A quantitative understanding of microRNA- mediated competing endogenous RNA regulation

Abstract

MicroRNA (miRNA) plays key roles in post-transcriptional regulations. Recently, a competing endogenous RNA (ceRNA) hypothesis has been proposed that miRNA targets could communicate and regulate each other through titrating shared miRNAs, which provides a new layer of gene regulation. Though a number of ceRNAs playing biological functions have been identified, the ceRNA hypothesis remains controversial. Recent experimental and theoretical studies argued that the modulation of a single RNA species could hardly change the expression level of competing miRNA targets through ceRNA effect under normal physiological conditions. Here, we reviewed a common framework to model miRNA regulations, and summarized the current theoretical and experimental studies for quantitative understanding ceRNA effect. By revisiting a coarse-grained ceRNA model, we proposed that network topology could significantly influence the competing effect and ceRNA regulation at protein level could be much stronger than that at RNA level. We also provided a conditional independent binding equation to describe miRNA relative repression on different target, which could be applied to quantify siRNA off-target effect.

Graphical abstract

Keywords

microRNA regulation / competing endogenous RNA / molecular titration / quantitative model / complex networks

References

[1] He, L. and Hannon, G. J. (2004) MicroRNAs: small RNAs with a big role in gene regulation. Nat. Rev. Genet., 5, 522–531

[2] Fire, A., Xu, S., Montgomery, M. K., Kostas, S. A., Driver, S. E. and Mello, C. C. (1998) Potent and specific genetic interference by double-stranded RNA in Caenorhabditis elegans. Nature, 391, 806–811

[3] Wee, L. M., Flores-Jasso, C. F., Salomon, W. E. and Zamore, P. D. (2012) Argonaute divides its RNA guide into domains with distinct functions and RNA-binding properties. Cell, 151, 1055–1067

[4] Zamore, P. D., Tuschl, T., Sharp, P. A. and Bartel, D. P. (2000) RNAi: double-stranded RNA directs the ATP-dependent cleavage of mRNA at 21 to 23 nucleotide intervals. Cell, 101, 25–33

[5] Bartel, D. P. (2009) MicroRNAs: target recognition and regulatory functions. Cell, 136, 215–233

[6] Hutvágner, G. and Zamore, P. D. (2002) A microRNA in a multiple-turnover RNAi enzyme complex. Science, 297, 2056–2060

[7] Agarwal, V., Bell, G. W., Nam, J. W. and Bartel, D. P. (2015) Predicting effective microRNA target sites in mammalian mRNAs. Elife, 4, 4

[8] Krek, A., Grün, D., Poy, M. N., Wolf, R., Rosenberg, L., Epstein, E. J., MacMenamin, P., da Piedade, I., Gunsalus, K. C., Stoffel, M., (2005) Combinatorial microRNA target predictions. Nat. Genet., 37, 495–500

[9] Kertesz, M., Iovino, N., Unnerstall, U., Gaul, U. and Segal, E. (2007) The role of site accessibility in microRNA target recognition. Nat. Genet., 39, 1278–1284

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

[11] Jens, M. and Rajewsky, N. (2015) Competition between target sites of regulators shapes post-transcriptional gene regulation. Nat. Rev. Genet., 16, 113–126

[12] Allantaz, F., Cheng, D. T., Bergauer, T., Ravindran, P., Rossier, M. F., Ebeling, M., Badi, L., Reis, B., Bitter, H., D’Asaro, M., (2012) Expression profiling of human immune cell subsets identifies miRNA-mRNA regulatory relationships correlated with cell type specific expression. PLoS One, 7, e29979

[13] Cajigas, I. J., Tushev, G., Will, T. J., tom Dieck, S., Fuerst, N. and Schuman, E. M. (2012) The local transcriptome in the synaptic neuropil revealed by deep sequencing and high-resolution imaging. Neuron, 74, 453–466

