Computational prediction of microRNA targets in vertebrates, fruitflies and nematodes

doi:10.1017/CBO9780511541766.015

12 - Computational prediction of microRNA targets in vertebrates, fruitflies and nematodes

from III - Computational biology of microRNAs

Published online by Cambridge University Press: 22 August 2009

Dominic Grün and

Nikolaus Rajewsky

Edited by

Krishnarao Appasani

Foreword by

Sidney Altman and

Victor R. Ambros

Show author details

Dominic Grün: Affiliation:
Center for Functional Comparative Genomics Department of Biology, NYU, 1009 Main Building 100 Washington Square East New York, NY 10003-6688 USA
Nikolaus Rajewsky: Affiliation:
Assistant Prof. of Biology and Mathematics New York University Center for Functional Comparative Genomics Department of Biology, NYU, 1009 Main Building 100 Washington Square East New York, NY 10003-6688 USA

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Summary

Introduction

MicroRNAs are a novel class of small endogenous non-coding RNAs, in their mature form typically of length 21–23 nt. They suppress protein production by binding to the mRNA of their target genes. The apparent fundamental role of microRNAs in nematode development, together with the outstanding degree of conservation of let-7, triggered large-scale searches for microRNAs in various organisms. In the order of at least 100–200 microRNAs per species have already been identified experimentally in C. elegans, D. melanogaster, D. rerio, M. musculus and H. sapiens, many of them being conserved over large evolutionary distances. Recent computational searches for microRNA genes in humans indicate that the true number of different microRNAs per species in mammals could exceed 500, including a substantial fraction of species or lineage specific microRNAs (Berezikov et al., 2005). After the discovery of hundreds of microRNAs in a variety of plants and animals this class of small non-coding RNAs turns out to be an important player in post-transcriptional gene regulation. Mature microRNAs display complex expression patterns during development and in adult tissues. Some were specifically expressed at high numbers, others appear to be expressed in almost all tissues (Barad et al., 2004; Baskerville and Bartel, 2005), suggesting substantial microRNA regulation in various physiological processes. The discovery and biogenesis of microRNAs is presented in other chapters of this book.

Type: Chapter
Information: MicroRNAs
From Basic Science to Disease Biology
, pp. 172 - 186

DOI: https://doi.org/10.1017/CBO9780511541766.015 [Opens in a new window]

Publisher: Cambridge University Press

Print publication year: 2007

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References

Barad, O., Meiri, E., Avniel, A.et al. (2004). MicroRNA expression detected by oligonucleotide microarrays: system establishment and expression profiling in human tissues. Genome Research, 14, 2486–2494.Google Scholar

Bartel, D. P. (2004). MicroRNAs: genomics, biogenesis, mechanism, and function. Cell, 116, 281–297.Google Scholar

Bartel, D. P. and Chen, C. Z. (2004). Micromanagers of gene expression:the potentially widespread influence of metazoan microRNAs. Nature Review Genetics, 5, 396–400.Google Scholar

Baskerville, S. and Bartel, D. P. (2005). Microarray profiling of microRNAs reveals frequent coexpression with neighboring miRNAs and host genes. RNA, 11, 241–247.Google Scholar

Berezikov, E., Guryev, V., Belt, J.et al. (2005). Phylogenetic shadowing and computational identification of human microRNA genes. Cell, 120, 21–24.Google Scholar

Brennecke, J., Stark, A., Russell, R. B. and Cohen, S. M. (2005). Principles of microRNA-target recognition. Public Library of Science Biology, 3, e85.Google Scholar

Burgler, C. and Macdonald, P. M. (2005). Prediction and verification of microRNA targets by MovingTargets, a highly adaptable prediction method. BMC Genomics, 6, 88.Google Scholar

Doench, J. G. and Sharp, P. A. (2004). Specificity of microRNA target selection in translational repression. Genes & Development, 18, 504–511.Google Scholar

Doench, J. G., Petersen, C. P. and Sharp, P. A. (2003). siRNAs can function as miRNAs. Genes & Development, 17, 438–442.Google Scholar

Enright, A. J., John, B., Gaul, U.et al. (2003). MicroRNA targets in Drosophila. Genome Biology, 5, R1.Google Scholar

Farh, K. K., Grimson, A., Jan, C.et al. (2005). The widespread impact of mammalian microRNAs on mRNA repression and evolution. Science, 310, 1817–1821.Google Scholar

