiTmIR) to facilitate the validation of target pathways. First, targets and target pathways are predicted and prioritized by computational means to increase the specificity and positive predictive value. Second, the novel webtool miRTaH facilitates guided designs of reporter assay constructs at scale. Third, automated and standardized reporter assays are performed. We evaluated HiTmIR using miR-34a-5p, for which TNF- and TGFB-signaling, and Parkinson's Disease (PD)-related categories were identified and repeated the pipeline for miR-7-5p. HiTmIR validated 58.9% of the target genes for miR-34a-5p and 46.7% for miR-7-5p. We confirmed the targeting by measuring the endogenous protein levels of targets in a neuronal cell model. The standardized positive and negative targets are collected in the new miRATBase database, representing a resource for training, or benchmarking new target predictors. Applied to 88 target predictors with different confidence scores, TargetScan 7.2 and miRanda outperformed other tools. Our experiments demonstrate the efficiency of HiTmIR and provide evidence for an orchestrated miRNA-gene targeting.

Highlights

MicroRNAs are small non coding RNAs, which regulate the gene expression post-transcriptionally [1]
Our high-throughput miRNA interaction reporter assay (HiTmIR) protocol, which was applied to two miRNAs, consists of three computational filters to increase the specificity of the target prediction and to reduce the size of the predicted targetome stepwise, followed by one experimental step (Figure 2A)
The validated target pathways as well as the positive and negative targets are stored in a data warehouse, miRATBase, a resource for testing and evaluating new target prediction tools

Summary

Introduction

MicroRNAs (miRNAs) are small non coding RNAs, which regulate the gene expression post-transcriptionally [1]. While miRNA gene targeting relies on a complementary binding of the seed region to the target gene, non-canonical binding between gene and miRNA seems to have a deterministic influence on the targeting process [11,12]. The limited understanding of the true complexity of the interactions between miRNAs and genes poses substantial challenges for the computational prediction of miRNA targets. In response to this challenge, many tools have been developed including TargetScan [13], PicTar [14], miRanda [15] and other consensus methods like miRWalk [16], which

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Results

Conclusion