[14] Gennarino, V. A., Sardiello, M., Avellino, R., Meola, N., Maselli, V., Anand, S., Cutillo, L., Ballabio, A. and Banfi, S. (2009) MicroRNA target prediction by expression analysis of host genes. Genome Res., 19, 481–490

[15] Jung, D., Kim, B., Freishtat, R. J., Giri, M., Hoffman, E. and Seo, J. (2015) miRTarVis: an interactive visual analysis tool for microRNA-mRNA expression profile data. BMC Proc, 9, S2

[16] Xie, P., Liu, Y., Li, Y., Zhang, M. Q. and Wang, X. (2014) MIROR: a method for cell-type specific microRNA occupancy rate prediction. Mol Biosyst, 10, 1377–1384

[17] Salmena, L., Poliseno, L., Tay, Y., Kats, L. and Pandolfi, P. P. (2011) A ceRNA hypothesis: the Rosetta Stone of a hidden RNA language? Cell, 146, 353–358

[18] Tay, Y., Rinn, J. and Pandolfi, P. P. (2014) The multilayered complexity of ceRNA crosstalk and competition. Nature, 505, 344–352

[19] Taulli, R., Loretelli, C. and Pandolfi, P. P. (2013) From pseudo-ceRNAs to circ-ceRNAs: a tale of cross-talk and competition. Nat. Struct. Mol. Biol., 20, 541–543

[20] Cesana, M., Cacchiarelli, D., Legnini, I., Santini, T., Sthandier, O., Chinappi, M., Tramontano, A. and Bozzoni, I. (2011) A long noncoding RNA controls muscle differentiation by functioning as a competing endogenous RNA. Cell, 147, 358–369

[21] Karreth, F. A., Tay, Y., Perna, D., Ala, U., Tan, S. M., Rust, A. G., DeNicola, G., Webster, K. A., Weiss, D., Perez-Mancera, P. A., (2011) In vivo identification of tumor- suppressive PTEN ceRNAs in an oncogenic BRAF-induced mouse model of melanoma. Cell, 147, 382–395

[22] Sumazin, P., Yang, X., Chiu, H. S., Chung, W. J., Iyer, A., Llobet-Navas, D., Rajbhandari, P., Bansal, M., Guarnieri, P., Silva, J., (2011) An extensive microRNA-mediated network of RNA-RNA interactions regulates established oncogenic pathways in glioblastoma. Cell, 147, 370–381

[23] Tay, Y., Kats, L., Salmena, L., Weiss, D., Tan, S. M., Ala, U., Karreth, F., Poliseno, L., Provero, P., Di Cunto, F., (2011) Coding-independent regulation of the tumor suppressor PTEN by competing endogenous mRNAs. Cell, 147, 344–357

[24] Memczak, S., Jens, M., Elefsinioti, A., Torti, F., Krueger, J., Rybak, A., Maier, L., Mackowiak, S. D., Gregersen, L. H., Munschauer, M., (2013) Circular RNAs are a large class of animal RNAs with regulatory potency. Nature, 495, 333–338

[25] Kumar, M. S., Armenteros-Monterroso, E., East, P., Chakravorty, P., Matthews, N., Winslow, M. M. and Downward, J. (2014) HMGA2 functions as a competing endogenous RNA to promote lung cancer progression. Nature, 505, 212–217

[26] Peng, H., Lu, M. and Selaru, F. M. (2015) The genome-wide gene expression profiling to predict competitive endogenous RNA network in hepatocellular cancer. Genom Data, 4, 93–95

[27] Qi, X., Zhang, D. H., Wu, N., Xiao, J. H., Wang, X. and Ma, W. (2015) ceRNA in cancer: possible functions and clinical implications. J. Med. Genet., 52, 710–718

[28] Zhang, J., Fan, D., Jian, Z., Chen, G. G. and Lai, P. B. (2015) Cancer specific long noncoding RNAs show differential expression patterns and competing endogenous RNA potential in hepatocellular carcinoma. PLoS One, 10, e0141042