Grün, D., Wang, Y. L., Langenberger, D., Gunsalus, K. C. and Rajewsky, N. (2005). microRN A target predictions across seven Drosophila species and comparison to mammalian targets. Public Library of Science Computational Biology, 1, e13.Google Scholar

Hobert, O. (2004). Common logic of transcription factor and microRNA action. Trends in Biochemical Sciences, 29, 462–468.Google Scholar

John, B., Enright, A. J., Aravin, A.et al. (2004). Human microRNA targets. Public Library of Science Biology, 2, e363.Google Scholar

Kiriakidou, M., Nelson, P. T., Kouranov, A.et al. (2004). A combined computational-experimental approach predicts human microRNA targets. Genes & Development, 18, 1165–1178.Google Scholar

Krek, A., Grün, D., Poy, M. N.et al. (2005). Combinatorial microRNA target predictions. Nature Genetics, 37, 495–500.Google Scholar

Krützfeld, J., Rajewsky, N., Braich, R.et al. (2005). Silencing of microRNAs in vivo with “antagomirs”. Nature, 438, 685–689.Google Scholar

Lai, E. C. (2002). Micro RNAs are complementary to 3′ UTR sequence motifs that mediate negative post-transcriptional regulation. Nature Genetics, 30, 363–364.Google Scholar

Lall, S., Grün, D., Krek, A.et al. (2006). A genome wide map of conserved microRNA targets in C. elegans. Current Biology, 16, 460–471.Google Scholar

Lewis, B. P., Shih, I. H., Jones-Rhoades, M. W., Bartel, D. P. and Burge, C. B. (2003). Prediction of mammalian microRNA targets. Cell, 115, 787–798.Google Scholar

Lewis, B. P., Burge, C. B., Bartel, D. P. (2005). Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell, 120, 15–20.Google Scholar

Lim, L. P., Lau, N. C., Garrett-Engele, P., Grimson, A. and Schelter, J. M. (2005). Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs. Nature, 433, 769–773.Google Scholar

Rajewsky, N. (2006). Computational microRNA target predictions in animals. Nature Genetics, 38, S8–13.Google Scholar

Rajewsky, N. and Socci, N. D. (2004). Computational identification of microRNA targets. Developmental Biology, 267, 529–535.Google Scholar

Rehmsmeier, M., Steffen, P., Hochsmann, M. and Giegerich, R. (2004). Fast and effective prediction of microRNA/target duplexes. RNA, 10, 1507–1517.Google Scholar

Robins, H., Li, Y. and Padgett, R. W. (2005). Incorporating structure to predict microRNA targets. Proceedings of the National Academy of Sciences USA, 102, 4006–4009.Google Scholar

Sood, P., Krek, A., Zavolan, M., Macino, G. and Rajewsky, N. (2005). Cell-type specific signatures of microRNAs on target mRNA expression. Proceedings of the National Academy of Sciences USA, 103, 2746–2751.Google Scholar

Stark, A., Brennecke, J., Russell, R. B. and Cohen, S. M. (2003). Identification of Drosophila microRNA targets. Public Library of Science Biology, 1, 397–409.Google Scholar

Stark, A., Brennecke, J., Bushati, N., Russell, R. B. and Cohen, S. M. (2005). Animal microRNAs confer robustness to gene expression and have a significant impact on 3′UTR evolution. Cell, 123, 1133–1146.Google Scholar

The Gene ontology Consortium (2000). Gene ontology: tool for the unification of biology. Nature Genetics, 25, 25–29.

Vella, M. C., Choi, E. Y., Lin, S. Y., Reinert, K. and Slack, F. J. (2004a). The C. elegans microRNA let-7 binds to imperfect complementary sites from the lin-41 3′UTR. Genes & Development, 18, 132–137.Google Scholar

Vella, M. C., Reinert, K. and Slack, F. J. (2004b). Architecture of a validated microRNA::target interaction. Chemistry & Biology, 11, 1619–1623.Google Scholar

Wightman, B., Ha, I. and Ruvkun, G. (1993). Posttranscriptional regulation of the heterochronic gene lin-14 by lin-4 mediates temporal pattern formation in C. elegans. Cell, 75, 855–862.Google Scholar

Xie, X., Kulbokas, E. J., Golub, T. R.et al. (2005). Systematic discovery of regulatory motifs in human promoters and 3′ UTRs by comparison of several mammals. Nature, 434, 338–345.Google Scholar

Zhao, Y., Samal, E. and Srivastava, D. (2005). Serum response factor regulates a muscle-specific microRNA that targets Hand2 during cardiogenesis. Nature, 436, 214–220.Google Scholar