MixMir: Microrna motif discovery from gene expression data using mixed linear models

Nucleic Acids Research

Volumn 42, Issue 17, 2014, Pages

  Diao, Liyang ^a   Marcais, Antoine ^b   Norton, Scott ^a,c   Chen, Kevin C ^a  

^a RUTGERS UNIVERSITY   (United States)

^b CENTRE INTERNATIONAL DE RECHERCHE EN INFECTIOLOGIE   (France)

^c UNIVERSITY OF CONNECTICUT   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CD4 ANTIGEN; INTERLEUKIN 2 RECEPTOR ALPHA; MESSENGER RNA; MICRORNA; MICRORNA 290; MICRORNA LET 7B; UNCLASSIFIED DRUG; 3' UNTRANSLATED REGION; DEAD BOX PROTEIN; DICER1 PROTEIN, MOUSE; RIBONUCLEASE III;

3' UNTRANSLATED REGION; 5' UNTRANSLATED REGION; ACCURACY; ADRENAL CORTEX CELL; ALGORITHM; ANIMAL CELL; ANIMAL EXPERIMENT; ANIMAL TISSUE; AREA UNDER THE CURVE; ARTICLE; COMPARATIVE STUDY; CONTROLLED STUDY; CWORDS ALGORITHM; EMBRYONIC STEM CELL; FALSE POSITIVE RESULT; GENE EXPRESSION PROFILING; GENE INACTIVATION; GENE TARGETING; GENETIC DATABASE; GENETIC PARAMETERS; GENETIC TRANSFECTION; HUMAN; HUMAN CELL; LINEAR REGRESSION ANALYSIS; MATHEMATICAL COMPUTING; MESSENGER RNA TRANSCRIPT ABUNDANCE; MICROARRAY ANALYSIS; MICRORNA MOTIF; MIREDUCE ALGORITHM; MIXED LINEAR MODEL; MOUSE; NONHUMAN; PRIORITY JOURNAL; PROTEIN EXPRESSION; RECEIVER OPERATING CHARACTERISTIC; RNA PROCESSING; RNA SEQUENCE; RNA STRUCTURE; SEQUENCE ALIGNMENT; SEQUENCE HOMOLOGY; SOFTWARE; STATISTICAL MODEL; STRUCTURE ANALYSIS; SYLAMER ALGORITHM; T LYMPHOCYTE; TIME SERIES ANALYSIS; TRANSCRIPTION REGULATION; VALIDATION PROCESS; ADRENAL CORTEX; ANIMAL; CHEMISTRY; DNA MICROARRAY; GENETICS; KNOCKOUT MOUSE; METABOLISM; NUCLEOTIDE MOTIF; PROCEDURES; SEQUENCE ANALYSIS;

3' UNTRANSLATED REGIONS; ADRENAL CORTEX; ALGORITHMS; ANIMALS; DEAD-BOX RNA HELICASES; EMBRYONIC STEM CELLS; GENE EXPRESSION PROFILING; LINEAR MODELS; MICE; MICE, KNOCKOUT; MICRORNAS; NUCLEOTIDE MOTIFS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; RIBONUCLEASE III; RNA, MESSENGER; SEQUENCE ANALYSIS, RNA;

EID: 84964315659     PISSN: 03051048     EISSN: 13624962     Source Type: Journal    
DOI: 10.1093/nar/gku672     Document Type: Article

References (46)

