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      Global and Local Architecture of the Mammalian microRNA–Transcription Factor Regulatory Network

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          Abstract

          microRNAs (miRs) are small RNAs that regulate gene expression at the posttranscriptional level. It is anticipated that, in combination with transcription factors (TFs), they span a regulatory network that controls thousands of mammalian genes. Here we set out to uncover local and global architectural features of the mammalian miR regulatory network. Using evolutionarily conserved potential binding sites of miRs in human targets, and conserved binding sites of TFs in promoters, we uncovered two regulation networks. The first depicts combinatorial interactions between pairs of miRs with many shared targets. The network reveals several levels of hierarchy, whereby a few miRs interact with many other lowly connected miR partners. We revealed hundreds of “target hubs” genes, each potentially subject to massive regulation by dozens of miRs. Interestingly, many of these target hub genes are transcription regulators and they are often related to various developmental processes. The second network consists of miR–TF pairs that coregulate large sets of common targets. We discovered that the network consists of several recurring motifs. Most notably, in a significant fraction of the miR–TF coregulators the TF appears to regulate the miR, or to be regulated by the miR, forming a diversity of feed-forward loops. Together these findings provide new insights on the architecture of the combined transcriptional–post transcriptional regulatory network.

          Author Summary

          It is becoming increasingly appreciated that a new type of gene which does not code for proteins, the regulatory RNAs, constitutes a considerable portion of mammalian genomes, and these genes serve as key players in the regulatory network of living cells. Among these regulatory RNAs are the microRNAs (miRs), small RNAs that mediate posttranscriptional gene silencing through inhibition of protein production or degradation of mRNAs. So far little is known about the extent of regulation by miRs, and their potential cooperation with other regulatory layers in the network. We investigated the potential crosstalk between the miR-mediated posttranscription layer, and the transcriptional regulation layer, whose dominant players, the transcription factors (TFs), regulate the production of protein-coding mRNAs. We found that the extent of miR regulation varies extensively among different genes, some of which, especially those who serve as regulators themselves, are subject to enhanced miR silencing. Further, we identified thousands of genes that are potentially subjected to coordinated regulation by multiple miRs and by specific combinations of TFs and miRs. The regulatory network, comprising transcriptional and posttranscriptional regulation, manifests several recurring architectures, one of which consists of a TF and a miR that together regulate a large set of common genes, and that also appear to regulate one another. Altogether this work provides new insights into the logic and evolution of a new regulatory layer of the mammalian genome, and its effect on other regulatory networks in the cell.

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          Most cited references28

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          Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs.

          MicroRNAs (miRNAs) are a class of noncoding RNAs that post-transcriptionally regulate gene expression in plants and animals. To investigate the influence of miRNAs on transcript levels, we transfected miRNAs into human cells and used microarrays to examine changes in the messenger RNA profile. Here we show that delivering miR-124 causes the expression profile to shift towards that of brain, the organ in which miR-124 is preferentially expressed, whereas delivering miR-1 shifts the profile towards that of muscle, where miR-1 is preferentially expressed. In each case, about 100 messages were downregulated after 12 h. The 3' untranslated regions of these messages had a significant propensity to pair to the 5' region of the miRNA, as expected if many of these messages are the direct targets of the miRNAs. Our results suggest that metazoan miRNAs can reduce the levels of many of their target transcripts, not just the amount of protein deriving from these transcripts. Moreover, miR-1 and miR-124, and presumably other tissue-specific miRNAs, seem to downregulate a far greater number of targets than previously appreciated, thereby helping to define tissue-specific gene expression in humans.
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            Prediction of mammalian microRNA targets.

            MicroRNAs (miRNAs) can play important gene regulatory roles in nematodes, insects, and plants by basepairing to mRNAs to specify posttranscriptional repression of these messages. However, the mRNAs regulated by vertebrate miRNAs are all unknown. Here we predict more than 400 regulatory target genes for the conserved vertebrate miRNAs by identifying mRNAs with conserved pairing to the 5' region of the miRNA and evaluating the number and quality of these complementary sites. Rigorous tests using shuffled miRNA controls supported a majority of these predictions, with the fraction of false positives estimated at 31% for targets identified in human, mouse, and rat and 22% for targets identified in pufferfish as well as mammals. Eleven predicted targets (out of 15 tested) were supported experimentally using a HeLa cell reporter system. The predicted regulatory targets of mammalian miRNAs were enriched for genes involved in transcriptional regulation but also encompassed an unexpectedly broad range of other functions.
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              Network motifs in the transcriptional regulation network of Escherichia coli

              Little is known about the design principles of transcriptional regulation networks that control gene expression in cells. Recent advances in data collection and analysis, however, are generating unprecedented amounts of information about gene regulation networks. To understand these complex wiring diagrams, we sought to break down such networks into basic building blocks. We generalize the notion of motifs, widely used for sequence analysis, to the level of networks. We define 'network motifs' as patterns of interconnections that recur in many different parts of a network at frequencies much higher than those found in randomized networks. We applied new algorithms for systematically detecting network motifs to one of the best-characterized regulation networks, that of direct transcriptional interactions in Escherichia coli. We find that much of the network is composed of repeated appearances of three highly significant motifs. Each network motif has a specific function in determining gene expression, such as generating temporal expression programs and governing the responses to fluctuating external signals. The motif structure also allows an easily interpretable view of the entire known transcriptional network of the organism. This approach may help define the basic computational elements of other biological networks.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Comput Biol
                pcbi
                PLoS Computational Biology
                Public Library of Science (San Francisco, USA )
                1553-734X
                1553-7358
                July 2007
                13 July 2007
                : 3
                : 7
                : e131
                Affiliations
                [1 ] Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel
                [2 ] Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
                Washington University, United States of America
                Author notes
                * To whom correspondence should be addressed. E-mail: Pilpel@ 123456weizmann.ac.il
                Article
                06-PLCB-RA-0543R2 plcb-03-07-16
                10.1371/journal.pcbi.0030131
                1914371
                17630826
                91beb99a-0351-469c-8800-136a481c3d79
                Copyright: © 2007 Shalgi et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 27 December 2006
                : 22 May 2007
                Page count
                Pages: 14
                Categories
                Research Article
                Computational Biology
                Computational Biology
                Computational Biology
                Genetics and Genomics
                Homo (Human)
                Custom metadata
                Shalgi R, Lieber D, Oren M, Pilpel Y (2007) Global and local architecture of the mammalian microRNA–transcription factor regulatory network. PLoS Comput Biol 3(7): e131. doi: 10.1371/journal.pcbi.0030131

                Quantitative & Systems biology
                Quantitative & Systems biology

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