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Detecting microRNA binding and siRNA off-target effects from expression data

Abstract

Sylamer is a method for detecting microRNA target and small interfering RNA off-target signals in 3′ untranslated regions from a ranked gene list, sorted from upregulated to downregulated, after a microRNA perturbation or RNA interference experiment. The output is a landscape plot that tracks occurrence biases using hypergeometric P-values for all words across the gene ranking. We demonstrated the utility, speed and accuracy of this approach on several datasets.

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Figure 1: Mouse miR-155 knockout experiment.
Figure 2: Human RNAi off-target analysis.

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Acknowledgements

We thank R. Grocock, W. Khong, H. Saini, S. Manakov, J. van Helden, A. Giraldez and W. Huber for useful discussions. This work was supported by the Wellcome Trust.

Author information

Authors and Affiliations

Authors

Contributions

S.v.D., C.A.-G. and A.J.E. conceived and designed the method. S.v.D. implemented the method. C.A.-G. and S.v.D. perfomed the analyses and validation experiments. S.v.D., C.A.-G. and A.J.E. wrote the manuscript.

Corresponding author

Correspondence to Anton J Enright.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–6, Supplementary Discussion, Supplementary Methods (PDF 7562 kb)

Supplementary Data 1

miR-155 genelists and sequences (ZIP 6555 kb)

Supplementary Data 2

miR-430 genelists and sequences (ZIP 1884 kb)

Supplementary Data 3

siRNA genelists and sequences (ZIP 8595 kb)

Supplementary Software

Sylamer source-code, binaries and JAVA interface (ZIP 9834 kb)

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van Dongen, S., Abreu-Goodger, C. & Enright, A. Detecting microRNA binding and siRNA off-target effects from expression data. Nat Methods 5, 1023–1025 (2008). https://doi.org/10.1038/nmeth.1267

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