1. Bartel, D.P. (2009) MicroRNAs: target recognition and regulatory functions. Cell, 136, 215-233.
2. Friedman, R.C., Farh, K.K., Burge, C.B. and Bartel, D.P. (2009) Most mammalian mRNAs are conserved targets of microRNAs. Genome Res., 19, 92-105.
3. 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.
4. 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.
5. van Dongen, S., Abreu-Goodger, C. and Enright, A.J. (2008) Detecting microRNA binding and siRNA off-target effects from expression data. Nat. Methods, 5, 1023-1025.
6. Rasmussen, S.H., Jacobsen, A. and Krogh, A. (2013) cWords-systematic microRNA regulatory motif discovery from mRNA expression data. Silence, 4, 2.
7. Sood, P., Krek, A., Zavolan, M., Macino, G. and Rajewsky, N. (2006) Cell-type-specific signatures of microRNAs on target mRNA expression. Proc. Natl Acad. Sci. U.S.A., 103, 2746-2751.
8. Lu, Y., Zhou, Y., Qu, W., Deng, M. and Zhang, C. (2011) A Lasso regression model for the construction of microRNA-target regulatory networks. Bioinformatics, 27, 2406-2413.
9. Stanhope, S.A., Sengupta, S., den Boon, J., Ahlquist, P. and Newton, M.A. (2009) Statistical use of argonaute expression and RISC assembly in microRNA target identification. PLoS Comput. Biol., 5, e1000516.
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. Krek, A., Grün, D., Poy, M.N., Wolf, R., Rosenberg, L., Epstein, E.J., MacMenamin, P., da Piedade, I., Gunsalus, K.C., Stoffel, M. et al. (2005) Combinatorial microRNA target predictions. Nat. Genet., 37, 495-500.
12. Grimson, A., Farh, K.K., Johnston, W.K., Garrett-Engele, P., Lim, L.P. and Bartel, D.P. (2007) MicroRNA targeting specificity in mammals: determinants beyond seed pairing. Mol. Cell, 27, 91-105.
13. Huang, J.C., Frey, B.J. and Morris, Q.D. (2008) Comparing sequence and expression for predicting microRNA targets using GenMiR3. Pac. Symp. Biocomput., 13, 52-63.
14. Le, H.S. and Bar-Joseph, Z. (2013) Integrating sequence, expression and interaction data to determine condition-specific miRNA regulation. Bioinformatics, 29, i89-i97.
15. Bussemaker, H.J., Li, H. and Siggia, E.D. (2001) Regulatory element detection using correlation with expression. Nat. Genet., 27, 167-171.
16. Kang, H.M., Zaitlen, N.A., Wade, C.M., Kirby, A., Heckerman, D., Daly, M.J. and Eskin, E. (2008) Efficient control of population structure in model organism association mapping. Genetics, 178, 1709-1723.
17. Kang, H.M., Sul, J.H., Service, S.K., Zaitlen, N.A., Kong, S.Y., Freimer, N.B., Sabatti, C. and Eskin, E. (2010) Variance component model to account for sample structure in genome-wide association studies. Nat. Genet., 42, 348-354.
18. Zhou, X. and Stephens, M. (2012) Genome-wide efficient mixed-model analysis for association studies. Nat. Genet., 44, 821-824.
19. Kozomara, A. and Griffiths-Jones, S. (2011) miRBase: integrating microRNA annotation and deep-sequencing data. Nucleic Acids Res., 39, D152-D157.
20. 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.
21. Cobb, B.S., Nesterova, T.B., Thompson, E., Hertweck, A., O'Connor, E., Godwin, J., Wilson, C.B., Brockdorff, N., Fisher, A.G., Smale, S.T. et al. (2005) T cell lineage choice and differentiation in the absence of the RNase III enzyme Dicer. J. Exp. Med., 201, 1367-1373.
22. Cobb, B.S., Hertweck, A., Smith, J., O'Connor, E., Graf, D., Cook, T., Smale, S.T., Sakaguchi, S., Livesey, F.J., Fisher, A.G. et al. (2006) A role for Dicer in immune regulation. J. Exp. Med., 203, 2519-2527.
23. Sommers, C.L., Rouquette-Jazdanian, A.K., Robles, A.I., Kortum, R.L., Merrill, R.K., Li, W., Nath, N., Wohlfert, E., Sixt, K.S., Belkaid, Y. et al. (2013) miRNA signature of mouse helper T cell hyper-proliferation. PLoS One, 8, e667092.
24. Sinkkonen, L., Hugenschmidt, T., Berninger, P., Gaidatzis, D., Mohn, F., Artus-Revel, C.G., Zavolan, M., Svoboda, P. and Filipowicz, W. (2008) MicroRNAs control de novo DNA methylation through regulation of transcriptional repressors in mouse embryonic stem cells. Nat. Struct. Mol. Biol., 15, 259-267.