[29] Bosson, A. D., Zamudio, J. R. and Sharp, P. A. (2014) Endogenous miRNA and target concentrations determine susceptibility to potential ceRNA competition. Mol. Cell, 56, 347–359

[30] Mayya, V. K. and Duchaine, T. F. (2015) On the availability of microRNA-induced silencing complexes, saturation of microRNA-binding sites and stoichiometry. Nucleic Acids Res., 43, 7556–7565

[31] Yuan, Y., Liu, B., Xie, P., Zhang, M. Q., Li, Y., Xie, Z. and Wang, X. (2015) Model-guided quantitative analysis of microRNA-mediated regulation on competing endogenous RNAs using a synthetic gene circuit. Proc. Natl. Acad. Sci. USA, 112, 3158–3163

[32] Denzler, R., Agarwal, V., Stefano, J., Bartel, D. P. and Stoffel, M. (2014) Assessing the ceRNA hypothesis with quantitative measurements of miRNA and target abundance. Mol. Cell, 54, 766–776

[33] Hausser, J. and Zavolan, M. (2014) Identification and consequences of miRNA-target interactions—beyond repression of gene expression. Nat. Rev. Genet., 15, 599–612

[34] Lim, L. P., Lau, N. C., Garrett-Engele, P., Grimson, A., Schelter, J. M., Castle, J., Bartel, D. P., Linsley, P. S. and Johnson, J. M. (2005) Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs. Nature, 433, 769–773

[35] Kou, Y., Qiao, L. and Wang, Q. (2015) Identification of core miRNA based on small RNA-seq and RNA-seq for colorectal cancer by bioinformatics. Tumour Biol., 36, 2249–2255

[36] Wang, Z., Gerstein, M. and Snyder, M. (2009) RNA-Seq: a revolutionary tool for transcriptomics. Nat. Rev. Genet., 10, 57–63

[37] Bazzini, A. A., Lee, M. T. and Giraldez, A. J. (2012) Ribosome profiling shows that miR-430 reduces translation before causing mRNA decay in zebrafish. Science, 336, 233–237

[38] Baek, D., Villén, J., Shin, C., Camargo, F. D., Gygi, S. P. and Bartel, D. P. (2008) The impact of microRNAs on protein output. Nature, 455, 64–71

[39] Hausser, J., Syed, A. P., Selevsek, N., van Nimwegen, E., Jaskiewicz, L., Aebersold, R. and Zavolan, M. (2013) Timescales and bottlenecks in miRNA-dependent gene regulation. Mol. Syst. Biol., 9, 711.

[40] Selbach, M., Schwanhäusser, B., Thierfelder, N., Fang, Z., Khanin, R. and Rajewsky, N. (2008) Widespread changes in protein synthesis induced by microRNAs. Nature, 455, 58–63

[41] Broughton, J. P. and Pasquinelli, A. E. (2013) Identifying Argonaute binding sites in Caenorhabditis elegans using iCLIP. Methods, 63, 119–125

[42] Chi, S. W., Zang, J. B., Mele, A. and Darnell, R. B. (2009) Argonaute HITS-CLIP decodes microRNA-mRNA interaction maps. Nature, 460, 479–486

[43] Konig, J., Zarnack, K., Rot, G., Curk, T., Kayikci, M., Zupan, B., Turner, D. J., Luscombe, N. M. and Ule, J. (2011) iCLIP—transcriptome-wide mapping of protein-RNA interactions with individual nucleotide resolution. J. Vis. Exp., e2638

[44] Loeb, G. B., Khan, A. A., Canner, D., Hiatt, J. B., Shendure, J., Darnell, R. B., Leslie, C. S. and Rudensky, A. Y. (2012) Transcriptome-wide miR-155 binding map reveals widespread noncanonical microRNA targeting. Mol. Cell, 48, 760–770

[45] Sutandy, F. X., Hildebrandt, A. and König, J. (2016) Profiling the binding sites of RNA-binding proteins with nucleotide resolution using iCLIP. Methods Mol. Biol., 1358, 175–195

