Abstract
MicroRNAs (miRNAs) have been implicated in virtually every metazoan biological process, exerting a widespread impact on gene expression. MicroRNA repression is conferred by relatively short “seed match” sequences, although the degree of repression varies widely for individual target sites. The factors controlling whether, and to what extent, a target site is repressed are not fully understood. As an alternative to target prediction based on sequence alone, comparative genomics has emerged as an invaluable tool for identifying miRNA targets that are conserved by natural selection, and hence likely effective and important. Here we present a general method for quantifying conservation of miRNA seed match sites, separating it from background conservation, controlling for various biases, and predicting miRNA targets. This method is useful not only for generating predictions but also as a tool for empirically evaluating the importance of various target prediction criteria.
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Acknowledgements
The TargetScan algorithm described was co-developed with David P. Bartel and was based on work by Kyle Kai-How Farh. The authors thank David Bartel and Vikram Agarwal for helpful discussions and the US Department of Energy Office of Science for funding the development of this algorithm.
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Friedman, R.C., Burge, C.B. (2014). MicroRNA Target Finding by Comparative Genomics. In: Gorodkin, J., Ruzzo, W. (eds) RNA Sequence, Structure, and Function: Computational and Bioinformatic Methods. Methods in Molecular Biology, vol 1097. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-62703-709-9_21
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DOI: https://doi.org/10.1007/978-1-62703-709-9_21
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