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Journal Article

Principles of microRNA Regulation Revealed Through Modeling microRNA Expression

MPS-Authors

Budach,  Stefan
RNA Bioinformatics (Annalisa Marsico), Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Marsico,  Annalisa
RNA Bioinformatics (Annalisa Marsico), Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society;
High Throughput Genomics, Department of Mathematics and Computer Science, Freie Universität Berlin, 14195 Berlin, Germany.;

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Citation

Budach, S., Heinig, M., & Marsico, A. (2016). Principles of microRNA Regulation Revealed Through Modeling microRNA Expression. Genetics, 203(4), 1629-1640. doi:10.1534/genetics.116.187153.


Cite as: http://hdl.handle.net/11858/00-001M-0000-002D-4D49-8
Abstract
Extensive work has been dedicated to study mechanisms of microRNA-mediated gene regulation. However, the transcriptional regulation of microRNAs themselves is far less well understood, due to difficulties determining the transcription start sites of transient primary transcripts. This challenge can be addressed using expression quantitative trait loci (eQTLs) whose regulatory effects represent a natural source of perturbation of cis-regulatory elements. Here we used previously published cis-microRNA-eQTL data for the human GM12878 cell line, promoter predictions, and other functional annotations to determine the relationship between functional elements and microRNA regulation. We built a logistic regression model that classifies microRNA/SNP pairs into eQTLs or non-eQTLs with 85% accuracy; shows microRNA-eQTL enrichment for microRNA precursors, promoters, enhancers, and transcription factor binding sites; and depletion for repressed chromatin. Interestingly, although there is a large overlap between microRNA eQTLs and messenger RNA eQTLs of host genes, 74% of these shared eQTLs affect microRNA and host expression independently. Considering microRNA-only eQTLs we find a significant enrichment for intronic promoters, validating the existence of alternative promoters for intragenic microRNAs. Finally, in line with the GM12878 cell line derived from B cells, we find genome-wide association (GWA) variants associated to blood-related traits more likely to be microRNA eQTLs than random GWA and non-GWA variants, aiding the interpretation of GWA results.