[46] Zisoulis, D. G., Lovci, M. T., Wilbert, M. L., Hutt, K. R., Liang, T. Y., Pasquinelli, A. E. and Yeo, G. W. (2010) Comprehensive discovery of endogenous Argonaute binding sites in Caenorhabditis elegans. Nat. Struct. Mol. Biol., 17, 173–179

[47] Kishore, S., Jaskiewicz, L., Burger, L., Hausser, J., Khorshid, M. and Zavolan, M. (2011) A quantitative analysis of CLIP methods for identifying binding sites of RNA-binding proteins. Nat. Methods, 8, 559–564

[48] Zhang, C. and Darnell, R. B. (2011) Mapping in vivo protein-RNA interactions at single-nucleotide resolution from HITS-CLIP data. Nat. Biotechnol., 29, 607–614

[49] Levine, E., Zhang, Z., Kuhlman, T. and Hwa, T. (2007) Quantitative characteristics of gene regulation by small RNA. PLoS Biol., 5, e229.

[50] Mukherji, S., Ebert, M. S., Zheng, G. X., Tsang, J. S., Sharp, P. A. and van Oudenaarden, A. (2011) MicroRNAs can generate thresholds in target gene expression. Nat. Genet., 43, 854–859

[51] Schmiedel, J. M., Klemm, S. L., Zheng, Y., Sahay, A., Blüthgen, N., Marks, D. S. and van Oudenaarden, A. (2015) MicroRNA control of protein expression noise. Science, 348, 128–132

[52] Milo, R., Jorgensen, P., Moran, U., Weber, G. and Springer, M. (2010) BioNumbers—the database of key numbers in molecular and cell biology. Nucleic Acids Res., 38, D750–D753

[53] Schwanhäusser, B., Busse, D., Li, N., Dittmar, G., Schuchhardt, J., Wolf, J., Chen, W. and Selbach, M. (2011) Global quantification of mammalian gene expression control. Nature, 473, 337–342

[54] Buchler, N. E. and Louis, M. (2008) Molecular titration and ultrasensitivity in regulatory networks. J. Mol. Biol., 384, 1106–1119

[55] Ala, U., Karreth, F. A., Bosia, C., Pagnani, A., Taulli, R., Léopold, V., Tay, Y., Provero, P., Zecchina, R. and Pandolfi, P. P. (2013) Integrated transcriptional and competitive endogenous RNA networks are cross-regulated in permissive molecular environments. Proc. Natl. Acad. Sci. USA, 110, 7154–7159

[56] Martinez, N. J. and Gregory, R. I. (2013) Argonaute2 expression is post-transcriptionally coupled to microRNA abundance. RNA, 19, 605–612

[57] Wang, D., Zhang, Z., O’Loughlin, E., Lee, T., Houel, S., O’Carroll, D., Tarakhovsky, A., Ahn, N. G. and Yi, R. (2012) Quantitative functions of Argonaute proteins in mammalian development. Genes Dev., 26, 693–704

[58] Riba, A., Bosia, C., El Baroudi, M., Ollino, L. and Caselle, M. (2014) A combination of transcriptional and microRNA regulation improves the stability of the relative concentrations of target genes. PLoS Comput. Biol., 10, e1003490.

[59] Poliseno, L., Salmena, L., Zhang, J., Carver, B., Haveman, W. J. and Pandolfi, P. P. (2010) A coding-independent function of gene and pseudogene mRNAs regulates tumour biology. Nature, 465, 1033–1038

[60] Figliuzzi, M., Marinari, E. and De Martino, A. (2013) MicroRNAs as a selective channel of communication between competing RNAs: a steady-state theory. Biophys. J., 104, 1203–1213

[61] Nitzan, M., Steiman-Shimony, A., Altuvia, Y., Biham, O. and Margalit, H. (2014) Interactions between distant ceRNAs in regulatory networks. Biophys. J., 106, 2254–2266

[62] Noorbakhsh, J., Lang, A. H. and Mehta, P. (2013) Intrinsic noise of microRNA-regulated genes and the ceRNA hypothesis. PLoS One, 8, e72676

