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

Validation of human microRNA target pathways enables evaluation of target prediction tools. Kern, F., Krammes, L., Danz, K., Diener, C., Kehl, T., Küchler, O., Fehlmann, T., Kahraman, M., Rheinheimer, S., Aparicio-Puerta, E., Wagner, S., Ludwig, N., Backes, C., Lenhof, H., von Briesen , H., Hart, M., Keller, A., & Meese, E. Nucleic Acids Research, 12, 2020.

Paper doi abstract bibtex

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.

@article{10.1093/nar/gkaa1161,
    author = {Kern, Fabian and Krammes, Lena and Danz, Karin and Diener, Caroline and Kehl, Tim and Küchler, Oliver and Fehlmann, Tobias and Kahraman, Mustafa and Rheinheimer, Stefanie and Aparicio-Puerta, Ernesto and Wagner, Sylvia and Ludwig, Nicole and Backes, Christina and Lenhof, Hans-Peter and von Briesen, Hagen and Hart, Martin and Keller, Andreas and Meese, Eckart},
    title = "{Validation of human microRNA target pathways enables evaluation of target prediction tools}",
    journal = {Nucleic Acids Research},
    year = {2020},
    month = {12},
    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.}",
    issn = {0305-1048},
    doi = {10.1093/nar/gkaa1161},
    url = {https://doi.org/10.1093/nar/gkaa1161},
}

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