MicroRNA transfection and AGO-bound CLIP-seq data sets reveal distinct determinants of miRNA action

  1. Anders Krogh1
  1. 1The Bioinformatics Centre, Department of Biology, University of Copenhagen, Ole Maaloes Vej 5, 2200 Copenhagen N, Denmark
  2. 2The Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Ole Maaloes Vej 5, 2200 Copenhagen N, Denmark
  1. 3 These authors contributed equally to this work.

Abstract

Microarray expression analyses following miRNA transfection/inhibition and, more recently, Argonaute cross-linked immunoprecipitation (CLIP)-seq assays have been used to detect miRNA target sites. CLIP and expression approaches measure differing stages of miRNA functioning—initial binding of the miRNP complex and subsequent message repression. We use nonparametric predictive models to characterize a large number of known target and flanking features, utilizing miRNA transfection, HITS-CLIP, and PAR-CLIP data. In particular, we utilize the precise spatial information provided by CLIP-seq to analyze the predictive effect of target flanking features. We observe distinct target determinants between expression-based and CLIP-based data. Target flanking features such as flanking region conservation are an important AGO-binding determinant—we hypothesize that CLIP experiments have a preference for strongly bound miRNP–target interactions involving adjacent RNA-binding proteins that increase the strength of cross-linking. In contrast, seed-related features are major determinants in expression-based studies, but less so for CLIP-seq studies, and increased miRNA concentrations typical of transfection studies contribute to this difference. While there is a good overlap between miRNA targets detected by miRNA transfection and CLIP-seq, the detection of CLIP-seq targets is largely independent of the level of subsequent mRNA degradation. Also, models built using CLIP-seq data show strong predictive power between independent CLIP-seq data sets, but are not strongly predictive for expression change. Similarly, models built from expression data are not strongly predictive for CLIP-seq data sets, supporting the finding that the determinants of miRNA binding and mRNA degradation differ. Predictive models and results are available at http://servers.binf.ku.dk/antar/.

Keywords

Footnotes

  • Reprint requests to: Anders Krogh, The Bioinformatics Centre, Department of Biology, University of Copenhagen, Ole Maaloes Vej 5, 2200 Copenhagen N, Denmark; e-mail: krogh{at}binf.ku.dk.

  • Article published online ahead of print. Article and publication date are at http://www.rnajournal.org/cgi/doi/10.1261/rna.2387911.

  • Received July 24, 2010.
  • Accepted January 20, 2011.
| Table of Contents