Letter

Combinatorial microRNA target predictions

Received:
Accepted:
Published online:

Abstract

MicroRNAs are small noncoding RNAs that recognize and bind to partially complementary sites in the 3′ untranslated regions of target genes in animals and, by unknown mechanisms, regulate protein production of the target transcript1,2,3. Different combinations of microRNAs are expressed in different cell types and may coordinately regulate cell-specific target genes. Here, we present PicTar, a computational method for identifying common targets of microRNAs. Statistical tests using genome-wide alignments of eight vertebrate genomes, PicTar's ability to specifically recover published microRNA targets, and experimental validation of seven predicted targets suggest that PicTar has an excellent success rate in predicting targets for single microRNAs and for combinations of microRNAs. We find that vertebrate microRNAs target, on average, roughly 200 transcripts each. Furthermore, our results suggest widespread coordinate control executed by microRNAs. In particular, we experimentally validate common regulation of Mtpn by miR-375, miR-124 and let-7b and thus provide evidence for coordinate microRNA control in mammals.

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Acknowledgements

We thank V. Miljkovic and S. Pueblas for preparing figures for the manuscript. N. Rajewsky thanks T. Tuschl, P. Macino and F. Piano for discussions. This project was funded in part by a grant from the US National Institutes of Health (to M.S.). D.G. acknowledges a scholarship by the German Academic Exchange Service. K.C.G. and P.M. were supported by grants from the US National Institutes of Health (to F. Píaro) and the US National Science Foundation (to K.C.G.). This research was supported in part by the Howard Hughes Medical Institute grant through the Undergraduate Biological Sciences Education Program to New York University.

Author information

Author notes

    • Azra Krek
    • , Dominic Grün
    •  & Matthew N Poy

    These authors contributed equally to this work.

Affiliations

  1. Center for Comparative Functional Genomics, Department of Biology, New York University, 100 Washington Square East, New York, New York 10003, USA.

    • Azra Krek
    • , Dominic Grün
    • , Rachel Wolf
    • , Lauren Rosenberg
    • , Philip MacMenamin
    • , Isabelle da Piedade
    • , Kristin C Gunsalus
    •  & Nikolaus Rajewsky
  2. Department of Physics, New York University, New York, New York 10003, USA.

    • Azra Krek
  3. Laboratory of Metabolic Diseases, The Rockefeller University, New York, New York 10021, USA.

    • Matthew N Poy
    • , Eric J Epstein
    •  & Markus Stoffel

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Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Nikolaus Rajewsky.

Supplementary information

Excel files

  1. 1.

    Supplementary Table 1

    Set of 58 unique microRNAs conserved in human/chimp/mouse/rat/dog/chicken.

  2. 2.

    Supplementary Table 2

    Predictions for single microRNA targets based on conservation in human/chimp/mouse/rat/dog/chicken.

  3. 3.

    Supplementary Table 3

    Predictions for single microRNA targets based on conservation in human/chimp/mouse/rat/dog.

  4. 4.

    Supplementary Table 4

    Predictions for combinatorially targeted transcripts in four different tissues for sets of co-expressed microRNAs.

PDF files

  1. 1.

    Supplementary Note

    Detailed description of the PicTar probabilistic scoring method.

  2. 2.

    Supplementary Methods

    The nematode sequence datasets, evolutionary conservation check and testing the quality of vertebrate alignments.