Abstract
MicroRNAs (miRNAs) have recently been discovered as an important class of non-coding RNA genes that play a major role in regulating gene expression, providing a means to control the relative amounts of mRNA transcripts and their protein products. Although much work has been done in the genome-wide computational prediction of miRNA genes and their target mRNAs, two open questions are how miRNAs regulate gene expression and how to efficiently detect bona fide miRNA targets from a large number of candidate miRNA targets predicted by existing computational algorithms. In this paper, we present evidence that miRNAs function by post-transcriptional degradation of mRNA target transcripts: based on this, we propose a novel probabilistic model that accounts for gene expression using miRNA expression data and a set of candidate miRNA targets. A set of underlying miRNA targets are learned from the data using our algorithm, GenMiR (Generative model for miRNA regulation). Our model scores and detects 601 out of 1,770 targets obtained from TargetScanS in mouse at a false detection rate of 5%. Our high-confidence miRNA targets include several which have been previously validated by experiment: the remainder potentially represent a dramatic increase in the number of known miRNA targets.
An erratum to this chapter is available at http://dx.doi.org/10.1007/11732990_49.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Ambros, V.: The functions of animal microRNAs. Nature 431, 350–355 (2004)
Babak, T., Zhang, W., Morris, Q., Blencowe, B.J., Hughes, T.R.: Probing microRNAs with microarrays: Tissue specificity and functional inference. RNA 10, 1813–1819 (2004)
Bagga, S., et al.: Regulation by let-7 and lin-4 miRNAs results in target mRNA degradation. Cell 122, 553–563 (2005)
Bartel, D.P.: MicroRNAs: Genomics, biogenesis, mechanism, and function. Cell 116, 281–297 (2004)
Bentwich, I., et al.: Identification of hundreds of conserved and nonconserved human microRNAs. Nature Genetics 37, 766–770 (2005)
Berezikov, E., et al.: Phylogenetic shadowing and computational identification of human microRNA genes. Cell 120(1), 21–24 (2005)
Kent, W.J.: BLAT – The BLAST-Like Alignment Tool. Genome Research 4, 656–664 (2002)
Eddy, S.: Non-coding RNA genes and the modern RNA world. Nature Reviews Genetics 2, 919–929 (2001)
Frey, B.J., et al.: Genome-wide analysis of mouse transcripts using exon-resolution microarrays and factor graphs. Nature Genetics 37, 991–996 (2005)
Hartemink, A., Gifford, D., Jaakkola, T., Young, R.: Using graphical models and genomic expression data to statistically validate models of genetic regulatory networks. In: Proceedings of the Pacific Symposium on Biocomputing 2001, pp. 422–433. World Scientific, New Jersey (2001)
Huang, J.C., Morris, Q.D., Hughes, T.R., Frey, B.J.: GenXHC: A probabilistic generative model for cross-hybridization compensation in high-density, genome-wide microarray data. In: Proceedings of the Thirteenth Annual Conference on Intelligent Systems for Molecular Biology, June 25-29 (2005)
Hughes, T.R., et al.: Expression profiling using microarrays fabricated by an ink-jet oligonucleotide synthesizer. Nature Biotechnol. 19, 342–347 (2001)
John, B., et al.: Human MicroRNA targets. PLoS Biol. 2(11), e363 (2004)
Jordan, M.I., Ghahramani, Z., Jaakkola, T.S., Saul, L.K.: An introduction to variational methods for graphical models. Learning in Graphical Models. MIT Press, Cambridge (1999)
Kislinger, T., et al.: Global survey of organ and organelle protein expression in mouse: combined proteomic and transcriptomic profiling. Submitted to Cell (2005)
Krek, A., et al.: Combinatorial microRNA target predictions. Nature Genetics 37, 495–500 (2005)
Lewis, B.P., Burge, C.B., Bartel, D.P.: Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell 120, 15–20 (2005)
Lewis, B.P., et al.: Prediction of mammalian microRNA targets. Cell 115, 787–798 (2003)
Lim, L.P., et al.: The microRNAs of Caenorhabditis elegans. Genes Dev. 17, 991–1008 (2003)
Lim, L.P., et al.: Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs. Nature 433, 769–773 (2005)
Lockhart, M., et al.: Expression monitoring by hybridization to high-density oligonucleotide arrays. Nature Biotechnol. 14, 1675–1680 (1996)
Neal, R.M., Hinton, G.E.: A view of the EM algorithm that justifies incremental, sparse, and other variants. Learning in Graphical Models. Kluwer Academic Publishers, Dordrecht (1998)
Xie, X., et al.: Systematic discovery of regulatory motifs in human promoters and 3’ UTRs by comparison of several mammals. Nature 434, 338–345 (2005)
Zilberstein, C.B.Z., Ziv-Ukelson, M., Pinter, R.Y., Yakhini, Z.: A high-throughput approach for associating microRNAs with their activity conditions. In: Proceedings of the Ninth Annual Conference on Research in Computational Molecular Biology, May 14-18 (2005)
Zhang, W., Morris, Q., et al.: The functional landscape of mouse gene expression. J. Biol. 3, 21–43 (2004)
Supplemental Data for Lewis et al. Cell 120, 15-20, http://web.wi.mit.edu/bartel/pub/Supplemental%20Material/Lewis%20et%20al%202005%20Supp/
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Huang, J.C., Morris, Q.D., Frey, B.J. (2006). Detecting MicroRNA Targets by Linking Sequence, MicroRNA and Gene Expression Data. In: Apostolico, A., Guerra, C., Istrail, S., Pevzner, P.A., Waterman, M. (eds) Research in Computational Molecular Biology. RECOMB 2006. Lecture Notes in Computer Science(), vol 3909. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11732990_11
Download citation
DOI: https://doi.org/10.1007/11732990_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33295-4
Online ISBN: 978-3-540-33296-1
eBook Packages: Computer ScienceComputer Science (R0)