[63] Wang, P., Zhi, H., Zhang, Y., Liu, Y., Zhang, J., Gao, Y., Guo, M., Ning, S. and Li, X. (2015) miRSponge: a manually curated database for experimentally supported miRNA sponges and ceRNAs. Database (Oxford), 2015, 2015

[64] Yu, G., Yao, W., Gumireddy, K., Li, A., Wang, J., Xiao, W., Chen, K., Xiao, H., Li, H., Tang, K., (2014) Pseudogene PTENP1 functions as a competing endogenous RNA to suppress clear-cell renal cell carcinoma progression. Mol. Cancer Ther., 13, 3086–3097

[65] Jeyapalan, Z., Deng, Z., Shatseva, T., Fang, L., He, C. and Yang, B. B. (2011) Expression of CD44 3′-untranslated region regulates endogenous microRNA functions in tumorigenesis and angiogenesis. Nucleic Acids Res., 39, 3026–3041

[66] Rutnam, Z. J. and Yang, B. B. (2012) The non-coding 3′ UTR of CD44 induces metastasis by regulating extracellular matrix functions. J. Cell. Sci., 125, 2075–2085

[67] Xia, T., Chen, S., Jiang, Z., Shao, Y., Jiang, X., Li, P., Xiao, B. and Guo, J. (2015) Long noncoding RNA FER1L4 suppresses cancer cell growth by acting as a competing endogenous RNA and regulating PTEN expression. Sci Rep, 5, 13445

[68] Jackson, A. L., Burchard, J., Schelter, J., Chau, B. N., Cleary, M., Lim, L. and Linsley, P. S. (2006) Widespread siRNA “off-target” transcript silencing mediated by seed region sequence complementarity. RNA, 12, 1179–1187

[69] Schafer, S., Adami, E., Heinig, M., Rodrigues, K. E., Kreuchwig, F., Silhavy, J., van Heesch, S., Simaite, D., Rajewsky, N., Cuppen, E., (2015) Translational regulation shapes the molecular landscape of complex disease phenotypes. Nat Commun, 6, 7200

[70] Jiang, J., Wakimoto, H., Seidman, J. G. and Seidman, C. E. (2013) Allele-specific silencing of mutant Myh6 transcripts in mice suppresses hypertrophic cardiomyopathy. Science, 342, 111–114

[71] Chiu, H. S., Llobet-Navas, D., Yang, X., Chung, W. J., Ambesi-Impiombato, A., Iyer, A., Kim, H. R., Seviour, E. G., Luo, Z., Sehgal, V., (2015) Cupid: simultaneous reconstruction of microRNA-target and ceRNA networks. Genome Res., 25, 257–267

[72] Tan, J. Y., Sirey, T., Honti, F., Graham, B., Piovesan, A., Merkenschlager, M., Webber, C., Ponting, C. P. and Marques, A. C. (2015) Extensive microRNA-mediated crosstalk between lncRNAs and mRNAs in mouse embryonic stem cells. Genome Res., 25, 655–666

[73] Xu, J., Li, Y., Lu, J., Pan, T., Ding, N., Wang, Z., Shao, T., Zhang, J., Wang, L. and Li, X. (2015) The mRNA related ceRNA-ceRNA landscape and significance across 20 major cancer types. Nucleic Acids Res., 43, 8169–8182

ACKNOWLEDMENTS

This work was supported by the National Basic Research Program (No. 2012CB316503), the National Natural Science Foundation (Nos. 61322310 and 31371341), Tsinghua University Initiative Scientific Research Program, and Tsinghua National Laboratory for Information Science and Technology.

The authors Ye Yuan, Xinying Ren, Zhen Xie and Xiaowo Wang declare that they have no conflict of interest.

This article does not contain any studies with human or animal subjects performed by any of the authors.

Funding

RIGHTS & PERMISSIONS

2014 Higher Education Press and Springer-Verlag Berlin Heidelberg