25. Krill, K.T., Gurdziel, K., Heaton, J.H., Simon, D.P. and Hammer, G.D. (2013) Dicer deficiency reveals microRNAs predicted to control gene expression in the developing adrenal cortex. Mol. Endocrinol., 27, 754-768.
26. Waterston, R.H., Lindblad-Toh, K., Birney, E., Rogers, J., Abril, J.F., Agarwal, P., Agarwala, R., Ainscough, R., Alexandersson, M., An, P. et al. (2002) Initial sequencing and comparative analysis of the mouse genome. Nature, 420, 520-562.
27. Kent, W.J., Sugnet, C.W., Furey, T.S., Roskin, K.M., Pringle, T.H., Zahler, A.M. and Haussler, D. (2002) The human genome browser at UCSC. Genome Res., 12, 996-1006.
28. Searle, S.R., Casella, G. and McCulloch, C.E. (1992) Variance Components. Wiley, New York, USA.
29. Lippert, C., Listgarten, J., Liu, Y., Kadie, C.M., Davidson, R.I. and Heckerman, D. (2011) FaST linear mixed models for genome-wide association studies. Nat. Methods, 8, 833-835.
30. Hastie, T., Tibshirani, R. and Friedman, J. (2009) The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer-Verlag, New York.
31. Bartonicek, N. and Enright, A.J. (2010) SylArray: a web server for automated detection of miRNA effects from expression data. Bioinformatics, 26, 2900-2901.
32. Landgraf, P., Rusu, M., Sheridan, R., Sewer, A., Iovino, N., Aravin, A., Pfeffer, S., Rice, A., Kamphorst, A.O., Landthaler, M. et al. (2007) A mammalian microRNA expression atlas based on small RNA library sequencing. Cell, 129, 1401-1414.
33. Huang, B., Zhao, J., Lei, Z., Shen, S., Li, D., Shen, G.X., Zhang, G.M. and Feng, Z.H. (2009) miR-142-3p restricts cAMP production in CD4+CD25-T cells and CD4+CD25+ TREG cells by targeting AC9 mRNA. EMBO Rep., 10, 180-185.
34. Elkon, R. and Agami, R. (2008) Removal of AU bias from microarray mRNA expression data enhances computational identification of active microRNAs. PLoS Comput. Biol., 4, e1000189.
35. Shin, C., Nam, J.W., Farh, K.K., Chiang, H.R., Shkumatava, A. and Bartel, D.P. (2010) Expanding the microRNA targeting code: functional sites with centered pairing. Mol. Cell, 38, 789-802.
36. Martin, H.C., Wani, S., Steptoe, A.L., Krishnan, K., Nones, K., Nourbakhsh, E., Vlassov, A., Grimmond, S.M. and Cloonan, N. (2014) Imperfect centered miRNA binding sites are common and can mediate repression of target mRNAs. Genome Biol., 15, R51.
37. Jing, Q., Huang, S., Guth, S., Zarubin, T., Motoyama, A., Chen, J., Di Padova, F., Lin, S.C., Gram, H. and Han, J. (2005) Involvement of microRNA in AU-rich element-mediated mRNA instability. Cell, 120, 623-634.
38. Helfer, S., Schott, J., Stoecklin, G. and Förstemann, K. (2012) AU-rich element-mediated mRNA decay can occur independently of the miRNA machinery in mouse embryonic fibroblasts and Drosophila S2-cells. PLoS One, 7, e28907.
39. 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.
40. 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.
41. Saetrom, P., Heale, B.S., Snøve, O., Aagaard, L., Alluin, J. and Rossi, J.J. (2007) Distance constraints between microRNA target sites dictate efficacy and cooperativity. Nucleic Acids Res., 35, 2333-2342.
42. Jacobsen, A., Wen, J., Marks, D.S. and Krogh, A. (2010) Signatures of RNA binding proteins globally coupled to effective microRNA target sites. Genome Res., 20, 1010-1019.
43. Foat, B.C., Morozov, A.V. and Bussemaker, H.J. (2006) Statistical mechanical modeling of genome-wide transcription factor occupancy data by MatrixREDUCE. Bioinformatics, 22, e141-e149.
44. Wu, R.Z., Chaivorapol, C., Zheng, J., Li, H. and Liang, S. (2007) fREDUCE: detection of degenerate regulatory elements using correlation with expression. BMC Bioinformatics, 8, 399.
45. Hafner, M., Landthaler, M., Burger, L., Khorshid, M., Hausser, J., Berninger, P., Rothballer, A., Ascano, M., Jungkamp, A.C., Munschauer, M. et al. (2010) PAR-CliP-a method to identify transcriptome-wide the binding sites of RNA binding proteins. J. Vis. Exp., 41, doi:10.3791/2034
46. Nesterova, T.B., Popova, B.C., Cobb, B.S., Norton, S., Senner, C.E., Tang, Y.A., Spruce, T., Rodriguez, T.A., Sado, T., Merkenschlager, M. and Brockdorff, N. (2008) Dicer regulates Xist promoter methylation in ES cells indirectly through transcriptional control of Dnmt3a. Epigenetics & Chromatin 1, 2.